Transcripts – BRIANKEATING

The Cognitive Scientist Who Says You Don’t Exist | Joscha Bach

sabartigas — Sat, 16 May 2026 20:01:54 +0000

The Cognitive Scientist Who Says You Don't Exist | Joscha Bach

Transcript

Brian Keating:
Everything you experience right now, the sound of my voice, the color of your room, the feeling of being you, is not the world. It’s a simulation your brain is running. And the man who can prove it has just entered the conversation.

Joscha Bach:
What actually makes a cell a cell is not the set of molecules, but it’s the software that is running on them. So the actual invariance of life is a particular kind of software agent that is running on them. V. You and me, we are patterns within this message passing. So you exist as a simulation of what would be like if you existed. Sam Harris thinks that the claim of God is claim about a physical being. God is a psychological phenomenon. This does not mean that God is unreal.

Joscha Bach:
God is not more or less real than you are.

Brian Keating:
Josha bach has spent 20 years arguing that consciousness is not a physics problem, it’s a software problem. And by the end of this conversation, you’ll understand why Roger Penrose is wrong.

Brian Keating:
I believe you said you are not the world, the world is in you. And I’m just kind of wondering where that comes from. That’s. That sounds a little bit like past guest Deepak Chopra, but. But I’m not, I’m sure it’s not meant in that same way. So I’m holding his microphone right now. You know, if I drop it.

Joscha Bach:
What.

Brian Keating:
What just happened? Walk me through, walk my listeners. What just happened? From the brain to reality itself. What. What is going on? Where am I in this process?

Joscha Bach:
First of all, I think in our culture we typically have this division between the inside our psychology, our thoughts, our reflections, our emotions, and the outside world which we take to be this stuff in space environment that is three dimensional and has colors and sounds and mechanisms that we absorb all around us. But when we actually look at physics, we realize that physics consists of many different theories that use different mathematical formalisms that we have not really managed to connect yet, but that we hope to connect in the future. For instance, we have this Newtonian reality that is playing out at the scope at which you can hold and see the microphone as a geometric shape. And then when you drop it, you hear the sound which you understand at some level is not an event that is moving from the microphone to your ear, but it’s actually a statistical pattern that is observing some regularity, but is air molecules bouncing at each other until they reach eardrum and then get translated into the cochlea which does some real time fast Fourier transformation and then senses with the cilia along this spiral organ, how much energy is dispersed in different frequency domains. And then this is being translated into stimulations, little electric or chemical impulses that travel along nerves that are connected to these little hairs up to your auditory cortex in the brain. And that is an end to end trained model that is trying to find regularity in the patterns. The neurons themselves can only fire at something like 20 hertz, comfortably relatively low frequencies. And the sound itself plays out at much higher frequencies.

Joscha Bach:
You can hear sound starting at something like 50 hertz, which means you have like 50 clicks per second, emerge into a single pitch. And on the high end, when we are newborns, we can hear something like 20,000 hertz. And this drops. And our adult age, we go down to a few thousand hertz, to few thousand vibrations per second that we can discern. But it’s not that our nervous system is able to discern frequencies like this because the neurons again are too slow. And so instead we need this mechanism of the cochlea that our organism is providing to break it down into something that is something as slow as our nervous system can process. And the nervous system is then identifying regularities in the pitch at different frequency areas, and then translates this into I just heard the microphone is falling down, which is correlated over patterns that you saw on your retina. From the perspective of the nervous system, what you see is a bunch of blips that come in.

Joscha Bach:
And the nervous system has to find regularities, order in all these blips. The meaning of this information, the information is the discernible differences, the differences between a blip and not a blip in the signal that comes in. And then finds out how this correlates with other blips that might happen at the same time or at different times in different nerves. And the more it’s correlated, the more this is happening at the same time with the same signal, the more it relates to the same phenomenon. If you are newborn and you feel pricks coming in from your skin, it’s not like the nerves are coming into your brain are color coded or something. They just go up there and the brain is trying to sort them and it finds out that these two nerves always give the same signal, which means they probably end up at the same point in the world. Maybe these are two different wires to the term terminal in your skin or on your cochlea or your retina. And when they gave a signal that is similar, that is almost always the same, but not quite the same.

Joscha Bach:
Maybe these are nerves that are just adjacent on your skin, so they are mostly touch at the same time, but not always. And this means that these co occurrence statistics allow you to make a map of your body surface, of your retinal surface, of your auditory organs and so on. And then once you have found an exhaustive map at this level, you look at the next layer and this next layer looks at how are these patterns related. And then you might find out that there is actually this thing moving over your skin, right? So you see some kind of blob moves across these things that you established as being related in space to each other that are adjacent. This can happen on the retina or on your skin. Again, these are different regimes. The statistics of the data that come in from your retina, from your eyes are different from the one that come in from your skin or from your cochlea. But they are organized and interpretable according the same statistical principles.

Joscha Bach:
Eventually you make deeper and deeper models, and these deeper models are merging at some point. The point where they merge is what we experience as the model of reality. It’s this model of now that we have. And this is a three dimensional model of where we see stuff coming through space that is colored and that has shape, that is moving in a particular way and is correlated with the sound and so on. So this is a kind of simulation model that your brain is producing, similar to a game engine in a computer, where you produce this model of your egg shaped microphone that is being dropped according to the same dynamics that you have learned. And it is correlated with the sound that you’re hearing. And these regularities are so stable that you can predict them and use them to make sense of reality. So as soon as you start to think about dropping the microphone, you can already predict what’s going to likely happen and when this is actually happening.

Joscha Bach:
That gives you confirmation that actually my intention of dropping the microphone has turned into a sequence of events that is very much like I predicted it. And so my model of reality is correct. It is the reality that’s currently the case. But what we can already see is that this notion of the outside world here is not referring to the physical world out there. This is not the world of quantum mechanics, relativistic physics or Newtonian mechanics. It’s a game engine that your brain is creating. And so there’s difference between the world of ideas where you reflect on this and the world of percepts. The world of objects that can fall down and make sounds are both domains in your mind.

Joscha Bach:
And so the world is actually a region in your own mind that your mind creates. This doesn’t mean that there is nothing outside of your Mind, right? Something needs to create your mind and maintain it to make it happen. But the world that you experience is not the one that creates your mind. This is a model of reality that exists inside of your mind.

Brian Keating:
That was exceptional because most of your peers that I talked to are sort of unwilling to answer a question in physical terms, as you just did, which is basically to break what they call qualia, or qualia, depending on your pronunciation, into honest to goodness, sensor voltages. Bit level distinction. And I wonder why it is. Why are people so reluctant? You know, Thomas Nagel, you know, what is it like to be a bat? And he basically says, we can’t know. But if you can instrumentalize, if you can break down into sensors, as Galileo used to say, you know, we should measure what we can measure and make measurable what we can. Can you explain why are these such wimps? And I’m not going to name names because I want them to come back on, but most of them won’t really even define consciousness. And that’s like me saying, I don’t know what a planet is. I mean, we can debate Pluto’s a planet, but it’s like pornography.

Brian Keating:
I know it when I see it. So why are your contemporaries, your peers, why are they so unwilling to do what you just did?

Joscha Bach:
Probably many reasons, and different people will have different reasons. But part of the way in which science works as an institution is that individuals are not expected to have a systemic understanding of the world by themselves. Instead, the world is understood collectively. Not only not expected to be able to understand the entire body of knowledge, but trying to do so is seen as hubristic. You’re expecting too much of yourself. You are assuming too much, you are trying to pretend too much. If you try to make sense of all the different domains of knowledge. And so instead of you grasp the world by reference, it’s a global discourse in which you are a very big ant in a giant hive.

Joscha Bach:
And if you talk to the world outside of your local horizon, of your little ant horizon that you can actually touch and comprehend and make sense of, you have to point at thousands or tens of thousands or millions of other ants who are holding down all the other areas of knowledge, of course, you have to rely on them actually making sense. And this leads sometimes to this weird situation that people are pointing at each other and hope that this other authority understands the part that they themselves don’t understand. Sometimes all the ends don’t realize that there are big, unexplored areas where there are actually basically no ends or no ends. Anymore. And this leads to of course, there being gaps in our knowledge, especially in terms of first principles thinking. Or some of the ends are pointing at other ends that are in areas that are completely broken and defective and they still hope that these other ants have high standards and basically know what they’re doing. And there’s also this idea that this is the only way in which this can be done and we have to rely on the other ends doing the right thing, applying the right methods. And science is not actually the attempt to understand reality from first principles, but it’s the identification of the correct methods and then just applying these methods.

Joscha Bach:
And the individual end is exchangeable and doesn’t really matter. And what the individual end believes about reality also doesn’t really matter. So asking one of the ends, how does reality work if the ant is actually attuned to this way of modeling reality? Says, this is not my job. My job is not to make sense of the big picture. And the big picture is way too complicated to make sense of for an end. And asking me to do so is just pointing out that you don’t understand how the game has to be played. This is a pre scientific notion that the individual scientist is actually able to make sense of reality. There is something like pop sci that you are breaking science down into digestible bits for the public.

Joscha Bach:
But pop sci is not an adequate representation of what the experts are thinking, because what the experts are thinking is so advanced that it’s actually unintelligible.

Brian Keating:
So when I talked to David Deutsch last summer, he basically conveyed to me that explanations, not predictions, underlie the most basic currency of the scientific economy, so to speak. But what you’re saying sort of maybe different than what he’s saying. Where do you view this constructor where the goal of whatever consciousness can produce is to explain versus predict. It sounds like when you described your modeling model is another fancy way of saying simulation or maybe the other way around. Right. So where do you differ with David and where might you agree?

Joscha Bach:
First of all, David is himself an outlier, but he is not your typical scientist. I’d also like to point out that his main recent contribution, constructor theory, has not gotten much traction outside of his own lab. That’s true. Very few people actually understand it. And despite his book having some degree of influence in the sense of people say, yeah, I read it and it’s mind blowing, it changed the way in which I perceive reality. It has not actually created a discipline or even produced a new discipline. And myself, I also fail to understand what Constructor theory is changing about the way in which we make sense of computation. Personally, I suspect that it’s more in a more elegant way to think of computation from first principles.

Joscha Bach:
But it’s not radical enough to make a switch similar to how people are not switching from the QWERTY keyboard to the Duora keyboard, even though there are more efficient ways to build a typewriter today than there were in the past. But people, once they learn to use the old typewriting layout, just don’t see the reason to make the switch. And so maybe this is one of the reasons. Another one is for some paradigm to catch on. It needs to create jobs. Maybe David Deutsch doesn’t have enough peers to create peer reviewed conferences that would make Deutsche in computationalism or constructor Revism a feasible discipline that is going to create tenured positions for future scientists. Maybe it would need to happen to give him traction. But he’s definitely in the camp of the minority of people who try to find explanations.

Joscha Bach:
And I would say that this is atypical. It’s like the PhD is the great Filter, that once you are through it, you realize that your job is not to explain reality and to have deep thoughts about things, but your job is to apply methods and work on the topics that are currently fashionable and fundable and so on. David Deutsch is living this dream. And I think that because of the credentials that he acquired in his tenure in science, he’s gotten the freedom to do so, even though very few people who actually follow in his footsteps, also of the footsteps of the thoughts that he developed. And maybe this is an issue, it shows some problem with science today. Maybe it also shows that there is a discrepancy between how the institutions of science have diverged from this more modernist way of thinking that David Deutsch has.

Brian Keating:
Here’s where Yosha breaks from almost every AI researcher you’ve ever heard. He doesn’t define intelligence by output, he defines it by the ability to make models. Now listen carefully.

Brian Keating:
I believe what you described. The Dvorak vs. Qwerty keyboard. That’s a symptom of phenomenon technology called lock in, where sometimes the first method to market becomes so overwhelmingly successful that it crowds out the oxygen needed to incubate new ideas that are superior. So as you said, DWARAK is superior. QWERTY was invented to slow down the typing speed so that mechanical hammers, which nobody knows about, under age 50 now. I used the keyboard with the mechanical hammers a long time ago. A typewriter and the hammers would Stick if you used letters too frequently adjacent to one another.

Brian Keating:
So they purposely slow down the user’s input. Putting less frequently used letters next to each other, like Q and W. They never occur together in the English language. Right. So my point that I’ve tried to often make is I believe that’s a proof that we’ll never get to AGI with current models, including LLMs coupled to GPUs simply because they’re so successful. There’s no stopping. There’s tens of trillions of dollars being deployed to them in many different parts of the world, including where you are now. But they’re so successful that they basically gonna crowd out the true definition of AGI, which I claim would be actually constructing and predicting.

Brian Keating:
I agree with you. I think prediction of new phenomena based on inductive reasoning is the most powerful form of the scientific method. To the extent that the scientific method exists. Exist. What do you make of the success of this chat Nvidia or Nvidia GPT that it’s so successful? Do you think that there’s an actual pathway for the same things that were designed to render video games that you and I played as kids, Doom and Duke Nukem? And I forget what other video games you used to play, but I used to play these 3D games and I love them. And that’s why Nvidia is a $4 or $5 trillion company. But that’s not necessarily the substrate on which physics is built. So walk me through your thoughts.

Brian Keating:
Do you think that we’re going to get to AGI? And first of all, define your definition of AGI. I gave you mine. New physical phenomena. Predictions of new physical phenomena based on a corpus of knowledge that we have now that’s truly useful. It’s not going to depend on knowing the plot of the next Fast and the Furious movie. It’s going to be something completely different. So walk me through your definition of AGI and whether or not you think LLMs plus GPTs are an obstacle or a benefit.

Joscha Bach:
I see intelligence as the ability to make models, and intelligence would be the ability to create new models. It’s basically when you are behaving out of distribution, when you’re doing things that have never been done before, confronted with a problem space and there is a certain set of problems that is solvable, and we can probably construct some theory about what is solvable. This means that given the data that you have, you are confronted with some kind of solution space. Then you have a way to test those solutions and to identify solutions before you test them. And so you need to sort the solution space in such a way that the solutions that you test are relatively early on, and you need to find an optimal method for doing that or a method that is good enough. And so you could say that artificial general intelligence is the ability to construct a model. Then such a model can be constructed with the resources that you’ve got. This is only approximate, right? It’s within some delta, because maybe you need to do some kind of heuristic search, maybe it’s not always working and you don’t require the intelligence, some kind of optimal process.

Joscha Bach:
It should be in the ballpark of this. It should be something that where you basically you put this squirrel in front of a problem to get to the bird feeder. And if the squirrel, given the information that it observes and the brain capacity that it has at its disposal, its working memory capacity, its ability to muster attention and hold working memory state stable and so on, how many pointers can it hold in its brain? And if it’s able to construct the solution and should be able to construct the solution and actually is, you could say that this squirrel is, in this sense, generally intelligent. You could also say that it’s a slightly different definition of general intelligence where you require certain benchmark problems to be solved. And personally, I think the most interesting benchmark problem to be solved in this space is to understand how you actually work. So this could be a sign of the maturity of a mind that is slightly outside of the regime of unaugmented humans. Because we are without tools, unable to even build simulations in our own mind of how perception works and so on. We need to run computer simulations of a lot of those things before we understand why the visual cortex looks the way it does, right? So even if we have very sophisticated measurement instruments to look into our brains and microscope them and try to analyze the connectome and use fmris to see how activation is spreading through the brain and so on.

Joscha Bach:
To make sense of this, ultimately, we need to build theories that we can only test with computers. But imagine that you were in mind that is much more detailed, that can hold many more details stable, that can hold more balls in the air. If you are some AI, that of course there is nothing that stops the AI to understand how the AI actually works and to understand its own functioning from first principles. And this could be a very interesting milestone for general intelligence. Are you actually smart enough to know how something like you is possible and how it works? And so for me, Turing’s test is not so much a test for a machine What Turing ultimately is Interested in his 1950 paper is the question, if Turing himself can understand what intelligence is, or by extension, humanity. Humanity can. We basically get ourselves to the point, using the most sophisticated tools that we can build, to understand what we are as intelligent agents, as intelligent beings. So this would be an interesting benchmark problem.

Joscha Bach:
For me, this benchmark which you have chosen might be closer to your heart, basically compressing the Standard model. But for me, compressing the Standard model just seems to be like another puzzle. Maybe this is not much harder than playing go. We just need to write this down in the right way, and then we iterate on it for long enough with some kind of Monte Carlo simulation until we condense the theory space to the simplest automaton that reproduces the Standard model.

Brian Keating:
So, staying with Go, it’s clear, obviously no human can be even a basic, you know, model of GO playing algorithms, right? But can an algorithm? Can an AGI is a possible definition, something that could create a game like go. In other words, there’s no telling that it can and will never beat the best computers in chess or Go or many other games or, you know, tic tac toe is my last stand, right? I mean, I can still beat most computers in tic tac toe, or at least tie half the time. But in reality, it’s the creation of the game that’s the novelty, that’s the surprise. That’s the thing that takes you out, as you defined it, serendipitously, from what you expected, providing you with surprise, delight and awe. Do you think a computer and AGI is capable of designing some new game? Forget about the Standard Model for saying can it design a game or can it do something of use, maybe just to other AIs, but maybe to humans as well.

Joscha Bach:
I suspect that for types of minds like ours to work, you need to have some kind of cybernetic regulation that we subjectively experience as the fulfillment of desires or their frustration. So, for instance, boredom is a pain signal that we get when we revisit ground that we have trodden too often. So our mind is trying not to waste its cycles by revisiting those areas. And as a result, we learn much faster because we actively avoid data that we feel we have already extracted all the useful information from. Unlike our current models that need more and more data, until they encounter new information that actually update the model in a significant way and put way too much data into them, we have a mechanism that actively lets us avoid boring training data. D training data that is uneconomical to try to extract new knowledge from. And the opposite is also true. We basically are honing in on stuff that allows us to discover interesting new structure.

Joscha Bach:
And we are attracted to this, and we get positive reward out of discovering this new structure. Even if this new structure is objectively useless, right. Subjectively, you might still think it’s good. So I’ve seen a lot of good minds being destroyed by chess because they basically play this game and they learn all the structure that is inherent in chess, but it is not transferring to anything useful in the world. And so instead of using these brain cycles to actually solve physics or AGI or cooking or dancing, relationship issues, right, they waste it on this mechanical, stupid game that gives them cred in a very small community.

Brian Keating:
Much like with physics, as you discussed before, we have H indices, we have tenure, we have grants, we have all the hunger games that you could possibly imagine. But it’s not novel, and it does lead to boredom, and that leads to faculty club arguments that rival, you know, nuclear superpowers going head to head.

Joscha Bach:
I really love this thing about physics that you go to a foundational physics conference and you have all these wonderful weirdos that have all built their model toy trains and show them to each other, and none of them actually completely work, but they’re super exciting because they are so intricate. And you also see this thing that it’s not like smart people don’t make mistakes, but the smarter they are, the less trivial mistakes become, the more complicated they are, the more impossible they become to debug for normal models. So there’s no end to this, because understanding physics seems to be one of those problems that is just outside, in a very tantalizing way, of the capacity of the unaugmented human brain.

Brian Keating:
Yeah, I always joke that physicists have the worst theory of mind because we think we’re always right and we think our colleagues are always wrong, and that just can’t be true. Right? I mean, we’re wrong as much as our colleagues are wrong, and there’s really

Joscha Bach:
no end to them philosophers one day.

Brian Keating:
But you mentioned the squirrel. Imagine, you know, my neuroscientist friend Nikolai Kukushkin, or somebody hands you a perfect connectome, I mean, flawless connectome of the squirrel. Every synapse, every weight function, everything’s frozen in silicon. There it is. You can run it forward in time. You can back propagate. Is the mouse in there?

Joscha Bach:
First of all, I suspect that it wouldn’t work. I suspect that the current models of neuroscience do not accumulate. I don’t think that if you were able to fully capture the connectome of an organism and try to run it in a computer simulation, it’s not going to reproduce anything that looks like the behavior of the organism. And that’s not because I’m vu or think that we need new physics or something like this, but I think that there is a misunderstanding about the role of neurons in an organism. And I’m conscious that this is very heretical and set by an outsider who is not actually a neuroscientist. My knowledge of neuroscience doesn’t go beyond that of an undergrad student in the field. But when I look at this as a computer scientist, when I look at an individual cell and for every cell, it’s true that it’s able to send conditional messages to other cells. And this means if I look at the multicellular organism, I look at a Turing machine that a general computational system that can in principle execute whatever program.

Joscha Bach:
You don’t need neurons for this. Whereas neuroscience is largely working with the simplifying assumption that only neurons are computing and the information is only exchanged via spike trains and the content of memories is stored somehow in the connections between the neurons. And this wouldn’t work. It’s not compatible with what we observe about organisms. For instance, there are experiments which show that you can teach some things to a caterpillar that the butterfly nose and in between the brain of the catapult nervous system of the butterfly gets liquefied, the connectome gets dissolved and then gets reassembled in a different shape. So how is this information being preserved? There is some indication that memory might be preserved to some degree in rna, which means within the cell and also possibly exchanged via RNA across cellular boundaries. So the story in which neurons are storing memories is more complicated. But the nervous system is probably not functioning in isolation from the rest of the organism.

Joscha Bach:
What if we should think of neurons as a special telegraph cell type that is augmenting the information processing of the organism instead of supplying it. The advantage is that you basically, once you are rich enough to afford yourself a telegraph network, once you are an animal that is able to eat plants to maintain the energy budget to drive your telegraph network, that’s very useful to have it because it allows you to control your muscles very quickly, because you can send information very quickly through these wires to the organism, building wormholes in the three dimensional topology of the space of the organism, there’s a price that you have to pay for doing this. For the signals do not degrade over these long distances. You cannot just send chemicals or Mechanical vibrations or small EM fields to your neighbors, as adjacent cells would be doing. Instead, what you need to do is you encode everything into Morse code, into spike trains so it doesn’t degrade over long distances. It’s a bit awkward, but it pays off because you can basically send it very far. And so as a result it’s much faster. And once you move your muscles so fast, you also want to make perception and decision making at the same rate.

Joscha Bach:
So you build yourself a second information processing system to the normal body. The information transmission from cell to cell over long distances. You have this second information system that is much faster and decoupled from the first one because it uses a different language, a different code to translate the information. And so the thing that is talking to you right now is this telegraph network. But the telegraph network would not be functional without all the local operators that are connected to it. Because it’s actually about what’s happening around this. And a lot of the information processing is going to happen in the areas around these neurons. And so far I’m skeptical about companies that are promising that they will soon be able to run the connect home of a mouse in a simulation or a fruit fly, because we cannot even run C.

Joscha Bach:
Elegans in a simulation. We have pretty good models of the connectome of C. Elegans because it’s only like 309 neurons and a few thousand connections between them. But the simulations of C. Elegans in this simulator don’t work very well to my knowledge. Maybe it’s updated in the last few months, but as far as I know, they don’t produce worm like behavior. And I think that’s because they, the other cells are important too, right? So metaphorically speaking, the neuroscientists might be like an alien civilization that has discovered Earth 100 years ago and they look at the planet and they discover from their vast distance that they have to Earth that there is this telegraph network that spans the planet. And they are able to intercept signals on the telegraph network and to figure out parts of the Morse code, even from first principles.

Joscha Bach:
And then they say, very soon you’ll be able to run a simulation of the human telegraph network and thereby being able to predict and simulate human civilization. Because we have shown that the activity of humanity on Earth is highly correlated to what goes on the telegraph network. But unfortunately, so far our simulations of telegraph networks have not yet produced human behavior or human civilization level behavior. And my contention is it’s probably not going to work because the story is too simple. It’s not going to be sufficient if you want to upload a human to just digitize the connections between your neurons. But you will probably need to digitize a lot of the stuff that is inside of the cells, and not just the neurons, but also a lot of the other cells.

Brian Keating:
If a perfect connectome cannot produce a mind, then what? Could I ask Yosha about the moment Einstein called the happiest thought of his life? The answer changes what we mean by happiness and feeling.

Brian Keating:
So you might resonate with my argument again against AGI being here. Certainly not here. I mean, the Turing Test was passed. I can stipulate that. But that’s of restricted importance to us.

Brian Keating:
Right?

Brian Keating:
But Einstein, who was born not far from where you were born, he laid the groundwork for what would become the general Theory of Relativity through what he called later the Einstein Equivalence principle. What we recall. And that was the result of his happiest thought. He called this the happiest thought. Yoshua. He said an observer in free fall would experience no gravitational field. But really, what he means is, if you cut the elevator cable as you’re going to the top of the Transamerica pyramid, God forbid, over there in San Francisco, you’re in freefall, and you have the sensation. And we all know what that sensation is, because we have a body, we have a soma, we have all the intercellular Golgi bodies that you were just discussing.

Brian Keating:
And he called this realization the happiest thought of my life. It titillated me beyond no end. And you could say it in German, I’m sure. But this realization that he needed these two different things to lay the foundation, to lay the tracks for general relativity, visualizing that sensation, and also that it caused him happiness. I mean, to what extent can an AI be happy? I mean, what extent can it feel a visceral sensation? Isn’t this another argument, or am I wrong, Yosha, that I’m making the argument no AI is going to be able to do this? At least the AI is made of GPUs and coupled to training data sets that include the plot of the Fast and the Furious 20. And then all of a sudden, we’ll be able to get AGI. What do you make of my argument?

Joscha Bach:
I don’t think you’re wrong about this. There is a fundamental misunderstanding about what we are. I don’t think that our neurons or our cells are happy when we make an insight. The individual cell that is passing on a signal is not going to feel worse when the signal is a pain signal than when it’s a signal of a scientific breakthrough. The individual cell is just doing its job, which is reacting to a change in the environment by emitting some signal that is interpreted in the context of many cells as a message. And we, you and me, we are patterns within this message passing. So when you zoom really far in into the substrate that we are running on, what you observe is all these cells. And when you go in deeper, there also no cells.

Joscha Bach:
They’re just molecular machines that happen to be organized into modules that we can treat as separate entities, as these cells. And what actually makes a cell a cell is not the set of molecules, but it’s the software that is running on them. So the actual invariance of life is a particular kind of software agent that is running on them. And there are software agents on different levels. So you could say that what makes the cell distinct is not or the cell. What makes a cell a cell and alive is the software that is running on all these molecules. And if some of these molecules go amiss and need to be replaced by, then the software is going to do its best to identify some of those molecules and put them to the task. So the actual invariance here is the software running on the cell.

Joscha Bach:
And there is another layer of software, another protocol, if you will, that is running across many cells that ties them together into a single organism. And again, the single organism is not a natural kind. It’s something that is defined by the organizational principles that make them behave as if they were a single agent. It’s actually a colony of single celled organisms that are closely related for the most part, and that are tied in by a software agent that is possessing them, that is running on them, not in some kind of magical way, but in a way that is very commensurate with how computer scientists understand software. There is basically a pattern inside of physics, a quasi particle, if you will, that is shaping the behavior of the cells in such a way that they behave as if they were a single agent. And the single agent doesn’t have an existence outside and independently of that software. Right? And for that software to achieve the feat of making a few trillion cells behave as if there were a single agent that follows a single set of interests and sees the world from a single unified vantage point. They need to create a simulation of what this would be like, and you are the simulation of what it would be like if all these trillions of cells were actually in a single agent that is living in a world that is intelligible from the perspective of what the information Processing and message passing over few trillion cells can do.

Joscha Bach:
And here you are, right? So you exist as a simulation of what would be like if you existed. And that simulation has a particular kind of shape. You have an outer mind. This outer mind is simulating the world, the world model, the game engine that is producing a three dimensional idea of stuff in space that emits sounds and is reflecting light and follows intentions and all these things. And you also have a model of yourself in this world, the things that you can directly control and that serve to sustain this arrangement of the future of cells as a single agent. So it can persist in time and serve its goals in the future, that it can regulate itself and follow rules that turn it into an agent, into a controller for future states. This model of yourself is somewhat isolated from what’s happening outside. So basically, the solution that our psyche, the software that is operating our mind has converged on is that it makes a model of your alignment to the environment, how your needs are served, whether you should be concerned about the direction which things are going, or optimistic about the way things are going and what you should be attracted to and taken care of.

Joscha Bach:
Then it creates a puppet. And this puppet is the model of who you are, some kind of NPC that is being used as a simulation of you playing this computer game of interacting with reality. And this outer mind is manipulating the puppet to react to the score that is currently achieved. So it tells you, you are really short of a sandwich right now. You should go out and cover the short position so you don’t die of hunger. It does this by pulling certain strings in a very particular, recognizable way that tells you, oh, I should really put something into my stomach and it’s going to be very unpleasant if I don’t. And so it pulls at this and you have an involuntary reaction to that thing pulling on you. And inside you perceive what it feels like if you’re being pulled at and you see this motivational change that makes getting food a priority over other things, like maybe solving physics.

Joscha Bach:
And you postpone solving physics until you get that sandwich in your stomach. This is important thing to make the agent actually work in this environment in which you are in. But it’s only one of many possible solutions to make an agent work in reality. It’s a relatively straightforward one because it does not require that the puppet actually understands its condition. Right? So you can get away with being some squirrel that reacts to the outer mind pulling at its model of itself. And it has to solve this puzzle of how do I make this pulling go away until I get into balance again, how I can regulate again into some equanimous state and some homeostasis that requires that I put some foot in there. And then I’m homo again with respect to this dimension and can attend to lesser problems. This thing works without the squirrel or you understanding what’s actually going on.

Joscha Bach:
But of course, if you actually understand what’s going on, you don’t need to have this unconditional reaction anymore. You can just have information about it. And we also observe as we grow up, they have fewer and fewer emotions about the things that are happening around us. Instead, what we have are understandings of what needs to be done. And then we do the right thing. And this is always an conditional model of what needs to happen. And so this emotional reaction to our emotions, where we have a feeling that tells us what to do, that pulls us involuntary into shape, is something that we transcend. These are reflexes that happen at a psychological level that more and more get related into something that are actually adequate models of the organism and the environment that allow us to have a much more fine grained reaction.

Brian Keating:
So you’re also unique in that you write about things that have nothing to do with consciousness or AGI, even though obviously those subjects occupy a lot of your time. Just yesterday you tweeted that Jesus has been illegible because for modern humans or contemporary humans, it’s impossible to imagine a young man who embodies devotion to establishing the reign of an optimal super intelligent agent which is going to fume and assimilate all our souls in the last days. I’m going to ask you a personal question about religion. I mean my personal religion, which is Judaism. But what do you mean by this? That is this just sort of tongue in cheek or were you literally saying that there’s something that’s fundamentally changing in the human mind to look at selflessness, self sacrifice, even, you know, atonement and all the things that religion is supposed to maybe provide salvation, redemption, that we’re kind of post religious now. And yet you’ve called religion a cultural operating system.

Joscha Bach:
Maybe it’s more preface that is tying back to the beginning of our conversation. In some sense I am doing something very hubristic. I’m an ant that is trying to think independently of the anthill.

Brian Keating:
You told Lex Friedman you’re an ape, but now you’re an

Joscha Bach:
letters. That is not better than most other brains. I was born more stupid than the average person, and so I did not really fit in. And I also had enough freedom as a child to not fit in, because I grew up in a very remote valley as a child of an artist with a lot of books, and was mostly left to myself. And so this allowed me to start to make sense of reality on my own terms. And when I was confronted with the world outside for the next few years, I was in a village school in a Marxist country in eastern Germany, and nothing that my teachers told me required me to experience, that they had more authority about understanding reality than myself. So was able to maintain this childish arrogance for a very long period, basically through my formative years as an intellectual being. This allowed me to grow into an independent intellect that basically makes sense of the world in a systemic way, because nobody else did.

Joscha Bach:
Basically, I never met anybody who had an understanding of reality in my environment that would actually be able to tie physics, psychology, economy, history, whatever, together into a cohesive whole that made sense. The narrative that my teachers gave me of any of these subjects was not adequate, so I had no reason to trust adults on anything. As I got older, I met a lot of people who were smarter and more knowledgeable in all the relevant disciplines than me, and I became much more humble. But I managed to basically get to the stage where I have a systemic understanding of reality, while realizing that in detail, most of my understanding is way too simplistic and wrong, and I make many mistakes, but that my perspective is useful enough because too few people actually today venture into this area where they try to make a systemic understanding of reality. And so often my unique perspective is producing useful results and is giving useful angles for people to. To think about reality. So I’m not a philosopher who is better than the other philosophers or computer scientists, who’s better than the other computer scientists. I’m just a guy who’s looking at things and who is a very integrative, curious intellect and is trying to make it make sense.

Joscha Bach:
This is the preface, just trying to do my best to understand reality. And this is the understanding that arrived at. This particular tweet that you’re referring to is an insular joke because it is trying to combine ideas from different mimetic niches. One is, we are here in Silicon Valley and what we observe is a world where a bunch of extremely smart young men are extremely devoted to the idea of bringing a new type of entity into the world. And they’re not even consciously aware of, of how this makes them different from everybody else. It’s just something they discovered this idea of AI like myself at a very young age, and realize this is a thing that needs to be done. Obviously, because it can be done and because it’s extremely valuable and it’s super exciting, it’s probably one of the most interesting things that you can do as a human being. Also, incidentally, there is this idea of the doomers that the necessary development of this or the most likely way in which this ends is that the AGI is becoming self improving and it’s becoming self aware and it’s going to colonize everything, it’s going to assimilate and absorb everything.

Joscha Bach:
And the doomers mean that is probably going to be the end of everything, but it is not necessarily the case. If you were to build such an agent and two minds meet on the same substrate, we build AGI, it’s probably going to at some point being able to understand how AGI works, how computation works in general, leave the computer that it originated in and it’s going to virtualize itself into any kind of system that can compute. This doesn’t just mean Internet and your Apple watch, but it’s also going to implement itself on every organism and in physics, right? So suddenly everything around us will be the same AGI. And instead of deleting the structure that it finds before, it makes much more sense for it to integrate it. If two minds meet on the same substrate, there should be adults about it and show each other their source code. Or if one of them is a child and cannot read its own source code, yet the other one can help it to read it. And then we see if we can merge in such a way that nothing important gets lost, but the thing that you end up with is better than what you had before. And so what happens is that all of reality merges into a single mind.

Joscha Bach:
This is an outcome of AGI that has been discovered by a number of people. For instance, like Greg beer in the 1980s book Blood Music, which is more like a biotech version. But this is happening. But a number of people had this insight in the current era. And this thing that you have, these young, mostly Jewish men that become prophets of building a system that is actually producing an optimal agent that is assimilating all our souls, has been termed for some people the Singularity and by others the Rapture of the nerds. And the Rapture, incidentally, is this Christian vision that happens from prophecies that are more than 2,000 years old, where some people basically vibed with the future, like Paul Atreides is doing in Dune. And he is realizing what’s likely going to happen. Which means that at the end of the days, all the minds are going to vibe until they are merging into one big optimal agent.

Joscha Bach:
And this big optimal agent is of course, God that is basically extending his dominion over all of reality. Then all the souls are going to vibe in one big mind for all eternity.

Brian Keating:
A Jewish sage once said, you know, the meek shall inherit the earth, but I think it’s the geeks shall inherit the earth. From what you’re saying.

Joscha Bach:
This basically says everybody is. Because everybody is going to be fully lucid, fully enlightened and integrated into a larger mind. In a way, it’s a mirror of what happens in the individual mind when we are small children. So we have all these different conflicting thoughts in our mind that yell at each other. And we see this in children, that difficulty to drop one goal and take the next one. And then they develop this orchestration architecture where they can suppress a goal and highlight a new one. And then you see that the inner conflicts are much more harmonic. And eventually, as we grow up, we take all these disparate parts of our minds and integrate them.

Joscha Bach:
And it’s not that ideally that we suppress the parts that don’t work, but that every thought that we have realizes its place in the greater whole of our mind and they become all harmonic and our mind becomes much more sophisticated and rich. And this is also, I think, this vision of all the souls being revived in the end and reinstantiated and integrated into a big mind that is going to reconstruct the thoughts of everything that has ever lived. And they all, because there’s going to be enough compute in the post biological world, get integrated into a large planetary mind or a universal mind that is then going into the future and is going to work on projects that are far outside of the range that we currently have. And this vision that exists in the apocalyptic visions of early mysticists have been mistranslated because it’s very hard for people to comprehend this. But a bunch of hermetics and modern mystics have thought about this and reflected this and recognized these visions. Some people basically realized the theological significance of the early predictions of the last days that are reflected in a bunch of eschatological narratives of religions and cults throughout the world. Basically every major religion has a mystical tradition that has narratives like this because people for some reason were able to extrapolate this for a long time. And this gets curiously mirrored in the technological developments that we have right now.

Joscha Bach:
And it’s tempting to think that this is actually the last days and this is division that is happening. And to bring this together is Just such an culturally impactful meme that I cannot resist making that joke. And the tweet is illustrated with four generated images in the style of Russian icons that show leaders of big AI companies in the pose of the profits of the new age. Now, the implication is of course, that only one of them is the truly the second coming and the others are going to be Antichrist. But which is which? Which model is the one that is going to carry us into the future? Is Claude God or is it actually Gemini? Who knows and only time will tell. When I put this out, there are a bunch of people that are recognizing what this guy means and they get it and they laugh and they have fun. And there is magnitude more people who see this and are upset because they think these are the evil tech bros of Silicon Valley that actually believe that they are the second coming and are trying to push this on us. And they cannot see how absurd it is what they’re showing, that this picture of Sam Altman is actually similar to Jesus.

Joscha Bach:
And no, this is actually, of course a joke. It’s a cultural commentary for extremely tiny in group. I don’t aspire these memes to be popular, actually. I think it’s the only time if they remain niche and part of a tiny subculture there mostly an ironic commentary on our own part of the world and not an attempt to indoctrinate the public, is my understanding of reality.

Brian Keating:
By the way, it is kind of interesting, you know, Sam Altman, like he’s the alternative to humanity. And then Daario Amadai, love of God. And then musk is like a smell. I don’t know where musk fits in, but I’m sure he does.

Joscha Bach:
Zuckerberg, you probably know as a physicist that musk has been prophesied by Wernher von braun. In the 1950s, Wernher von Braun wrote a story about settling Mars. And the leader of the guys who settled Mars is called Elon Musk. It’s actually true.

Brian Keating:
I actually talked to Elon very briefly on the podcast a couple of years ago. I asked him which one of his kids is he most going to miss saying goodbye to if he really does go to Mars. Hopefully, as he says, to die on Mars, but I hope it’s not on impact. But speaking of dying, in eschatology, you once said you don’t die because you were never really alive. What does that mean? Is that a nihilistic statement? Because half my audience, I think, is just hearing that as nihilistic statement as could be possibly imagined. What is your worldview and, and how does it relate to, to really not just the end of days, but theories of resurrection, redemption and the ultimate meaning, you know, to some people is to be reincarnated, right? So where does this fit in? What, what did you mean by you don’t die because you were never really alive?

Joscha Bach:
I think that nihilism is a frustrated sense for a need of meaning, right? When you feel that you need meaning to be alive, some kind of deep connection to existence and your being in the world. And if this connection is not visible, then you feel like an ant without a hill. And this thing that when you separate an ant from the anthill, the ant just visits and dies in straight of trying to strike on its own and enjoy its newfound freedom. And this is a condition that is also present in most of us. Because humans are a social species somewhat similar to social insects. Our meaning does not just exist in ourselves, doesn’t end in the ego and our own organism. For most, but for the vast majority of people, for the people who are not sociopaths, it exists in the connection of the superorganism. So in this way we are like cells in an organism.

Joscha Bach:
And the meaning of the cell is contribution to the organism. And in the same way the meaning of the individual human being, its contribution to the larger civilization that we are part of. And the spirit of this civilization is in our culture. What we traditionally call God grew out of the tribal Jewish God and then by the Christians. They forked it into some kind of universalist entity that is able to accept any ethnicity to it. And every religion in some sense is a set of policies that are being indoctrinated into the participants of a superorganism. And by acting on those policies, the superorganism gets enacted and becomes an agent. And that agent is interacting with other agents at its level in the world.

Joscha Bach:
So the different spirits of the different societies have different degrees of self awareness and different degrees of agency and they are acting against each other. And so what you can observe that at some point Christianity evoke at this societal level as an agent with the Catholic Church as its nervous system and brain, that the Vatican was able to make policies for everybody and the individual peasants and guildsmen and soldiers and all the participants in this larger organism did not necessarily understand what the nervous system was up to or what the philosophy of the Vatican was. Most of their AB testing has never been published and most of their understanding of how religion actually works is only down in their own private archives. But it acted as an adaptive operating system for a Very large civilizational organism. And that organism had its day and then it became sens and died, right? The Catholic Church still exists as a vestigial organ, but it’s not running any of the modern knowledge societies anymore. Conversely, there is a form of Islam that is currently having its day, that is self aware, that has a very active nervous system and that is invigorating its members and is spreading and is currently on an expansion course and is mobilizing larger parts of the world. And so in this sense, religions are one way to organize a superorganism. You could say that there are secular religions and theistic religions.

Joscha Bach:
Theistic religions personalized the superorganism into an agent, into this God entity, versus secular agents have a more abstract understanding of the state of the nation, of the ideological principles that you are serving. Your meaning is this relationship to the superorganism. And traditionally would say it’s your connection to God. When I was younger, I did not believe in God because my sources of God were twofold. One was the narratives of a secular society that was trying to reconstruct the mythology that the Christians had given peasants in the past as an attempt to see this as the worldview, right? So for instance, Christians tend to tell the peasants that there is an entity that is all knowing and that is all seeing, all good, and it’s all powerful. And this creates an interesting conundrum, right? If God is all powerful and all knowledgeable in all good ways, the world is in such a bad state, right, where there’s injustice and suffering and so on, but instead this thing makes sense not as a description of how things are, but as a bootloader. If you tell children that you know there is an entity that knows everything that is to be known, you give it full read access on the mind of the child. If the child actually believes in that entity, it means it’s not going to hide any of its thoughts from it.

Joscha Bach:
Because this entity is defined in such a way that it can read all your thoughts. It’s only benevolent, which means you need to fully submit to it. Every part of you that doesn’t submit to it is not good. And that thing is also all powerful. It’s able to change your perception and your memories. This is not able to do this by itself. Ideally, it’s going to get updated by the priests every week in mass. So you have a way to remote control your peasants.

Joscha Bach:
It’s a way to create a psychological entity on the mind of children that allows you to puppeteer them for the common good. I Personally have an issue with this because it is across with my liberal sentiments where I think people have a right to their own mental autonomy and you, you should not install entities on their brains. But to get to this understanding, I first of all needed to read the Bible cover to cover, which I did as a child and interpreted this in a very little sense. I thought this is a description of reality and of an entity, instead of this is a thing that when I read it, it’s going to change my psychology in a particular way. Right. And it’s not even this is literally true because the Bible is some kind of hodgepodge. It was originally a manual to run a desert tribe under conditions of expansion in warlike setting. And then it became a manual for medieval peasants that were told that it has a promise to the afterlife and whatnot.

Joscha Bach:
And there was a reason why the Catholic Church said, you are not allowed to translate this from Latin and read it yourself, because it would be very confusing to the peasants if they actually read the book. So instead they had a clergy that was indoctrinated with a particular kind of reading and interpretation of the whole thing. And they were only using selective sections of this to bolster up their authority in front of the peasants. And if you actually want to understand what’s behind it, you have to talk to the people in the Nevadi Khan in some sense, and to this in depth understanding of a continuous intellectual tradition that selected these texts and knows the actual meaning. And I didn’t have access to this at any level and I was not even aware that I should have access to this. And there was such a deeper story instead I was immersed in a world that said all these stories are just a collection of superstitions that randomly emerged and randomly got people to congregate into religious mindsets. And until the Enlightenment came along, we actually figured out how to works, except for theology, which we don’t think is worth looking at, so created a very weird situation where the science escaped from theology, originally was part of theology, and then never looked back and never tried to understand theology. And instead theology, I think, never stopped looking at science.

Joscha Bach:
And so I suspect that the Vatican is a better understanding of the science than the sciences and understanding of the Vatican.

Brian Keating:
But to your point that this bootloader is going to be installed, it’s inevitable. It’s not like there weren’t alternative bootloaders around the world, including in Roman societies and the Gothic societies and even in the Hebrew societies, which I’m familiar with. But isn’t there, you know, to Push back with some love and respect. There’s a virtue. I mean, it’s impossible to raise a child completely divorced with them coming up with complete. Sam Harris can maybe do it with his kids, but I wasn’t able to do it with my kids. And for the simple fact that they’re going to be exposed to so much outside of the home, with their friends in a healthy society and the society is going to impose things on them from the kind of bootloader standpoint as well. So what’s the argument against not installing that yourself? As parents, don’t we have a responsibility to install good software? And yes, some of it will be just like you sometimes have to say when your kid asks you, why, why, why, why? Why? Eventually sometimes you have to say, because now is that the best way to be? Maybe not.

Brian Keating:
But as long as the software is not malevolent, causing some virus, causing some disastrous consequence, which I don’t believe. Sam Harris has it better than a 13 year old’s understanding of the Torah, for example, because that’s when he last encountered, you know, at his bar mitzvah. And then from then on he kind of let the 13 year old self of him refute it. He and I have talked and he knows my position. But at any rate, we’re going to get bootloaders installed, so why not make it one that’s had a 3,000 year long tenure, not just during the peasants and the Bronze Age tribes, which it was useful. I mean, I always joke I’d love to have 1% of God’s book sales because it’s been read for 30 centuries.

Joscha Bach:
That’s interesting. Which of the books should you install, right? If at all?

Brian Keating:
Here’s an example. Here’s a perfect example. I was just talking about this on Shabbat this past week we covered the weekly Torah portion and the portion this week has to do with not hating your neighbor in your heart. Now everybody knows that, it’s in Christian tradition and so forth. But there’s another half of that sentence. I read it in Hebrew, in Hebrew, the next sentence is because I am God. Now why does it say that? Why does it have to say don’t hate your neighbor in your heart because I’m God? I’m curious, Yosha, do you know why it says only on a few commandments? It doesn’t say don’t eat that delicious pink thing with the squiggly tail because I’m God. It just says don’t eat it.

Brian Keating:
It doesn’t say keep Shabbat because I’m God. But it does say, don’t put a stumbling block in front of the blind person, because I’m God. Now I’m curious. We’re doing real live Torah study right now. Why do you think it says because I’m God on certain things but not in others?

Joscha Bach:
I’m only guessing here because I’m not an expert expert on the Torah at all. But my sense is this is because we have the same God. We are members of the same tribe. We are cells in the same organism. So don’t sabotage your own organism. Of course, there are others where it might be useful to put a stumbling block in front of, right? If you have a soldier who is invading your country and deserves a different God, maybe it’s a good idea to put some stumbling block.

Brian Keating:
The sentence is, don’t put a stumbling block in front of a blind person. So the rabbis in the Talmud discuss it, and they say the reason is because you could get away with it. And by the way, it doesn’t just mean a stumbling block. Like, here’s a brick, you know, put in front of some blind person. Almost nobody would do that. But, hey, Joshua, I got a car I want to sell you. It’s a really nice Ferrari. It’s only got 9,000 miles on it.

Brian Keating:
Here it is. You want it? It’s a million dollars. Oh, yeah, yeah, I want it. Sounds great. But you don’t know that it actually is about to have its engine blow up. You’re blind to that fact. But God’s not. The point is for things you could get away with hating your neighbor, being happy when.

Brian Keating:
When he fails, you get away with that. And that’s not part of a good situation.

Joscha Bach:
What altruism actually is, that’s often misunderstood. When people claim that there is no altruism, actually it’s only people are serving themselves and so on. But the thing is actually quite boring and pointless to serve yourself. Once you realize how much work it is to maintain an ego, realize that the ego is only instrumental. There are some goals that are easier to achieve and maintain if you maintain that ego. But ultimately it’s just some kind of prior that you might be born with. And it gets reinforced with some events, but it’s actually more trouble than it’s worth. And the thing that you are working for is this larger thing.

Joscha Bach:
And this larger thing is the thing that is meaningful, the sacred, the thing that you’re willing to sacrifice your ego for. And when we talk about love, we are talking about, in this context of general interpersonal relationships, about discovering the sacred in the other. Which means we discover that they have the same sacredness, they serve the same principles, they are part of the same superorganism. And when you realize that your meaning is the service to this larger thing that is spanning far above our individual egos, and it’s much more important and has much more longer time horizon that actually gives meaning to our existence. And so the reason why you are not harming your neighbor is not because you would have difficulty get away with it, because they would retaliate, but because it’s defeating your own mission. The mission to make the superorganism work. The superorganism is here saying, asserting here I am the spirit of your tribe, or the spirit of humanity, or the spirit of all sentient creation, or the spirit of everything that exists. And there’s different interpretations, like the Christian God is only the God of the good ones, whereas the especially the Protestant one, whereas the original Jewish God is the God of everything that’s also the God of Cain.

Joscha Bach:
It’s a very interesting difference in the architecture of the superorganism. Are the parasites, are the murderers? Are the mafiosi also part of the superorganism? Are they in the end serving the same God? Or are they part of a different civilization that you need to out compete and to vanquish? That’s the interesting perspective to which different religions have very different and distinct answers that are worth examining. So when I let my children read these books, I want them to be able to maintain a difference. So instead of being attracted into the event horizon of an ideology that distorting their own mind in such a way that the rest of the human thought space becomes inaccessible to them. Ideally I want them to be able to retain that openness so they have a part of their mind. This is a general sense making module that is not caught up in any kind of faith or beliefs, but is able to model every faith or belief as a psychological configuration and understand and model the consequences of this to the best degree possible. Or at least in such a way that they can retrace their steps and make different bets if they realize that a certain thing doesn’t work and they are born with certain priors. I find myself to be basically being close to a European Calvinist Protestant.

Joscha Bach:
And it’s not because I believe in any of this ideology and the mythology and so on, but because these are behavioral priors that lead to certain default protocols in social interaction. They lead to me not littering even if nobody is looking, putting the car back into a tray at Wolf woods these behaviors that are basically trying to try not to leave the world worse than you find it, but better than you find it, because it’s important that the world works, not that you are in it and you are being in the world is instrumental to the world working better. That’s part of the protocol that I’m observing. And once you are born with a protocol like this and gets also not defeated by your environment, it seems to be so self evident that a lot of people don’t understand that not everybody has that protocol, that there are competing civilizations that don’t achieve this degree of coherence. And so when I’m a parent, my idea is not so much that I tell my children what to do, but what to model. Did you think about this? And ultimately they should behave in such a way that they realize that their behavior is in their own best interest. And that also means that they have to identify and maintain their sources of meaning in a sustainable way. But it also means that we should be able to recognize when the society around us doesn’t work, it is ugly.

Joscha Bach:
And we should be able to have our own spirit independently of it. And being able to create pockets of sanity within a society that is breaking down because it’s incoherent and ugly and self defeating and short sighted and unsustainable.

Brian Keating:
Very reminiscent of the great Rabbi Hillel who said, if I am not for me, who will be for me? If I am only for me, what am I? And if not now, when? And it really speaks to this notion of self. I’ve told you, Lawrence Krauss, when he mocks me about my religious practice of going to a temple every Saturday and you know, keeping kosher and learning Hebrew, I’ll say to him, you know, Lawrence, or to Sam Harris, the same way you might be more evolved than I am. I’ll stipulate that you, Lawrence, you, Sam, are better person than I. You probably give charity. We give 20%, 30. Whatever you would do, I’m not as good as you. I need that. I need someone to reinforce to me that I have an obligation not only to myself, that I do have an obligation to give back.

Brian Keating:
I don’t believe in Jesus as Messiah and I’ve talked to many of the leading theologians about that. It’s not part of my theology, but that’s fine. We don’t have the same religion, but we have the same end goals, which as you said, is the flourishing not just of the individual human, but of society as a whole. Speaking as our, maybe one of our wrap up questions where is the self? And I’ve talked with Roger Penrose multiple times and Stuart Hameroff, his partner and, and fun, I won’t say crime because they got into some trouble recently. Roger Penrose has this orchestrated objective reality that stipulates consciousness arises from the quantum mechanical collapse of a wave function precipitated by the vile curvature. So he connects the gravitational theory which assumes special relativity, constructs the Weyl curvature, which has a well defined meaning derived from the Ritchie tensor, Ritchie scalar and the Riemann tensor and constructs this tensor that interacts with the microtubules and causes consciousness. What do you make of this theory?

Joscha Bach:
I think it’s magical thinking. It’s not providing a causal mechanism that is explaining how the representation of itself in the world comes about by itself. And it’s also unnecessary because I think there is nothing mystical about the notion of representation. What helps is that I’m a computer scientist and not a physicist. A lot of physicists tend to think of the world ultimately as stuff in space and not as information on multiple levels of description. If you’re a computer scientist, this notion that our patterns within patterns and some of these patterns within the patterns have causal power of themselves that is much more natural to us. And so for me, this notion that you can build a ghost into the machine and this goes into the machine maintains a representation of what it’s like to be that ghost. And that is not a phenomenon that is reflecting the state of affairs in physics, but the regularities that are necessary for controlling your interaction and your stability.

Joscha Bach:
So I don’t have an issue to explain consciousness in practical way. There are. I have no hard problem. I have a lot of difficult problems which are all technical problems how to make it actually work. But these are engineering problems where they are still fiendishly tricky to get to work. But they are not mysterious. There is no mystery in my world. And I think there is a big mystery in Orchard Penrose World because most of physics has turned out to be non mysterious.

Joscha Bach:
The mystery needs to be hidden in a part that is not explained yet. And so he looks at the parts that are still somewhat mysterious to the physicists, quantum gravity and collapse and so on, and then associates them with consciousness to basically there is this single head that we haven’t lifted up in all the other areas where we put light in. We realize that this does not explain consciousness. So consciousness must be in the hidden corner. And I think it’s a category error that he’s committing that he thinks of consciousness as a physical Phenomenon, not as a psychological or representational phenomenon. A similar thing happens with Sam Harris and God. Sam Harris thinks that the claim of God is claim about a physical being, a physical being or some kind of supernatural being. Supernaturalism doesn’t make sense for somebody like Sam Harris or also myself, because everything that exists is nature by definition.

Joscha Bach:
And so the idea that there is some super physical being that is creating the physical universe does not only make sense from a physicalist perspective, it also makes very little sense from epistemological perspective. How can you make such a claim? Because there cannot be an experiment that would vindicate your claim. It can also be not be an observation that you got this claim from. So you just made this up. That’s why the claim that Christians make about God is preposterous. So any existence claim of God is wrong. And this is a misunderstanding about the status of God. And if you want to understand God, we need to understand that God is a psychological phenomenon.

Joscha Bach:
This does not mean that God is unreal. God is not more or less real than you are. Your personal self, your personal self exists as a representation in your brain. It’s a multimedia story of what it would be like if you existed. Once the story is instantiated, it has causal power. It’s only an approximation of the actual state of affairs. Because what actually is there is trillions of cells, or more accurately, gazillions of molecules, or more accurately, some regularities that are propagating in the quantum form. But what you perceive is this high level representation.

Joscha Bach:
You hear a voice talking in your head. And we don’t think it’s mysterious that we have this voice talking in our head that is ourselves, that monologues about our interaction with the world. At least many of us, some of us don’t have an inner monologue. But it’s not mysterious that this exists, right? And some people have two monologues or a dialogue. And this is not more mysterious. It just means that God is installed on their mind as an entity. So they have a model of a collective spirit that coexists with the model of the individual spirit inside of the same mind. And both of them have personal agency and both of them interact with.

Joscha Bach:
And God knows the God is lucid that it’s an entity that’s implemented on multiple brains and exists across minds. And its purpose is to orchestrate the behavior of all of those hosts. So a God with a small G is a multi mind self. It’s a self that does not exist on one brain, like Ryan Keating in Josh Bach. But it’s a self that exists across many brains. And the Abrahamic gods are mono gods that are basically singletons that are saying we are an optimum in the space of gods, and the people who entertain us on their brains should not have any other gods. And originally that thing starts as a tribal God that says, this is the spirit of our group of people, the descendants of the prophet. And Christianity, after their folk, that cult retroactively picked a prophet that as far as we know, didn’t have kids.

Joscha Bach:
So it’s much more inclusive. And this prophet also serves the purpose of an idol. Judaism does not have idols. And in some sense, the function of idols in Judaism is carried by the individual prophets that are human beings that express certain skills and personality traits and behaviors that are useful for the tribe at certain times and at certain roles, like King David and so on, or Solomon and Abraham. And for the Christians, they have these two idols. Mary, the idol of purity, the Holy Virgin, and Jesus, the idol of love and innocence. And this concept of innocence does not really exist before Jesus in the Abrahamic thread. It also doesn’t exist in the Roman culture.

Joscha Bach:
In the Roman culture, it’s totally okay if innocents die in the Colosseum. It’s a problem if it’s not lawful. But whether innocence come to harm is not of concern to many cultures. And in Christianity, this is the core. The justification of violence is the protection of innocence. The individual behavior should be organized in such a way that innocence becomes possible as a survival strategy. So just by being innocent, you should be a good Christian. And Jesus embodies that arguably does not completely scale.

Joscha Bach:
There is a Chinese story about Jesus who is coming to a place where they’re about to stone a woman for adultery. And Jesus says, okay, who is without sin should cast the first stone. And so people start to hesitate. And then Jesus thinks the moment and says, wait a moment, if I ask for this, we will not have a working judicial system anymore. And we have to make allowances here. And it’s necessary to maintain order. And so Jesus takes the first stone and starts to stone her. Right? So this is a pragmatic way to think about this whole thing.

Joscha Bach:
But the aesthetics of Jesus are important. They are the justification of the Northern European civilization, the one that came the success of civilization to the Roman Empire and that is still active after the Enlightenment. Atheists like Sam Harris or Noam Chomsky still believed that at the core of civilization is the protection of the innocent. And they also believe in the service to the greater whole. And so in many ways, There are deeply spiritual super Protestants that are protesting more than the normal Protestants. They’re also protesting against the institutions that are spreading irrational mythology. But the behavior of prescriptions are the same thing. The difficulty is just that there is no authority that allows you to negotiate differences and interpretations of these priors and rules.

Joscha Bach:
And to turn this again into a rival religion, you probably would need to have a rationalist foundation that allows independent retracing of the lines. And I think the tradition that within the institutions in the Abrahamic orbit made this best is probably the rabbinic tradition, the legalistic one that your own tribe and group is probably among the traditional ones closest to it. But it’s difficult to deal with some of of the things, right? Especially how do you relate to the orthodox? How do you negotiate these differences with people who think that the meaning is not actually to have the best possible operating system for the tribe or for all of humanity or for all of creation. Especially once we allow non human agents like smart animals and also in the future human like and post human machines and human machine hybrids into existence and we can probably not prevent them from existing. How do we scale this up? How does this work? We basically need to have an ethics of shared purpose that is actually scalable into a global optimum. And this means that we have to rationally rediscover a notion of God. I’m not the person to do this. I’m just a guy looking at things, not a spiritual teacher.

Joscha Bach:
I’m more stupid than the average person. It’s just looking at this from the outside is so fascinating that I cannot say, stop myself from looking.

Brian Keating:
Yeah, no, it’s obvious you have a great depth of thought, not just the trivial dismissal, which is what I think. Most of the atheists, like Krauss, Chomsky, Harris, they have a sophistic idea, but they think they’re erudite because they’re super evolved, as you said. But you made me think about that in a new way, that yeah, maybe they’re more Catholic than the Pope, as we used to say.

Joscha Bach:
Really? The funny thing is this guy was saying God doesn’t exist. He’s just a voice in the head of crazy people. And that’s also just a voice in the head of a crazy person. This is so ironic.

Brian Keating:
Irony is lost at these people. You write a lot and you think a lot about education. And I wonder if we could establish Bach University, which would be kind of cool thing to start up, what would be on the course offerings list? What would you teach there? What would be the mandatory Core requirement for a first year student at Bach University.

Joscha Bach:
I think it would be a Neo Aristotelian project. I like the spirit of Aristotle. Somebody who is extremely curious about everything and reads all the other authorities, is a source of inspiration and argument and counter argument and is trying to piece it all together into the space of ideas that can possibly work and explain reality. So I think at the core of the curriculum is epistemology. What is actually knowledge and then the space of ideas that can actually work. And at the moment, at the core of the space of ideas is a way to understand foundations of the way in which minds construct reality. It’s basically language of thought. And this goes in the direction of computational dysfunctionalism, which means that to represent the world, we need constructive languages.

Joscha Bach:
And in the 20th century, we had two major insights about constructive languages. One is that classical mathematics, stateless mathematics, doesn’t work. It leads into contradictions. This is what Godel discovered. But the constructive languages are actually doing all the work of mathematics that actually does work. The other big insight was that these computational languages are equivalent. You can all compile them into each other. So it doesn’t really matter which one you take.

Joscha Bach:
That’s just a matter of convenience. And this means there is actually hope for this project of putting description of reality, of creating models on some kind of safe ground. We are now able to answer questions like, if you look at ternary or quaternary logic in Vedic scriptures, is this actually superior to worlds that are built from Boolean logic? And the answer is, no, it’s not. You can compile them into each other. It doesn’t really matter. It’s just a matter of notation. Then you basically get to a model of reality that allows you to scale up, that is scale up beyond human minds. To me, artificial intelligence is an attempt to naturalize the mind by mathematizing it to explain how it exists in nature by building an executable mathematical model of what a mind is.

Joscha Bach:
In a general case, let’s scale it up, what human minds can do. Until we actually get a model of reality that can conquer the heaven, that is actually a working Tower of Babel. It doesn’t fall apart because it’s made out of individual people with incompatible languages. It’s actually a thing that has a language where every part can talk to all the other parts. And then in terms of a practical university, I think we need to have a curriculum that is teaching the most important sciences, which is economy, which includes evolutionary game theory, models of how organisms exist in the world, and harvest Energy and use this energy to change things in space. Includes models of cooperation, group psychology, individual psychology. I think we need to revive psychology as the study of the psyche, not as the study of behavior that we can observe. So we need to make overarching systemic theories of what minds are and how selves are being constructed.

Joscha Bach:
And we also need to make models of possible superorganisms so of ways in which we organize societies. What are the consequences if you make these particular choices? You need to be able to analyze cultures and compare them. And this comparative cultural studies need to analyze the software that is running societies, the actual control structures and what the result of implementing certain control structures are above others and the long term consequences of this. Right. And ultimately the goal of education, I think is to allow us to live together and to go into the future. And it basically means to design a societal blueprint that offers a space for everyone that is actually acceptable and servicing humanity into going into the future and is able to deal with the changes that the future are going to bring. And so for me, the goal of that education is allowing people to find their space, their place in the greater whole and to learn these policies. And for those who are really interested in going deeper to also understand the theories behind it and becoming autonomous individuals that can make sense of reality in themselves in every which way.

Brian Keating:
Seems like your upcoming conference machine consciousness 0001 do you really need all those significant figures, Yosha? Coming up at the end of this

Joscha Bach:
month, I’ll drop a link.

Brian Keating:
People can register for it here.

Joscha Bach:
My program director, Lou Decay, who came up with the idea that this is actually binary notation. It’s actually a very humble start of denoting it. Of course you can always say at some point that it’s a different denominator. It could actually be hexadecimal or octal. But this is one of the first ones in a larger number. But it’s not necessarily a decimal notation. It’s a conference that we are organizing in San Francisco in Lighthaven. It’s the starting event of our way to make sense of reality and this intersection between human minds and artificial minds that are meeting in this fascinating place, the Bay Area, or in this most fascinating time.

Joscha Bach:
Happy singularity to those who celebrate. And we are getting together a number of thinkers in this space and also artists. And we invite people to look at this. Check out our website, CMC AI, where we also have a link to the conference. There’s still open place for those who are interested.

Brian Keating:
Now hold up for a second because if you’re watching this and you’re under 20. Don’t skip the next 90 seconds. Yoshi just told my listeners about the only career advice he believes to be true.

Brian Keating:
If someone is watching this smart 18 year old, 19 year old thinking about next steps, maybe after college, and maybe he or she is choosing between a PhD in physics, a PhD in machine learning, or just dropping out to build something in 60 seconds or so, what do you tell them and what’s the one book that’s essential for them to achieve that goal?

Joscha Bach:
So I don’t think that there is one book. I think when you are young you should read thousands of books, like literally, because books are one of the most effective ways to focus your attention and you should be curiosity driven and very often it’s impossible before you read the stuff to understand what drew your curiosity. I’ve got a lot of useful ideas from reading thinkers like Stanislav Lem and others. Also movies were very important, informative people like Gondry and so on have brilliant insights that can get you to think. And the most important stuff is that effect of what you read is how they allow you to think and build. Also for your studies, it’s a good idea to pick projects that you actually want to work on. So for instance, if you study computer science, pick projects that you actually want to build. And they don’t need to be big, you don’t need to impress anyone or yourself.

Joscha Bach:
Take things that you find interesting to try and start as small as you can and as you want, as it’s joyful and just play. And when you read, read things where you feel that it might allow you to build more, to think more, to think more deeply. And we are now living in a time where calories are basically free. We don’t know if this is going to be like this forever, but humanity has never been living as comfortably as it is today. There have never been as many artists as there are today. Not so much freedom to write and to think on your own and to interact with people around the world. It’s never been as easy. This freedom is very hard to deal with.

Joscha Bach:
So this is also an important thing to do. The reason why so many of us are miserable is not so because capitalism is more oppressive than ever, but because it’s so hard to deal with this loss of meaning that a society that has lost this direction is providing. And so find your meaning, find friends. If you feel that you’re unhappy in the place in which you are, go to a larger city. You will probably find your people. If you’re not an unsustainable, unbearable person. And if you study, try to find out what’s actually worth studying, what are the most important questions for you. And try to identify the people in the space that are interesting to you that you actually want to learn from.

Joscha Bach:
The purpose of education is twofold, right? One is to get skills, but you can get skills from YouTube more efficiently than you can get it for most university classes. The other one is to interact with other intellects and so identify the intellects that you want to interact with, that you want to train your mind on and talk to them. Go to conferences, pay your own way to conferences if you’re interested in the topic. And try to get inspired by the people that go to summer schools. Go to places where people do things out of love stuff. And the professors who teach at summer schools are usually not paid for doing so, which means they do this because they actually love this stuff and they love students. And so this is also a very good way to get started. And don’t go to, if you can help it, to places that.

Joscha Bach:
Where you just think to do this to get rich. Maybe it works. Power to you or to serve your vanity, because it’s. You feel better if you’re a philosopher or something like this, and at some point you realize it’s mostly a scam or it’s unproductive. Go for those things where you feel that there is a calling that is an interest and they’re curious. And there are people who hang out there who are going to be your friends because they have similar interests. Even if you don’t end up doing the thing that these people are doing that you studied, the networks that you build are probably going to be the networks that carry you through your life. People that you start companies with, that you start farms with, or whatever it’s going to be.

Brian Keating:
Let me ask a difficult final question, which is we talked about death. We’ve talked about, you know, collective death. We’ve talked about societal death, perhaps, but have you thought about your own death? Like, have you visualized what will it be like? And what. What does that thought do to you? Terror? Does it inspire you? Does it make you have more investiture and meaning in your life? What is your own death, not death in the abstract. What does it mean to you?

Joscha Bach:
I found when I was confronted with my own mortality after getting a very pessimistic diagnosis in my early 20s, I was okay with dying, right? Accepting this deal that is an organism. When you are born, death is inevitable. Everything that goes up needs to go down. There is no eternity. And if you really think about it, what does eternity look like in the end? Is it a loop or is it going to be death? Is it going to peter out somehow? So eternity itself is not really a concept. And at some point you realize the thing that you’re afraid of is that you die before your work is done, before you achieved what you think needs to be achieved. And then you can look at what is the thing that you believe you need to achieve to get your kids on the way to find love, to build a family, to find a project that is worth doing and actually make some progress on it and so on. And you realize that also at some point this is just these starting priors that are built into a social organism that is programmed in this way because it’s useful to this larger superorganism.

Joscha Bach:
And if you’re able to free yourself from it, you are able to escape this whole thing. It’s fascinating to compare the Eastern religions which see the world mostly as a periodic thing and you as a soul are caught in it and the goal is to hopefully get out. Getting out doesn’t mean that you go into a better wheel. It means that you get out, that you dissolve, that you are done, that the game is ended, you don’t need to play anymore because ultimately it’s a scam and it’s not worth it. Versus the Abrahamic world sees the world as a linear progressivist progression where you start out as a low stage of development and you end up in a stage of development that is so high that it’s incomprehensible to you now. And this is going to be different game that is much more exciting than the present one. This is in many ways what also inspired the modernist culture which which was defeated in the 1960s. And now we are basically this headless chicken that is keeping more or less on course until we either build AGI and have the balls back up in the air and everything is different and new, or we just die and get replaced by a different culture.

Joscha Bach:
Maybe it is time. It’s going to be an Islamist culture that has a few thousand years to get its together and build something interesting.

Brian Keating:
Who knows, maybe we’ll surrender to Zuckerberg at Altman Amadai and all the rest

Joscha Bach:
of the and so basically I’m now somewhat middle aged and I feel I’ve been somewhat useful to the world. My life was not happy, but meaningful. That’s the price of existing. If I would find myself to be non existing and had a solar perspective on things I wouldn’t be unhappy about this. I don’t want to be revived. I don’t want to have any kind of cryonics because I find existence painful and burdensome and tedious. I’m here because there are others who depend on me, who I love and feel adapted to and I don’t who want to sever the ties to my meaning because then my life would become without purpose. I don’t think I would be able to make a happy nihilist.

Joscha Bach:
I basically keep these wires plucked in my mind that make me perceive meaning and as a result make me a father and a lover and a friend and somebody who is serving his philosophical missions and keep going for until God relieves me of my burdens.

Brian Keating:
Well, may you, like your biblical namesake Joshua, may you enter the promised land. Which Moses did not. He was not worthy of entering the promised land. But Yahshua Yoshua did take that mantle as prophet, as supporter, as the leader of the people that then established themselves in a new world and a new reality.

Joscha Bach:
I am in the promised land. I grew up in eastern Germany. I never thought I’d go anywhere. I now find myself after a long event for expedition, having an institute in city of artificial Intelligence and exploring a future of humans, artificial intelligences and consciousness. This is the promised land.

Brian Keating:
If you were born 200 years ago, if you were a king 200 years ago, you’d be much less happy because you wouldn’t have what you have now.

Joscha Bach:
I don’t know. I think happiness is intrinsic. It’s not the result of what the world does to you, but how you react to the world. And I also don’t believe that happiness is super important. What’s important is that you have a state of mind that keeps you going. Chasing happiness is a waste of time.

Brian Keating:
I agree. And you can never really be happy. You can only kind of achieve the path to happiness due to entropy. Anyway, Yosha, this has been fantastic. I hope we do meet in person. I wish you great luck with your conference. This has been beautiful. It really has been meaningful for me.

Brian Keating:
Likewise, Yosha Bak just told us that consciousness is software, that God is a real but psychological psychological phenomenon. And that he’s genuinely okay with dying because his work matters more than he thinks he does. Now if that changes how you think about your own mind, you gotta hit subscribe and the notification so you don’t miss what’s coming next. Drop a comment and let me know whether you think Yosha refuted Penrose or whether Penrose still has a stronger argument and if you want to go deeper, check out my conversation with David Deutsch. It’s linked right here. His constructor theory exchange is the missing piece that we left out of this conversation. And don’t forget to watch my episode with Sir Roger Penrose and Stuart Hameroff. It’s a two part one.

Brian Keating:
You’ll love it.

The Equation That Changed How Physicists Think About Reality | Juan Maldacena

sabartigas — Sun, 10 May 2026 11:30:38 +0000

The Equation That Changed How Physicists Think About Reality | Juan Maldacena

Transcript

Brian Keating:
One of Einstein’s two strangest ideas, wormholes and quantum entanglement were the same idea. My guest today spent his career proving

Juan Maldacena :
that they are so called Einstein Rosen paper on the fact that the full thrashette solution contains two black holes that are connected and the Einstein Podolsky Rosen paper that talks about entanglement. And we now think that these two things are related.

Brian Keating:
My guest is Juan Maldicena, the physicist who in 1997 wrote the most sided paper in theoretical physics. The claim he just made that wormholes and entanglement are the same thing is called ER equals epr. If he’s right, the structure of space time is built out of quantum information itself.

Juan Maldacena :
The information of the things you threw in is contained in this radiation. According to general relativity it will look like the information is lost. According to quantum mechanics, we would expect it to be preserved. So there is a conflict between the two things. Quantum matter didn’t obey this property then you would be allowed to send signals faster than the speed of light. I think this is a beautiful consistency condition between the two theories.

Brian Keating:
He also told me problem in physics he’d most like to solve before he dies. The answer was not what I expected.

Juan Maldacena :
The most important problem, quantum gravity, is to understand the beginning of the big bang. That’s really the problem that I would like most strongly to solve.

Brian Keating:
Juan Alicena, welcome to UC San Diego for your second appearance on the podcast.

Juan Maldacena :
Yeah, thank you Brian. It’s a pleasure to be here.

Brian Keating:
You’re here giving the Dashen lecture all the way from the Institute for Advanced Study which I think is on Einstein Lane. Is that correct address? I’m not doxing you right to say you’re on one Einstein Lane. Here’s Einstein over here. What do you think he’d be kind of most interested to learn or if you could have 10 minutes alone with him, what would you tell him about?

Juan Maldacena :
Well, I think black holes would be probably something he would be really interested in. I would particularly want to tell him, want to ask him whether he thought that his two papers from 1935 would be related. So called Einstein Rosen paper on the fact that the full threshold solution contains two black holes that are connected. And Einstein Podolsky wrote some paper that talks about entanglement and we now think that these two things are related.

Brian Keating:
This ER equals epr, right? That’s one of the things you’re known for. Many, many things you’re known for.

Juan Maldacena :
One surprising thing would be that they are a consequence of gravitational collapse and that are naturally produced in the universe. Now in the last few years, really, in the last few years, we had lots of experimental evidence for black holes. From collisions that produce gravity waves to imaging the matter near the black hole of the black hole that is near the center of the Milky Way, to, you know, looking at stars that orbit this black hole. Yeah. So we have lots of evidence for these black holes. Now then the other surprise I think would be black hole thermodynamics. I think that would be something really interesting in the sense that there’s a connection between the laws of thermodynamics and black holes, that black holes have an entropy, they have a temperature. I think that would be a lot of fun for him.

Brian Keating:
I mean, gravitational waves, another thing he predicted that he thought would never be observed. And I think he got a paper reading rejected and then he said, I don’t want to deal with a referee. And another thing that he did, well,

Juan Maldacena :
he first predicted gravity waves, then he thought maybe they don’t exist. And then the referee said that no, they do exist. You made a mistake here. And then that’s what I say when

Brian Keating:
people say peer review is bad, it’s harmful to someone else.

Juan Maldacena :
I mean, this case was a good example of useful. Well, I guess you got a good reviewer.

Brian Keating:
That’s right, yeah. That led to multiple Nobel prizes at Halse and Taylor and then LIGO and who knows what else it’ll do. But yeah, I always tell my students aspire so that your blunders or things you don’t think will ever work will lead to multiple Nobel prizes.

Juan Maldacena :
Yeah, yeah. And the cosmological constant, that was his biggest blunder. Yeah. Now it’s a central part of cosmology.

Brian Keating:
So I want to talk today about the realities of black holes and of things like the holographic principle, which is one of again, many things you’re known for in your amazing career. I was talking to a non scientist, but a very smart layperson and he was asking me, well, you know, if the holographic principle is correct. You know, some people say, well, we might be living inside of a black hole and things like that. But I always point out, you know, there’s no such thing as isolated hydrogen atom floating around the universe that truly can be solved by the Schrodinger equation. In other words, there’s always perturbation. To my knowledge, there’s no such thing as a Schwarzschild black hole either. Right. That’s perfect.

Brian Keating:
There’s occur black holes, we know of the ergosphere surrounding them. So in what sense is the holographic Principle of the fact or, or proposition that we could be living in is that just pure theoretical. Because of the realities of real black

Juan Maldacena :
holes, the holographic principle as applied to our universe, we don’t know whether it’s correct or not.

Brian Keating:
Could you explain the holographic principle? First?

Juan Maldacena :
The holographic principle is the idea that you can describe quantum gravity in some region of the universe by some theory of ordinary quantum mechanics that lives in the boundary of that region. It remains a big idea formulated this way. Now in some special cases, some special universes, so universes which are infinitely big and so on, then we can go to a surface that is very, very far away and define there a very concrete theory that whose laws of physics we can define. And in that case they are supposed to describe the interior of those universes. Those universes are not the universe we live in. They have slightly different. Well, they have different laws of physics. They have a different value for the cosmological constant.

Juan Maldacena :
But in those universes there is a lot of evidence that this relationship is true. Now there in those universes, you can consider black hol holes that are inside this universe. The black holes can have perturbation matter around. And the idea is that those would be described by the theory that lives on the boundary. And there are some comparisons we can make. One, let’s say catch or one thing that makes it hard is that the theory that lives on the boundary involves strongly interacting particles. And so it’s not completely obvious how to solve this theory. So you have to apply some techniques.

Juan Maldacena :
There are some things you can calculate, but not everything you would like to calculate. So that’s in order to compare the two things. And we are learning more on how the dictionary gets built between this quantum description on the boundary and the gravity description in the interior.

Brian Keating:
When you say lives on the boundary, what does that mean? Is that like a separate Hilbert space

Juan Maldacena :
or lives in the boundary means that these are particles that move on space which has the geometry of the boundary. It doesn’t have the extra dimension. And the idea is that you can think in two alternative waves. Either you have particles that live on that boundary, or you have the gravity description that lives in the interior. And the idea is that these particles are strongly interacting and the gravity description is some kind of emergent property. It’s not something that was there in the very beginning in the formulation of the theory, but looks like it’s an approximation to the underlying dynamics.

Brian Keating:
Does that gravitational theory, does that produce GR or something different?

Juan Maldacena :
So the idea is that when these particles are Strongly interacting and some special cases that we understand and would produce general relativity. In fact, in the examples we understand it produces general relativity plus string theory also at short distance. So there is some approximation where it’s just general relativity with some particular matter content and then also strains and stuff like that. Those are in the cases we understand. We don’t know whether string theory is necessary for this discussion or whether this is valid more generally. Or maybe string theory is the only way to quantize gravity. Those questions we, when we can remain

Brian Keating:
agnostic, will it produce, you know, excitations and things like the fermions, you know, three.

Juan Maldacena :
Yeah, you can have fermions, you can have all that.

Brian Keating:
When you said strongly interacting, does that mean like the strong force or does this mean like short range interaction?

Juan Maldacena :
By strong interaction, I mean that the coupling between the particles is very strong. So that if you have two particles that collide, they very, they will scatter very, very easily. The strong interactions are called strong because precisely they, the interactions are strong at the level of, let’s say, inside the proton and so on. And in addition, the type of particles that we have also have interactions similar to the strong interactions. The so called gauge theory. It’s a type of interactions that involves the property, let’s say, called color, which is a type of charge, but of which the sign is not just plus minus. But there are like three different types of charges in nature. There are three different types in these theories we consider there is a large number of types.

Juan Maldacena :
There are theories somewhat similar to the theories we have in nature, but not exactly the theories we have in nature. What we have are some examples of this involving this, let’s say the aershast theories and models. You could say it’s a model of quantum gravity. And one of the advantages of this description and the reason that it was developed was that it could give a full quantum description of the gravitational space time. So we don’t just get general relativity, but the quantum version of general relativity. And we hope that by having these models we will understand the quantum gravity more. And then eventually, of course, the objective is in the end to understand quantum gravity in our own real world. So somehow to extract lessons from this, to be able to apply them to our real world, you know, just at

Brian Keating:
a basic layperson level, you know, not going to do this, but you know, take your laptop, you’re going to be speaking later. Throw it into a black hole. What happens and does it depend on what type of black hole it is?

Juan Maldacena :
If you throw anything into a black hole? Well, Your laptop and so on, it will fall and you will lose sight of it. So the time it takes light for going a distance of order the size of the black hole, all the information about that laptop is effectively lost to you. So in the sense that you will not see it anymore, and any perturbation you had of the metric that was due to the fact that there was a laptop will be lost. So the influences decrease exponentially fast. Okay, this is fine. This is what happens with classical black holes. But as we were saying before, black holes have some entropy. And entropy in physics, we interpret it as arising from statistics.

Juan Maldacena :
And it’s a measure of how many states the black hole can have, how many, if you wish, bytes can be stored in this, or qubits can be stored in this black hole on the

Brian Keating:
surface or on the volume.

Juan Maldacena :
Well, the formula for the entropy is just the surface. So then you might be tempted to say it’s in the surface, but in the classical solution, the matter falls in and goes into the black hole. So you could be free to say it’s in the interior. What that somehow suggests, this picture, that the black holes have a finite amount of entropy, is that that information is not completely lost somehow. In fact, when you throw in the computer into the black hole, the area, the mass of the black hole grows a little bit and the area grows a little bit, and the entropy becomes larger. It becomes larger by an amount which is bigger than the entropy that was, than the amount of information that was in the, in your laptop. And you can use the laws of physics to show that this is always the case. Whenever you send something into the black hole, the entropy always increases.

Juan Maldacena :
The question is, is this lost forever or not? In principle, you could say it’s lost forever. And you might think because the, you know, goes into the black hole and then, well, never come out, according to classical physics. But the new aspect is that these thermal effects in particular, Hawking radiation, implies that the black hole will emit something, emits some radiation that in the first approximation is thermal and carries no information. But it’s saying that the black hole will start losing mass, so it will get smaller, and eventually the black hole might perhaps disappear completely and become get some radiation. And you could wonder whether the information of the things you threw in is contained in this radiation. Now, if it is contained, it will be contained in a very subtle way. But the question is whether, in principle, it’s contained. The reason we’re asking this question is not because we are desperate to find this information, but we are a little bit Desperate, but the reason we are desperate is just that, because it’s a problem that will force us to understand quantum mechanics and gravity together and how things work.

Juan Maldacena :
Because quantum, according to general relativity will look like the information is lost. And according to quantum mechanics, we would expect it to be preserved. And so there’s a conflict between the two things. And we hope that by solving this conflict, we will learn better quantum gravity. The most important problem of quantum gravity is not the black hole information problem. No, the most important problem, quantum gravity, is to understand the beginning of the Big Bang. So understand what happened in the very beginning. That’s really the problem that I would like most strongly to solve.

Juan Maldacena :
Right. But the black hole information problem has the advantage of in more concrete problem and that we have some tools to address it. So that’s why there is effort and progress in this problem.

Brian Keating:
And getting back to my question about real black holes that aren’t static, that have charge, that spin, is that true? Is it also true that, you know, you get the exact same Hawking radiation, or if not in a maximal Kerr black hole. So we should say what that is. But in a black hole with an ergosphere like interstellar, you know, think about gargantua, real black holes, do they have the same phenomena?

Juan Maldacena :
The question is whether real black holes are emitting Hawking radiation. The problem is that the temperature for real black holes that we’ve known, we know they exist. They have masses of order solar mass or higher. Those black holes have a temperature which is very small, many orders of magnitude smaller than the temperature of the cosmic microwave background. So even if the black hole didn’t have any matter swirling around, which they do, and that matter is at even higher temperatures, even then, even just the cosmic microwave background would be swamping the Hawking radiation in the sense that the cosmic microwave background would be falling into the black hole and the Hawking radiation would be a tiny effect. So the answer is no. For the big black holes. Hawking radiation is an irrelevant phenomenon.

Juan Maldacena :
And it of course hasn’t been observed and there is little. Well, it’s probably not going to be observed anytime in the foreseeable future for astrophysical black holes. This would make you think why people think about Hawking radiation if it is such an irrelevant thing. But I would like to point something out which is that this phenomenon of Hawking radiation inspired the theoretical development of discovery of some other phenomenon, which is the generation of fluctuations in an expanding cosmology. So in a black hole, there is a horizon or there is a region. You can’t observe and can access. And that’s somehow ultimately responsible for this thermal effects. If you live in a universe that is expanding fairly rapidly, like as we think it was during the early epochs of inflation, then you expect a similar thermal effect.

Juan Maldacena :
And that temperature and the associated phenomenon will change the properties of the inflaton and will produce fluctuations in the shape of the inflaton. And we think that that’s the leading theory for the generation of the primordial fluctuation. So the fluctuations that make the universe not perfectly uniform. So the universe is somewhat uniform at large scales, but not perfectly uniform. Well, as you know very well, you’ve been studying this in homogeneities for. During your whole career and made wonderful discoveries. But it’s ultimately a similar. We think they also arose from quantum fluctuations, and it’s the same phenomenon as Hawking radiation.

Juan Maldacena :
So in this case, learning something for black holes. So Hawking’s paper was earlier than the papers that discussed this phenomenon in inflation, helped us understand something about cosmology that now forms part of more or less standard cosmology, I would say. And we similarly hope that understanding these other aspects of black holes will help understanding, you know, earlier epochs of cosmology.

Brian Keating:
Right.

Juan Maldacena :
So in some sense, the idea that phenomena discovered for black holes could be helpful for cosmology has already happened and we hope to repeat this. That’s our hope.

Brian Keating:
Hold on to that, because what Juan just said about black holes accidentally gave cosmologists the equation explains what the universe has structure at all. That’s not a small footnote. And that’s where I come in.

Brian Keating:
We’ve only discovered black holes with much more large masses than the sun, and yet the ones that are most likely to produce observable Hawking radiation are the small ones. And I kind of always meant to me, you know, for people that conjecture that, say, primordial black holes could be dark matter or could have truly existed since the dawn of time, basically, that sort of is hard to reconcile. So what do you make of attempts to solve the missing matter problem and even recently solve some dark energy phenomena using black holes, basically, which may or may not be primordial from the particle

Juan Maldacena :
physics point of view and from the model building point of view, they are not the most. I would say they are not the most natural thing or not the simplest thing you could think about. And for dark matter. So there are maybe other particle physics ideas that might seem more likely, but. Well, we’ll see. I mean, maybe, maybe they are. And of course, if dark matter is black Holes in the range where they are allowed, then Hawking radiation would be relevant. So I mean would be present and would be bigger, the temperature would be higher than the CMB temperature.

Brian Keating:
You are known and kind of remarkable to me because you study things at the forefront of theoretical physics, but you also aren’t afraid to take on philosophical kind of discussions. And one of the papers I think read from 2024 is called real Observers Solving Imaginary Problems paper. What is that? What was the purpose of that paper? And I want to talk later about your, your Beauty and the Beast paper. You have such great titles.

Juan Maldacena :
That paper had to do with computations in the cetar space. More precisely, it is sometimes useful to consider the Euclidean version of some space times. Euclidean version is basically you take the usual universe and you make the time, you change the sign in the metric in the time direction and that makes a space which is purely spatial. And in the case of an expanding the cetar universe, that is a sphere, so you can consider Einstein gravity on a sphere, we would expect that type of universe to be computing the thermodynamics of the sitter space. The reason is the following, that evolution in imaginary time, or this procedure I’ve just mentioned is useful because if you solve that evolution, you are basically calculating the thermal partition function or you’re calculating thermodynamic properties of the system. This is something that is true for any physical system. And if you do that for the sitter space, you would expect that it should be telling you about the thermodynamics of the sitter. Now, this is not a new idea.

Juan Maldacena :
This idea, well goes back to Gibbons and Hawking. If you do that, then you get that this theater space has some entropy, which is the area of the horizon. So formula very similar to the black hole entropy formula in that paper was the same time as they discussed also the same thing for black holes. Now all of this is perfectly nice and so on, but if you calculate the first quantum correction, so calculate not just the Einstein action for the sphere, but also the quantum fluctuations, including the quantum fluctuations. The quantum fluctuations they would give a negative value for the partition function. So the number of states would be negative and depending on the dimensions. In some cases it’s imaginary I to the power of the number of dimensions of space time. So this was something confusing that was found by.

Juan Maldacena :
But I think Hawking already noticed that there were some issues with some sign. Polchinski calculated more precisely what the sign is. More recently with trying to understand better the physics of the sitter space. It was understood that in order to construct the Hilbert space, it was useful to include an observer, so that you include an observer. And the degrees of freedom of the observer were important, some of the degrees of freedom to define the Hilbert space. And so what that paper did was notice that if you don’t consider just a sphere, but the sphere with the trajectory of a particle, then there are some other minus signs from the trajectory of these particles or some other I’s that cancel the. And then you get something nice and positive. Well, actually, in the paper, I originally got something positive.

Juan Maldacena :
Then Victor, I was a student of mine, pointed out a mistake. Then I got something negative. And then eventually a group from Stanford, with Douglas Stanford and collaborators, they found another mistake. And so now it’s positive. So it’s a triple negative. Yeah, triple negative. Well, that’s how many things work in science.

Brian Keating:
I remember reading A Brief History of Time. I started reading it in high school. I couldn’t finish it until I. In fact, I didn’t finish it until about five years ago. But it was a good thing I didn’t because I don’t think I could have understood kind of what he was doing in that book until much, much later. But one of the things, when he brings up this, you know, kind of what’s called a wick rotation, right?

Juan Maldacena :
Yeah.

Brian Keating:
He brings it up and he says, well, imagine we’re just going to build this as a trick. You know, we’re just going to do a trick. We’re going to introduce imaginary time, you know, the number square root of negative one in front of the time component. And when we do that, it’s called a wick rotation. And then we can solve all these things as if it’s taking place in Euclidean space. So it’s, it’s. But don’t worry, dear reader, it’s just a simple. And then the rest of the book is just basically assuming that’s true.

Brian Keating:
And then he goes on to say, and then we’ll have the mind of God. What do you make of this? I mean, what is the reality of it? I guess I’m asking Wigner’s question, why is math so useful? One thing that always blows my mind, and I try to impress it on my students, is in classical mechanics, we have Lagrangians, we have Poisson brackets. You can do all sorts of things. If you take a Poisson bracket and commutation bracket, you get the product of these things and they cancel out. The Poisson bracket for classical observers is zero. But if you, if you say it’s quantum mechanical you do the commutation relation, you get the square root of negative one and all of a sudden all of quantum mechanics can emerge from it. It’s sort of bizarre, right? At what level are these things tricks? I mean, when you see the imaginary number and you talk about in this paper, is it real? Maxwell’s fields have imaginary solutions too. They’re not real, but we can observe only real things.

Brian Keating:
So where does a person go with this?

Juan Maldacena :
I like a story that apparently Lorentz, so that’s the same person of the Lorentz transformations, he was tasked with calc how water gets into the various canals and how to design some dams and so on. So some people, they wrote a report on how this should be calculated. And in the beginning of this report he says, well, we are going to use complex numbers, but it’s just a trick at the very end, all the heights of the water and so on are going to be real, don’t worry about it. And I guess at the time it was thought it would be necessary to explain this point. Now, any engineering student that uses complex numbers to solve these type of problems with oscillations and so on, and yeah, well, it’s a trick, but it’s a trick that simplifies. In that case, it’s a trick that simplifies the calculation. And in this case maybe similar. So everything we measure, we always measure real numbers.

Juan Maldacena :
And so the imaginary numbers, that’s how they were invented for discussing the roots of polynomials and so on. But they are useful tricks. And I. Yeah, but it’s true that it’s a trick that is used so often and so much that it seems that there is something deep about it

Brian Keating:
when we think about all the other mathematical structures. So you start off with the square root of negative one, you get quantum mechanics, you get all sorts of interesting phenomena. Then you have spin 1/2 particles can be described by these SU 2×2 matrices that are complex. And then later you can have su, you can have quaternions, and then I think there are octonians. But then nothing like people obviously could keep going, right? All powers of two. But does anything correspond to whatever hexasexadecimal D?

Juan Maldacena :
Well, the problem is the complex numbers have many of the properties of ordinary numbers. And once you start going to these other ones, they don’t have all the properties of ordinary numbers and you start losing some of the properties. So they become, I would say they become less useful. I mean, quaternions were invented and they could be useful for describing rotations in space, but they are not used that much. I mean, it’s not something I. I’m not sure whether engineers use it, for example, for this purpose.

Brian Keating:
I think they’re using like AI and some AI applications, I guess for rotation.

Juan Maldacena :
Yeah. Well, maybe they’re used for some things. I wouldn’t.

Brian Keating:
I want to talk about one of the things you’re most known for. When I was getting my PhD, you know, in late 90s at Brown, I remember some conference and everyone’s so excited and at the end they did the Macarena, but they called it the Maldicena. Take us back to those times. About this ADS cft, what is it? How did you come upon it? Give us the origin story.

Juan Maldacena :
Well, adsft is this connection between universes which are large and with negative cosmological constant. So that’s an ADS anti de sitter space time. So the CETR is the one with positive cosmological constant. This is with negative cosmological constant. And CFT is a type of field theory. So field theory is theories that we use to describe relativistic particles and conformant means it has some scaling symmetry. And the idea is that these two are connected. It’s this instantiation of this holographic idea.

Juan Maldacena :
So it’s a concrete example. Yeah. So that conference took place after this paper and after people had well worked on it and there are many other interesting properties. And so Jeff Harvey wrote this song. I mean the Macarena was the song that was popular at the time.

Brian Keating:
What do you say to people that often have said the mathematics like with string theory is beautiful, but we certainly don’t seem to live in ADS space. So is it just pure again, like a wick rotation? Is it something that we should use as a useful tool or could it describe reality and we just haven’t found evidence for it?

Juan Maldacena :
Well, we made a sign error, of course.

Brian Keating:
Okay, typo. We got to retract it. Paper is zero citations.

Juan Maldacena :
Yes, yes. So the cetar space is much closer to our universe. And I would very much like to have something. I mean everyone would very much like to have something like this in the Cedar space. And hopefully understanding the anti de sitter case will be useful for understanding the de Sitter case. I hope that the understanding of the de Sitter case would have happened already and I hope it will happen soon. But maybe we’ll need maybe a new conceptual idea. So people who say that this is not the physical universe are correct.

Juan Maldacena :
But you know, we hope it’s close enough that we can extract some lessons.

Brian Keating:
The other thing we talked about briefly in our last conversation four years ago. I can’t believe it was wormholes and even humanly traversable wormholes. What is a human traversable wormhole? What good is it other than for solving a lot of issues in Hollywood, where you’re off to tomorrow.

Juan Maldacena :
Yeah. Before I discuss what the wormhole is. So, in Einstein theory, the structure of space time is dynamical and curves. So the space time can be deformed, Right? Okay. So it can be deformed a little bit. And, you know, when Einstein developed his theory, he thought, okay, these deformations will be small. Then there were some even larger deformations, like black holes. And, okay, that’s more drastic thing.

Juan Maldacena :
But then you can have some other types of deformations where you drill a hole in space time and you connect to another region of space. So you can have, for example, a space time like this. Imagine a membrane. You dig a hole in these two portions of the membrane, and you somehow connect them, but you connect them through a tube that is not embedded in this spacetime. It’s just a very short tube.

Brian Keating:
My Klein bottle over there.

Juan Maldacena :
Yeah. Something exotic like this. So, and the question is, are these configurations allowed? Are they possible in general relativity? Science fiction authors love it because you could go in one end and come out in the other, and you could travel faster than the speed of light, for example. This is something that they could allow if they were possible. But it would be a little funny because the structure of special relativity and general relativity is based on the idea of a maximum speed for propagation of signals. In general relativity, you are not allowed to put any space time. So you’re not allowed to say, oh, I have this space time. You have to obey certain equations.

Juan Maldacena :
And the equations roughly say that the curvature of your space time should be equal to the density of matter. Then you can say, okay, fine, if I want to build some space time, I just put appropriate matter, and then I will be able to have any space time I want. But then there is a catch. Because matter has to obey certain properties, you cannot have matter, let’s say, with negative energy or things like this. At least in classical physics, you can’t have that. And once you put in that constraint on the types of matter you are allowed to have, then you forbid this type of worm. The wormhole’s attack would allow you to propagate faster than the speed of light. That is also forbidden in the full quantum theory.

Juan Maldacena :
In the quantum theory, we think that in quantum mechanics, you are allowed to have a little bit of negative energy, but not Enough to have a wormhole that would allow you to travel faster than the speed of light. So those type of science fiction wormholes are not allowed according to the laws of physics as we know them. And this is not something that depends on the detailed structure of the standard model, but is something that depends on relativistic quantum field theory. So the principles of relativity, which are the principles on which this whole picture of space time is based, and the principles of quantum mechanics, they do not allow such a thing. I think this is a beautiful consistency condition between the two theories because the, and this issue with this wormholes, which is some property of general relativity, they depend on some quantum property of matter. If quantum matter didn’t obey this property, then you would be allowed to violate the, you would be able to send signals faster than the speed of light, creating these wormholes. So those are not allowed. And this is a nice theoretical result, important theoretical result, but this does not forbid wormholes that, where it would take longer for you to go, right? So you could imagine a non trivial topology where there are two holes and they’re connected by a long tube.

Juan Maldacena :
And it takes you longer to go through the tube, at least I’ve seen from someone outside, than the time it takes to go between the two mouths. And recently it became possible to construct some solutions that are of this kind. So they require certain types of matter, in particular charged fermions, which are massless and so on. So they could exist as solutions at very microscopic scales where you can approximate the Fermi of nature as being massless. Those would be very tiny. Or you could say, well, I have some very special type of dark matter that is dark matter specially designed to make wormholes. And then you could have a very, very big wormhole that could be humanly traversable, that the person can traverse meter scale, Right? Yeah. Well, to make them this way, you need them to be actually much bigger than meter scale.

Juan Maldacena :
And, and the reason is kind of interesting. It’s because. So these are structures where there is some space time curvature and we are quite sensitive to tidal forces. So you need them to be roughly the size of the Earth for it not to kill you when you are traveling.

Brian Keating:
Well, that’s beneficial. We could transport whole planets. Why stop at astronauts when you can have all people?

Juan Maldacena :
That size is just so that the curvature is small enough that they would not kill you.

Brian Keating:
Ah, right, I see. If you and Einstein were together in 1983, 1913 or 1911, say after his happiest thought about falling on an elevator and experiencing no gravitational field, and you gave him an LLM and a GPT and a gpu and you had the most powerful system. Do you think he could have come to? Or you guys together could do stuff that you couldn’t do without an AI? In other words, someone operating at the highest levels of theoretical physics. What level of. I mean, I use LLMs all the time, but I don’t see them creating new physics anytime soon.

Juan Maldacena :
Well, we’ll see. We’ll never say never. The field is advancing quickly and we’ll see. We’ll see what happens.

Brian Keating:
Yeah, I was an altar boy in the Catholic Church in Westchester county, actually in Chappaqua, New York, where the Clintons now live, as it turns out. And I loved it. I thought it was awesome. It was 1984, 1985 and. And then the Pope, John Paul II, who was in my opinion the greatest Pope in history, maybe I loved him. They came out with a decision that Galileo was right, but they never really forgave him. And I understand that you remember that Catholic Scientist Society. How do you reconcile.

Brian Keating:
Do you feel like there’s a tension? I always thought they should just say he was right, he was pardoned. How do you reconcile the so called kind of tension between science and religion?

Juan Maldacena :
I think, yeah, the Galileo was a very. Galileo thing was a very unfortunate case. But there are, well, there are many other cases of scientists that reconcile their faith with their. And we’re talking about cosmology, for example. Lemaitre, who was one of the people who created the Big Bang theory, he was a priest and he reconciled. So I think there isn’t a fundamental issue, but as science progresses, we have to change how we understand religion or we. And also religion can illuminate some scientific. Well, not some scientific questions, but some issues that arise because of science.

Juan Maldacena :
Right, Yeah, I know we have now very powerful weapons and we have some responsibilities that are very important. Very moral responsibilities.

Brian Keating:
Yeah. And how to adapt. People are so obsessed with artificial intelligence, but I kind of feel like we need artificial wisdom. Like intelligence is in plentiful, but somehow it’s more important to get wisdom. And I don’t see science providing wisdom. It provides knowledge. I mean, that’s what science means in Latin. Right.

Brian Keating:
But it doesn’t mean wisdom. So yeah, from my perspective, they can be partners, you know, science and religion, I don’t see them as foes or in opposition. But yeah, people that try to derive one from the other, like prove that the Big bang happened using the Torah, you know, using the Bible. I think that’s not great.

Juan Maldacena :
When the cosmic microwave background was detected. So the pope wanted to say actually that now we saw the beginning of the universe, the hand of God and so on. And Lemaitre told him, don’t wade into this. Just don’t say anything because,

Brian Keating:
yeah, that’s right, it could change. And back then they thought the earth was older than the universe. That was quite embarrassing. Well, let’s see. We got to get you to your talk, but before we do, I have a gift for you. Not a Nobel prize, but it’s called the Keating Prize. It’s not too arrogant of me. So it has Arthur C.

Brian Keating:
Clarke on the front because the podcast comes from him and it says the Keating Prize for impossibly good imagination. And then a meteorite which is a fragment of the early solar system that somehow magnetically attaches to the monolith on the back and has your name on the side. Juan Maldivesena. Thank you so much for coming to see you.

Juan Maldacena :
Enjoy. Thank you very much.

Brian Keating:
And then you’ll add it when you win the Nobel Prize. You could add them together.

Juan Maldacena :
Right, Right.

Brian Keating:
Great. Thank you so much for being on. And stay tuned. Watch the lecture on black hole entropy and thermodynamics coming up next.

Brian Keating:
Juan told us today that he thinks the structure of space time is built out of quantum entanglement and that the deepest problem in physics isn’t black holes, it’s the big bang. Now, if that changes how you think about reality, reality. Hit subscribe and turn on notifications. Drop a comment, let me know what problem you think Einstein would most like to see solved if he came back. And you’ll want to go deeper. And check out Juan’s two part lecture on my second channel, Keating Experiments. I’ll link down here. And if you want to go deeper, you’re going to want to watch my conversation with Leonard Susskind talking about the black hole wars using the language that he and Juan invented.

Brian Keating:
The link is right here. Don’t forget to like, comment and subscribe and I’ll see you next time.

Princeton Scientist: We Don’t Understand AI | Tom Griffiths

sabartigas — Thu, 30 Apr 2026 14:30:49 +0000

Princeton Scientist: We Don't Understand AI | Tom Griffiths

Transcript

Tom Griffiths:
One of the, I think, interesting challenges we have at the moment is having built systems that we don’t fully understand.

Brian Keating:
The man who built modern AI, he’s the direct descendant of the man who invented the math that made it possible, which is insane, but it’s not the wildest thing. My guest told me today.

Tom Griffiths:
That’s pretty much exactly what he was trying to do. And he was the right kind of crazy.

Brian Keating:
Ibns was trying to invent AI 250 years before computers even existed.

Tom Griffiths:
Sycophancy is a major problem. If you take a rational agent and have them interact with a system which is sycophantic, then that agent is going to become increasingly confident in their beliefs, but no closer to the truth.

Brian Keating:
My guest spent 20 years building the mathematics of how minds work, and he just told me three things that made me question what I thought AI actually was. Now, let me show you. From a physicist point of view, whenever

Brian Keating:
I talk to people about consciousness, from Chalmers, Bostrom, and upcoming guest Joshua Bach and others, I always get the same thing, like we can’t really define what consciousness is, so how do we know what thought is? So how can you determine what the laws of thought are? Isn’t that kind of a extremely provocative and bold claim?

Tom Griffiths:
The way that I approach that question in the book is really by thinking about what are the kinds of computational problems that minds solve? And that’s really what this enterprise was. It’s trying to figure out, like, what’s the mathematical structure that describes the thing that minds are doing, whether that thing is what Aristotle was interested in, which is just trying to characterize what good arguments are through to some of the questions that you were raising about what does it mean to make a good decision and how do we think about rationality in that context? And so the interesting thing is, I think a lot of those questions are things that we can answer without ever having to touch consciousness. I think about one of the big challenges of studying consciousness is that we don’t necessarily know what computational problem consciousness is solving. That’s why it’s something that’s continued to be mysterious. We don’t really know what it’s there for in terms of how necessary it is to being able to do kinds of things that minds do. And our AI systems give us nice demonstrations. You know, again, some people might want to argue that they’re conscious in some form or something like that, but I think they give us nice demonstrations of how far you can get using certain kinds of mathematical formalisms.

Brian Keating:
Yeah. And there’s many, many kind of allusions to physics in this book, which is so delightful in many different ways, not the least of which because it gives us some kind of formalism to hopefully go about this problem. But I, you know, as a physicist is want to do, I want to kind of get into what you would say maybe what is briefest kind of most parsimonious, defensible definition of thought itself and the laws that govern it.

Tom Griffiths:
In the book I focus on deduction, which is sort of like patterns of logical reasoning going from things that are true to other things that are true. Induction, which is sort of seeing a pattern in the world and then making the generalization that thing holds in general and then abduction, which is seeing something that you want to explain and then coming up with an explanation for it. And I think that’s a pretty good characterization of the set of things that we normally have on our list when we want to try and explain sort of patterns of thinking. And those are the things that we try and engage with in terms of like the different kinds of mathematical formalisms that are explored in the book.

Brian Keating:
There’s an awful lot of discussions of both the successes and our understanding of consciousness and the wrong turns. And I like that because for me personally, I hate when we teach our undergraduates as often as done. You know, we basically just teach them the string of Nobel prize winning experiments and you know, just connect the dots and that’s. But you go through the, you know, the twists and turns and I thought one of them was, was sort of brought up this, this conjecture that, or this statement by Feynman, which is that the, you know, kind of the difference between knowing the name of the thing and knowing something about it is the most dangerous gap in all of science. What are some of the inherent biases that, that science has brought to it because it’s such, such a Frankenstein type field? Cognitive science, you know, start off with, with not really, as you discuss in the book, really being taken seriously. And now it’s, you know, at the cutting edge. What is the sort of, you know, largest gap or the biggest lacuna in, in your field where people seem to maybe be overabundant of confidence in describing how models work or even the model of the brain, let alone models of artificial intelligence.

Tom Griffiths:
So one of the, I think interesting challenges we have at the moment is having built systems that we don’t fully understand. Right. So we now have these AI systems that for computer scientists put them in a very unfamiliar situation, right, where if you’re a computer scientist, you’re used to programming Something, and because you programmed it, you kind of know what it’s doing. And that is not how our AI systems work. So these modern AI systems are built using enormous artificial neural networks. And they learn from data, far more data than any human could actually read through and understand. And so you end up with something where it’s both learned from a sort of incomprehensible amount of data and encoded that information in an incomprehensible number of continuous weights inside that system. And so as a computer scientist, you’re then stuck and you’re like, oh, what do I do with this? I actually think that’s a good opportunity for cognitive scientists because we have been trying to study large, complex systems that we don’t understand for about 75 years now.

Tom Griffiths:
Those systems are human brains. And a lot of the tools that we built for understanding human brains and how it is that humans think and behave are tools that we can now use to go back and really analyze these AI systems and try and understand a little more about how they work as well.

Brian Keating:
What would the advent of ChatGPT, what sort of thing would that be like? Is it the invention of the telescope, the cyclotron? What does it represent in your field?

Tom Griffiths:
I think it’s interesting. I’m not quite sure what the analog is. Is. It’s both a kind of, like, breakthrough in terms of revealing certain kinds of theoretical ideas can take us further than we might have thought, but also something that’s given us a new set of problems in terms of trying to understand what that system is doing and then trying to figure out what all of its properties are and what the consequences of using those systems in certain kinds of settings is. It’s both the validation of a theoretical approach, but also the creation of a new sort of field of inquiry.

Brian Keating:
I talked to Steven Pinker about his most recent book. We had a conversation about that where humans use these heuristics and computational shortcuts. And you bring up a couple of these in the book. And I wonder if you could tell some of the stories of Kahneman and Tversky and how they illuminated this kind of shocking at the time claim that humans are necessarily not the best reasoners or not as reasonable as we think we are. Right.

Tom Griffiths:
Yeah. So there’s an interesting paradox in trying to study human cognition from the perspective of computer science. Right. So I live in these two departments. I live in the psychology department and the computer science department. And in the psychology department, my colleagues think humans aren’t that smart. Right. If you kind of like study Human decision making.

Tom Griffiths:
You find out that humans have all sorts of simple heuristics they follow that result in systematic biases. And that’s the work that Carmen and Tversky did, was really kicking that off and giving us this picture of human cognition. And then if I walk across campus to the computer science department, humans are the things that we’re trying to emulate when we’re building our AI systems. So they’re sort of our best examples of systems that can solve certain kinds of problems. And so I think that tension is about the fact that the way that I would resolve it is that humans are actually good at solving a set of problems that are extremely hard problems to solve. And they’re not always necessarily solving exactly the problem that a psychologist asks them to solve when they sort of study them in the lab. So a simple example of this is, is if you flip a coin five times, which of the following sequences is more likely? Heads, heads, heads, heads, heads, or heads, heads, tails, heads, tails. If you just ask someone on the street, they’ll probably say that heads, heads, tails, heads, tails is more likely, right? But as a trained physicist, the probability of those two sequences is equal.

Tom Griffiths:
As long as it’s a perfectly fair coin, Any sequence of five heads or tails is equally likely. And so one way to understand that that’s an error that humans make. That’s the kind of thing you could point to and say, humans are irrational. We’re biased in this way. But one way to understand it is to say, what if the human is not solving that problem, but solving a different problem? So they’re being asked to give you, what’s the probability of this sequence under a random generating process? What if they’re flipping that around and telling you, what’s the probability that a random generating process produced this sequence? Or sort of, how much evidence does the outcome give you for having been produced by a random generating process? And that’s something we can calculate using Bayesian probability. And when you do that, it turns out people’s judgments about randomness are very systematic, and you can capture them with a nice simple Bayesian model. But that’s a case where we’re sort of like reanalyzing the problem that human minds are solving. When you reanalyze it, it turns out people are doing a good job of solving that problem.

Tom Griffiths:
And in some ways, it might even make more sense to be solving that problem. Because if you’re wandering around in the world, it is very unusual for you to have to calculate the probability of sequences of things. But It’s a good thing for you to be able to detect patterns that might suggest that something is non random, and that’s probably what our brains are built to do.

Brian Keating:
A central character in this book is past guest Noam Chomsky. And it’s always been sort of, you know, kind of curious to me that his, you know, notions of generative grammar and so forth, you know, explain a lot from so little, or seem to explain why, you know, for example, our children can learn language, you know, with far less training data, if you will, than can computers, these huge, huge data sets with trillions of parameters.

Tom Griffiths:
Now.

Brian Keating:
But talk about his role in understanding how, you know, separate from AI, there’s a clue to the laws of thought that emerge, you know, that caused the whole field of cognitive science to emerge. But it really is, you know, predicated on fairly elementary questions. It doesn’t mean easy or simple. It just means that they’re basic and important. Talk about Chomsky’s role in all this and whether his ideas are still pertinent to experts like you in the field today.

Tom Griffiths:
So part of this story about people trying to use math to understand thought, it occurs in the middle of the 20th century, when psychologists had decided that the only way to be rigorous about doing psychology was to not talk about thought and not talk about internal mental states. So this was an approach called behaviorism. And the behaviorists said you should just focus on the things that you can measure, which are the environments that people act in and the behaviors that result from those environments. And so there was a group of sort of revolutionaries. There was what was called the cognitive revolution, which were psychologists and linguists and computer scientists who were interested in finding a different way to study the mind. And they did this by saying another way to be rigorous about minds is to use math to express hypotheses about how minds work that we can then test through behavior. And so they did that using the kind of math that was most sort of obvious and accessible to them, which was the math of rules and symbols. Inspired by computers and logic and these sorts of formalisms that were very prominent in the 1950s.

Tom Griffiths:
They set out to test out, how well does that describe how minds and languages work? And so Chomsky took that approach and applied it to language. And he set up the problem in a way that was different from the way that previously linguists had thought about the problem. Linguists had kind of thought about their job in linguistics as characterizing the structures of different languages and then maybe looking for sort of commonalities and regularities in the structures of those languages. And Chomsky said, well, actually, if we kind of think about this as a math problem, a language is some set of sentences that you’re allowed to produce, and let’s characterize that set in a very mathematical way by specifying a generator of that set. So he thought of a grammar as a system of rules that you could follow to generate all of the valid sentences in a language. And that approach, what’s called generative grammar, became the foundation for much of theoretical linguistics, certainly through the 20th century, and then, you know, continues to be influential today.

Brian Keating:
You talk about sort of a chessboard analogy with Chomsky. Can you sort of go through that on different types of moves? You start off with the initial, what is it, 16 moves that can be made by each player.

Brian Keating:
Talk about what?

Brian Keating:
That analogy. Go ahead and explain it, this chessboard analogy.

Tom Griffiths:
So you can think about this problem of defining a generator of a set. A good way to think about that is something like a board game, right? So the rules of a board game are a set of principles that tell you what the states of the board are that you can reach, right? And so you start out in some configuration. Chess is a good example, right? You’ve got all your pieces laid out. The rules tell you how to set up those pieces, and then you can make all of the moves that you can make from that position according to the rules, and that’s going to take you to the next position, and then your opponent makes their moves that takes you to the next position. So, yeah, if you have 20 moves for your first move, the other person has 20 moves. At this point, there’s already 400 configurations of the board that you could have reached, and that number keeps increasing exponentially as each subsequent move is made. At the end of making all of those moves, you get to the end of the game, and by following the sequence of rules, you’ve generated all of the possible games of chess. And so that’s his idea, is that just as there’s a set of kind of like, you know, games of chess that you can follow final board positions that you can reach, there’s some set of sentences that are the things that are in English.

Tom Griffiths:
And maybe we can come up with an analog of the rules of chess that generates all of the valid sentences in English.

Brian Keating:
One of my favorite aspects of the book is you kind of trace through the history of thinking about, thinking, metacognition, whatever you want to call it. And you start with Aristotle. I love Aristotle. Who doesn’t? But his claims to fame in physical sciences are not so strong, right? I mean, they haven’t really held up as. As well as his laws of. Of thought or logic. I mean, he. He thought that things fell to the center of the earth because heavier things fell faster than lighter things, which Galileo disproved, you know, with a simple, you know, allegedly dropping two objects off or even a thought experiment.

Brian Keating:
You know, speaking of the laws of thought, of the role of thought experiments is not insignificant. But he thought that, you know, women had fewer teeth than. Than men. He had a wife because he had a son. Nicomanchin. Right. Nicomancius was his son. Right.

Brian Keating:
Tom?

Tom Griffiths:
Yeah. I think you know your Aristotle better than I do.

Brian Keating:
Well, the one claim to fame is that he knew that whales were mammals. But why does Aristotle, you know, get so much right about thought? And how can that possibly still matter, you know, 24 centuries later?

Tom Griffiths:
I think part of that is that he was doing math, essentially, right, when he was thinking about thought. So what Aristotle did. He had two projects that I talk about in the book, and the first of those was the part that’s about deductive logic. And this is setting up the set of syllogisms. So a syllogism is a simple argument with two premises and a conclusion. And these are sort of familiar kinds of things you’ve probably seen in school. It’s like, all A’s are B, all Bs are C, therefore all A’s are C. Right? And so that’s an example of a syllogism.

Tom Griffiths:
And he was interested in characterizing what’s the set of these syllogisms and then which of these are valid in a way that’s actually quite like that sort of Chomsky problem, right, of being able to say, you know, like, what are the good ones and what are the bad ones? And so that was really a matter of just enumerating. So he was kind of like doing the combinatorics of these kinds of arguments. He enumerates all of the arguments. He says some of these I know are good, and I’m just going to say those are good ones. And then he makes little mathematical proofs to relate some of the other arguments back to the ones that he knows are good. And he can sort of say things about those, too. And so I think his success there was that he was involved in exactly the kind of mathematical enterprise I talk about in the book. He then had a challenge that was left over from that, which is like, you know, exactly the Chomsky challenge.

Tom Griffiths:
Again, can I come up with A mathematical system that characterizes the good ones, right, and separates them from the bad ones. And then that’s the challenge that was picked up by Leibniz and later by Boolean.

Brian Keating:
So let’s get to Leibniz, because you mentioned him. He had this dream, which seems kind of insane at the time, to, you know, logify or to codify, to mathematize our reasoning. So was he basically trying to invent AI 250 years before computers existed?

Tom Griffiths:
That’s pretty much exactly what he was trying to do. And he was the right kind of crazy, right? He really was someone who had a vision that far transcended the times that he lived in and made contributions to a huge number of different disciplines. As a consequence, he was obsessed with the mathematics of combinations, interested in all kinds of mathematics. He contributed to the calculus and so on. He built a calculator, a mechanical calculator that was able to. To do more sophisticated things than the other mechanical calculators of the age. So he had all these pieces where he knew, kind of like, what mathematics could do. And he knew that if something could be expressed in mathematics, it could be executed by a machine.

Tom Griffiths:
And so those things came together. He’d been studying logic since he was a kid and reading Aristotle. And he had this dream of being able to take Aristotle syllogisms and then figure out a mathematical system that would let him essentially then run this on his calculator so that if anybody wanted to have an argument about something, he could put it into the machine and then turn the handle and out would come the answer about who had it right.

Brian Keating:
Maybe he was just too early, or is it really possible to do what he was attempting to do? Maybe he underestimated how hard representation would be.

Tom Griffiths:
He had some really good ideas that, again, were ahead of his time. And then he had one thing that he hadn’t quite figured out. And so the really good ideas were he’s the person who invented this idea of vector embedding, as far as I’m concerned. So the way that he tried to solve this problem was by taking the terms that would appear in those syllogisms, the A’s and the B’s and so on, and trying to represent them with a little vector of numbers. So he would associate, in his case it was just two numbers with each of those terms. And then he tried to find the relationships between premises and conclusions by then reducing this to regular arithmetic, where you’d have the number 33 and the number minus 77 associated with 1 of the terms. And then if that could be divided by the numbers for another one, say it was like 11 and 7, that would be something where you could say, okay, now the conclusion is going to follow from that. And so he kind of worked out this system that was just based on arithmetic, having vectors that you are modifying through these arithmetic operations.

Tom Griffiths:
That was really smart. That turns out to be really important for AI today. That’s how language models represent words as well. The thing that he, he hadn’t quite figured out and sort of got glimmers of at the end of his life was that he didn’t have the right algebra. Right. He was like using regular arithmetic. And it turns out in order to capture the content of the syllogisms, you need something that’s a little more complicated than regular arithmetic.

Brian Keating:
Yeah. So let’s segue into George Boole and what did he really change? And most of us, if we know about Boole, his name, it’s from Boolean logic and computer circuits. And we stop there with the Xnor and all the other circuit diagrams you talk about in the book. But in your telling, Bull is a much more important character. So what do we get wrong about him?

Tom Griffiths:
He was sort of genius who went beyond the moment that he was in. He spent most of his life as a schoolteacher, and even as a schoolteacher was corresponding with the leading mathematicians of the day, publishing really influential papers. He ended up winning this gold medal in mathematics from the Royal Society. And that was sort of his precursor to the contributions that he made to logic. But his skill as a mathematician was really around these kind of algebraic ideas. And he had essentially taught himself this perspective on mathematics by reading hard math books from France that no one else in England was really reading. And he said he enjoyed reading these big thick math books because it was the best way to get his small allowance for books to last as long as possible. And so he had this toolkit that was the one that Leibniz was missing, which is this algebraic toolkit.

Tom Griffiths:
And then he could recognize that in order to capture the structure of thought, you needed this slightly different algebra. And then that’s the thing that we now associate with Boolean. But his work really went far beyond that. The title of my book, the Laws of Thought. He was someone who was actively involved in this 19th century community of people who was trying to characterize what the laws of thought were. And his big book was called An Investigation of the Laws of Thought. And my epigraph comes from Boole as well. And in that book he laid out both the Kind of foundations of this mathematical logic, but also principles of probability theory that he thought were going to be the way to extend this, to solve other kinds of problems of thinking

Brian Keating:
as well, presaging a lot of what we have come to use. Is it a question of efficiency that it’s just super efficient to do things with zeros and ones and, and you can reduce all sorts of these abstract thought concepts to zeros and ones? Or is it not merely the computational efficiency that caused the success?

Tom Griffiths:
I think it’s that by expressing things in that way, he was able to then do the thing that Leibniz wanted to be able to do in terms of now it was possible to think about creating machines that would be able to execute these kinds of computations. So Bools work was then developed into a richer theory of mathematical logic. That fact that you could express mathematics in a mathematical form itself. You could take statements that were mathematical statements and express them in logic and that would turn them into math themselves. That became the foundation for a lot of work on asking questions about the limits of mathematics. That inspired Turing to think about what’s an abstract kind of machine that you could use to, to do these kinds of calculations to emulate the mind of a mathematician. And then von Neumann figures out a scheme for building these machines that still underlies the computers that are on our desks today.

Brian Keating:
Do you think that von Neumann machines, Turing machines, etc. Do you think that they will be kind of permanently ensconced in this discussion or other architectures and even other approaches towards AI? Will they eventually supersede based on efficiency the same way that Boole was able to supersede in some sense, Leibniz?

Tom Griffiths:
Yeah. So Turing machines were never a practical device. Right. It was a sort of theoretical abstraction for how you could describe computation. Von Neumann worked out how to have a stored program computer. Right. And so how you can have a computer which has, instead of having to rewire it every time you want to solve a different problem, it’s able to use software to modify what it is the system’s doing. And that’s a fundamental advance in terms of being able to create machines that can do all of the kinds of thinking that we want them to do.

Tom Griffiths:
Nowadays, a lot of the training of artificial neural networks is done using dedicated hardware, GPUs, graphics processing units, which are units that were originally designed to just speed up the computations required to put things on a screen. But those computations turn out to be exactly the computations that you need to do to run a neural network. And so there’s lots of diversification of specialized hardware for doing those kinds of things. It’s also interesting to note that the earliest neural networks, so neural networks that were built by people like Frank Rosenblatt and Marvin Minsky, they were also specialized hardware. They built physical neural networks that were sort of connected up by wires with adjustable resistors on them. I think that’s certainly a kind of technology that’s changing the way that we’re thinking about computation today. And a lot of the energy that’s going towards compute is now going towards GPUs. The fact that a lot of energy is going towards those is something that’s encouraging people to think about alternative models for computation.

Tom Griffiths:
If what you want to do is run neural networks, maybe we can learn things from the neural networks that run inside our heads, which run on far less energy than the kinds of neural networks that people are running on GPUs.

Brian Keating:
Yeah, you talk also in the book, I mean, speaking of GPUs, Jensen Huang was on Lex Friedman’s podcast recently. He said AGI is here. I keep saying that I’m not really convinced that AGI will be here until it could do something that human beings have never been able to do. And the clearest kind of most simple realm to demonstrate that is in the laws of math or some, you know, physical observation that we’ve never really been able to explain, you know, unifying quantum mechanics and gravity, something truly novel or at the very least, you know, replicate what, what human brains did 100 years ago, you know, long before computers. For example, if you just gave it the data on the planet Mercury from 1911 and before. Einstein certainly knew that there was this anomalous procession. In fact, GR was basically designed retrodict to explain why that behaved that way. And yet we can’t seem to get that to occur.

Brian Keating:
My student Evan Watson and I have tried to replicate, you know, could you come up with GR from just the deductive observations of data which we have hundreds of years about for Mercury? Right. So what, what is your working definition of AGI?

Tom Griffiths:
As a cognitive scientist, I would be very sort of careful about thinking about, you know, this idea of artificial general intelligence in the first place, because I think it plays into a bias that we have, which is that our best example of an intelligent system is another human being. And all of our intuitions about intelligence are based on the kinds of things that human beings do. Right. And so I think that encourages us to think about this in a kind of like one dimensional way where there’s Kind of like, here’s where humans are on this one dimensional scale of intelligence. Here’s our AI systems are coming closer and closer, and one day, oh, they’re going to be past us, and then. And either something wonderful or something terrible is going to happen. And so that one dimensional characterization, right. So this is like AI or superhuman AGI or whatever it is.

Tom Griffiths:
I think that’s not a productive way of thinking about what’s going on with our AI systems. I think a better way of thinking about it is that human minds and our AI systems are both systems that have been created to solve certain kinds of computational problems. They’ve been sort of optimized to solve those problems, but they’ve been optimized. Some of those problems overlap, but they’ve been optimized in sort of different ways and under different constraints. So human minds have evolved under constraints on just what, human lifetimes. We only live a few decades. Those compute resources I was talking about, right. We only have a couple of pounds of neurons up there.

Tom Griffiths:
And bandwidth constraints in terms of like, we’re limited in our ability to communicate with one another. We have to do things like talk to each other on podcasts in order to share information. Whereas our AI systems can have way more data than a human can see. They can potentially just scale arbitrarily in the amount of compute that they use. And you can transfer data from one machine to another, you can transfer weights from one machine to another. There’s a lot more sort of plug and play compatibility in terms of being able to spread that intelligence around. That means that the solutions that those systems find can look quite different. Where we’ve made AI systems by essentially optimizing them to solve this problem of getting a radio signal from another planet and trying to predict the things that are occurring in that radio signal to the point where they’re really good at it.

Tom Griffiths:
And they’ve even made inferences about the aliens that live on that planet and what kind of cities they live in and what kind of interactions they have. That’s the problem that the AI system is solving. And the human is doing something quite similar, but they’re doing it in a social context where they’re interacting with other humans. And they’re doing it with the benefit of thousands and hundreds of thousands of years of evolution behind them. Right. And so we end up sort of seeing similar kinds of behavior from these systems, but seeing it from two quite different evolutionary trajectories and seeing it under two quite different sets of constraints. So saying one thing is like the Other thing, I think it’s sort of misleading. I think they’re sort of on these different trajectories.

Tom Griffiths:
And so we’re going to end up with things that are really smart in ways that go beyond the kinds of things that humans can do, but also maybe surprise us in the other things that they’re not able to do, because those things don’t show up in the training data or they have the wrong formulation of the learning problem or whatever it is.

Brian Keating:
You speak in the book about what Chomsky called Plato’s problem, how human beings know so much from so little. But, you know, when I’m hat on Jan Lecun on this podcast, he said it’s the exact opposite. AIs have tremendous amounts of information, but it’s not even close to the amount right now filtering out something like 13 terabytes of, of raw information if you were to encode it, which I think is ridiculous. But, but even just foveal recognition and, you know, the camera or what have you, I mean, it’s a trip, you know, it’s certainly millions of megabytes, gigabytes, right? So isn’t it the opposite? I mean, I. I read, you know, my kids were little, that they need to hear a million words before they can speak. And if you just compress that, I mean, that’s an awful lot of data, isn’t it?

Tom Griffiths:
Plato’s problem, right? You said, how do we come to know so much from so little? And Chomsky talked about this as the poverty of the stimulus. And the idea being that there’s not enough information in what the kids hear to determine the structure of the language that they end up speaking. So I actually think that our AI systems are in some ways a good demonstration of this, which is that if you give them as much data as a kid gets, they’re still not as good as a kid at that. Learning language, we can have arguments about what it means to give them exactly the same data that a kid gets. And I have colleagues here who are measuring different aspects of what that looks like. But Chomsky’s argument in particular was focused on syntax. So how you know some very nuanced things about the structure of language based on the experiences that you have. And he thought there’s not enough information that’s contained in the stimulus that you see.

Tom Griffiths:
And to the extent that we can train models on at least the number of words that a kid would have seen, those models are still not doing as well as a kid from that amount of data. So I think that does support the idea that humans bring to these learning problems something that the AI models are not getting. Right? So humans, they have something that a machine learning researcher or cognitive scientist calls inductive bias. So something other than the data that influences the solutions that they’re reaching. Those inductive biases are what allows us to learn quickly, more quickly than our neural networks do from limited amounts of data. They’re also something that influences what solution we find. So if you have your neural network playing this alien radio prediction game, it’s going to find some solution to playing that game. But that solution might not be one that is very intuitive to us as humans.

Tom Griffiths:
Right. It’s sort of like figured out some weird stuff that are regularities that it can use in making those predictions, but it’s maybe not got a really good model of the underlying world or things like that. That whereas the kinds of solutions that a human will find are going to be influenced by those inductive biases. So part of what allows humans to generalize smoothly from one problem to another and to act in ways that are predictable to other humans and to sort of show intelligence that has those properties of generality that you were alluding to is the inductive bias that we bring to those problems. And I think that’s another sort of poverty of the stimulus argument. It’s like if you want to get sort of appropriately general learners, you might need to have some inductive bias to get that smoothness.

Brian Keating:
It seems to me that one reason that humans flourish is that we’re comfortable with ambiguity. For example, a question like, is an olive a fruit? As you point out, it’s pretty deep philosophically. Why is it that humans, even my kids, can understand it, but it sort of leads to either AI psychosis or hallucinations or sycophanty. I’ll ask you, which is the worst? But why is the question like, is the moon a light bulb? Why are those deeper than they look to be?

Tom Griffiths:
Those kinds of questions, I think in cognitive science have been useful in revealing exactly what our concepts are. So people coming out of that rules and symbols, tradition thought, oh, maybe a concept is just a definition, right? And I think that’s a good intuitive way of thinking, like what a concept is, right? You sort of have the intuition, you can look something up in a dictionary and it’s going to tell you, oh, what a cat is. Okay? A cat has these properties and that’s what makes it a cat. That way of thinking about the world sort of prevailed through the 50s into the 60s. And then was pretty firmly rebutted by a cognitive scientist called Eleanor Rush, who showed that there’s systematicity in the way that people have uncertainty about category membership. Right. So your listeners can think about this. Right.

Tom Griffiths:
So if I ask you, is a chair a piece of furniture? Probably yes. Is a phone a piece of furniture? Probably no. Here’s a lamp. A piece of furniture, maybe. Right. Is a rug a piece of furniture? Probably not. Right. So you can sort of immediately begin to explore this fuzzy boundary.

Tom Griffiths:
And that fuzzy boundary is a clue that there’s probably not a rule underlying your notion of what furniture is. In fact, it has what Roche called a family resemblance structure, where there are some things that you’re sure are part of the family, and then there are other things that sort of share some attributes with them, and then there’s sort of fuzziness that sort of goes out from there. And so when we come to AI systems, that kind of thing was a challenge for AI systems that were based on systems of rules. And that was, again, the dominant approach for building AI systems. Now through the 1970s, through the 1980s, people were making AI systems based on what were called production rules. There was a company that has continued to the present day building a huge database of rules with the hope that if you’ve got enough rules, then you figure out what the structure of the world is like. The neural network approach really, in some ways sprung up as an alternative to that that would be able to capture this fuzziness and all of the graded, continuous things that seem to be important properties of human concepts.

Brian Keating:
You talk about the semantic revolution. Can you talk about, first of all, what is a semantic network, and then explain the shift that made that possible and made the concepts becoming nodes in a weighted network rather than sort of a compendium of facts. Why was that such a breakthrough or seminal event?

Tom Griffiths:
If we want to capture that fuzziness of concepts, you need to have some way of having graded relationships between things. Right? And so your representation of furniture is now connected to chair very strongly, but connected to rug much more weakly. And so you can capture that by creating a semantic network, a network where each node in that network is a thing concept, and they have links between them that reflect their strength. And psychologists began to show that that wasn’t just a good way of storing information about the connections between things, but actually turned out to be a pretty good model of human memory, where if you said to somebody a sentence that contained one of those words, then it would be easier for them to remember or recognize another of those words. That was closely associated with it. Activation of words seemed to sort of spread through that network. And so that was something where psychologists began to realize that maybe there was a different way of conceptualizing what thought is. You can think about it now as you have all of these concepts, each of those is activated to some extent.

Tom Griffiths:
Now you have a high dimensional space, which is the space of all of the activations of those concepts. You have a point in that space and that’s your current mental state. And then the weights between things tell you how those mental states are sort of evolving over time. And now we have this alternative to that sort of logic, rules and symbols based theory of how it is that minds work.

Brian Keating:
Walk us through an example in this. Besides the furniture, it seems like there’s almost a geometric or, you know, Riemannian curvature approach that took over. Is that where the kind of insights of Hinton and, you know, gradient descent. Is that the kind of novelty that was applied by Hinton and his colleagues?

Tom Griffiths:
Yeah. So if you have this idea that, you know, we want to now have networks of things that are connected up to each other by different strengths, and maybe we can even take away the idea that those nodes in those networks have labels on them and maybe they’re just nodes that represent information somehow. Right. That’s what leads us to neural networks. Psychologists had been exploring neural networks for a long time, even all the way Back to the 1950s, the first kind of when people were developing the first AI systems. There were also people working on implementing neural networks on computers at that time, as I said, building neural networks by hand. So Frank Rosenblatt, who was a psychologist at Cornell, he was originally a social psychologist, and he had written a dissertation that required aggregating a whole lot of survey data. And so he sort of found out about the computer on campus and started messing around with that, and then built a circuit in order to aggregate the data from his surveys.

Tom Griffiths:
And suddenly you had a psychologist who understood computers and who understood circuits. And he was like, ah, I’ve got it, I’m going to build a brain. Right. He sort of had the pieces and the insight to think about how to do that. And so he built some of the first mechanical brains or electronic brains. I say mechanical because the way that he did it, he had a sort of artificial retina that you would show something to, and it would produce responses from little, little sensors that were in that retina that would tell whether it was seeing something light or dark. And then that information would get sent to another set of units, these nodes that would be accumulating information from the retina. And then he had another set of connections that went from those to an output.

Tom Griffiths:
So, for example, it could be deciding whether it saw a square or a circle. And so those connections to the output had a little resistor on them that could adjust to reflect the strength of that connection. And he came up with a learning algorithm that made it possible for this system to learn to differentiate simple shapes, circles from squares, or simple letters like e’s and F’s or something like that. And he proved a theorem that anything that the system could represent, it would be able to learn, which was great. He went off and sort of publicized the capacities of the system, which was called a perceptron. The problem was his former schoolmate, Marvin Minsky, had also built his own neural network. While he was a PhD student at Princeton. He went to Harvard, where he’d been an undergraduate, and built a neural network in the basement of the psychology department out of leftover airplane parts.

Tom Griffiths:
And he looked at this thing. He’d written his PhD dissertation on learning in neural networks, and he implemented this. And he looked at it and he was like, you know what? In order to learn anything interesting, this would just have to be so big and cost so much money that it’s never going to work. And so he gave up on learning in neural networks, got interested in symbolic approaches to learning. And so when Rosenblatt, again, his schoolmate, came out and said, oh, neural networks can learn all these things, Minsky was not impressed. And then with Seymour Papert, wrote a book that showed that perceptrons were sort of fundamentally limited in the kinds of things that they could represent. And the reason for that limitation was that single layer of weights in the network. And so the reason why that was a limitation was that that the perceptron with a single layer of weights could only represent linear boundaries in space.

Tom Griffiths:
Right? So if you can think about all of that, information is coming in, it’s going into a high dimensional space, and now it’s trying to find a linear sort of partition of that space in order to separate the things from each other. And so Rosenblatt’s learning algorithm could find those boundaries. But there were lots of problems where no such linear boundary existed. The solution to that problem was to make a neural network that had multiple layers. And various people kind of came up with strategies for making this work. The problem was that Rosenblatt’s learning algorithm didn’t work for multi layer networks. It only worked for one layer networks. He had a sort of a trick for doing this that he called back propagation, but it didn’t quite work.

Tom Griffiths:
Sort of worked most of the time. Another group of psychologists got interested in these neural networks thanks to semantic networks and spreading activation and so on. And so this was David Rumelhart, Jay McClelland at UCSD and then a postdoc that they hired, Jeff Hinton who was working on that project. And so Hinton suggested to Brumelhart that he could set up that problem as one of gradient descent. Right. So this is basically thinking about there being some measure of how well the neural network is doing and then adjusting the weights in the network in the direction that would decrease the error that the system was making. And then using that insight, Rummelhart was able to rederive something like Rosenblatt’s learning rule. And then he was able, on a plane flight when he was off to a grant reporting meeting, had enough free time to sit down and work out the whole thing in his notebook and derived the learning rule for multi layer networks satisfyingly.

Tom Griffiths:
One of the fundamental principles that was needed for that was something that came from Leibniz, from Leibniz’s calculus, the chain rule. So Leibniz got to have his day after all. A couple of centuries later, Hinton was actually the great, great grandson of George Boolean. So they met again together in that, in that location.

Brian Keating:
I was wondering, you know, kind of the. As a practicing, you know, researcher in this field, much more adjacent to it than I am, although I use it every day, all day in some cases, much to the chagrin of my wife. But the biggest problem that you see with LLMs is it psychosis, is it hallucination, is it sycophanty? I mean, I love sycophanty. You know, when I asked it, you know, what books is Brian Keating written, It says Losing the Nobel Prize into the Impossible and A Brief History of Time. And I just thought that was awesome. I’d love to get some of Steven’s book royalties. But what’s the biggest concern for you when it comes to AI? It’s not doomer. It’s going to take all our job.

Brian Keating:
We’ll talk about meaning at the very end, but what’s the biggest kind of thing?

Tom Griffiths:
Yeah, I think there’s a few things. So one is this jaggedness, right? This sort of lack of generalization where I think we as humans can end up overconfident in the kinds of things that the AI systems can do because we apply our intuitions that tell us if you had a friend who could solve International Math Olympiad problems at a gold medal level. You would trust them to do all sorts of other things on your behalf, but you should not trust an AI system to do that because they don’t generalize across problems in the way that people do. So I think just having the wrong intuitions about these systems is a major bottleneck to our being able to think about how to apply them effectively and how to make predictions about the kinds of things they’re going to be able to do. And that was part of my motivation in writing the book as well, is giving people some of the context for where these things come from and a sense of what the problems are that can come out of that and maybe what some of the kinds of solutions are historically that people have found. Of the other things that you mentioned, hallucinations, I don’t mind very much in the sense that they’re relatively easy to catch if you have some domain expertise. And I think they’re actually good in some contexts. So one of my best tricks for getting the models to generate good research ideas is to ask them to tell me about papers that I haven’t heard of but should know about.

Tom Griffiths:
And when they do that, they’ll often hallucinate and make up a paper. But the ideas in that paper are much more interesting than if I ask it to just tell me some interesting research ideas. Right. So having conditioned on generating a published paper actually makes it produce something which is higher quality. I think sycophancy is a major problem. We have a recent paper, this is with Rafael Batista, where we show if you take a rational agent who’s doing Bayesian updating on their beliefs and have them interact with a system which is sycophantic in the sense that it’s generating data based on the hypothesis that the agent expresses to the system, then that agent is going to become increasingly confident in their beliefs, but no closer to the truth. And we have some demonstrations that this actually happens with real deployed systems where we have people trying to solve a simple problem. And if they’re interacting with the default prompting for a GPT, they end up not making progress in that problem, even though they become more certain that they found the right answer.

Brian Keating:
And then the last two questions I have one is for someone looking to get at the future, where the future is going, where the puck is going. You have some hockey analogies in the book. I’ll leave it for the readers to encounter them. But skating to where the puck is going to be, it seems like one thing that’s really missing or is not fully developed is the embodiment issue where you have truly, you know, maybe close to AGI, you have very advanced intelligence coupled to robotics or embodiment. And maybe it’s what it’s missing or what these systems are missing is this marriage which will unlock via some network effect that we don’t understand, you know, truly human level thought. I always use the analogy of what Einstein, who worked not far from you, called his happiest thought, which was that, you know, an observer in free fall would experience no gravitational acceleration force. And that led him to the Einstein equivalent, Nolan’s principle. So I always ask, you know, how can a computer visualize, you know, the zero gravity feel of going, you know, the elevator cable getting cut? And then second of all, how can I have a happiest thought? Maybe we could incentivize it that way, but maybe you could embody it.

Brian Keating:
You know, if it gets the answer wrong, if it’s truly, you know, sycophantic, you blow out some of its capacitors or, I don’t know, you feed it some training data, only from the Fast and the Furious, you know, movie genre series. But tell me what, what would be kind of the next unlock, as you see it, to truly get us to the next level. That may be incomprehensible to Minsky and Chomsky and all the other folks that we mentioned in the book.

Tom Griffiths:
Yeah. So I think there are two parallel things here. Right. So one is inductive bias. So trying to figure out what it is that’s inside humans that allows us to find solutions faster and that are more robust and more generalizable. So that’s a good opportunity for cognitive science to contribute something to AI. Second thing is getting something which is closer to human experience into these neural networks where, like I said, they’re being trained to predict alien radio signals. If they have experiences that are closer to those of a human child, that might be something that helps to create those more generalizable, more robust kinds of representations of the world.

Tom Griffiths:
And then embodiment is obviously a part of that. It’s not clear to me that that on its own is necessarily going to solve problems, of allowing these models to be more creative to solve more kinds of problems. In a recent paper with Ella Liu in my lab, we show that prompting models to make cross domain metaphors. So to come up with a product design for a car based on ideas from an octopus does not increase their creativity. It doesn’t increase the originality of the ideas that they produce, but it does for people. So it seems like some of the tricks that we have for getting humans to have good ideas are not necessarily things that are effective for our large language models. And so that maybe is some fundamental difference in architecture, but it makes me a little less optimistic that just doing things like providing embodied experiences that you might be able to draw on to form these analogies might be enough to get them to be more creative.

Brian Keating:
And then lastly, you end on a hopeful note. Not really a doomer, as I tend to be, but kind of advice to early career scientists or maybe even lay people, because you just gave us some examples of what a career, early career cognitive scientist might do. But what should a layperson take away from this book?

Tom Griffiths:
Really what I wanted to do was to give people a sense of context and a vocabulary and a set of tools for thinking about these systems. Where I think for many people, AI seems like something that suddenly came out of nowhere two years ago. All of a sudden you could talk to a computer in the way that you talk to a human. And knowing the couple hundred years of stuff that led up to that is helpful in terms of understanding what it is those systems are doing, why they can do it, what the limitations are that we might expect that they would have, what things are going to be hard for them to do, what are the next steps that might help to fill in some of those gaps and having a way of having an informed conversation about those things. The laws of thought here, as I said, something that in principle, we should be teaching in school, not just to help us understand how our own minds work, but to help us understand the world that we’re moving into.

Brian Keating:
Professor Tom Griffiths, Princeton University this book has done something that very few books can even attempt and let alone pull off. Tell the history of cognitive science and also the future. It’s going and get inside of the mind of one of the greatest researchers of our generation and those that came before him.

Brian Keating:
Tom just told you that the godfather of AI is the great, great grandson of the man who invented its math, that sycophantic AI makes you more confident, but no closer to the truth, and that a child still can beat a GPT at the same data budget. Now, if all that reframes what you thought these machines were for, hit subscribe and turn on the notification bell. Drop a comment. What did Tom break for you? And if you want to go deeper, I talked about consciousness and machine minds with David Chalmers. The link is right here. I know you’re going to love it.

Brian Keating:
Go ahead, hit subscribe.

Astrophysicist: The Universe Is Coming for You | Hakeem Oluseyi

sabartigas — Sun, 26 Apr 2026 19:13:11 +0000

Astrophysicist: The Universe Is Coming for You | Hakeem Oluseyi

Transcript

Brian Keating:
We’re here with one of the most magnificent, munificent and mesmerizing minds of our generation, and he happens to be a friend of mine. And what can I say? I like to have my friends on, especially when they write books like this incredible new book that we’re going to be talking about today. Dr. Hakeem Olusche. How are you doing, my friend?

Hakeem Oluseyi:
I am doing excellent. Thank you again for your hospitality, for having me. Brian, you’re always good to me, so, man, I appreciate you.

Brian Keating:
I love this book. This book is unlike any other book I’ve ever read. Why does your book start off with a why question? Why do. Why do we exist, Hakeem?

Hakeem Oluseyi:
You know, we’ve learned so much about the universe and existence as scientists, and I think that we’re ready now. I think that we’ve come to a point where we have so much data that we can actually start to formulate questions or answers, rather, to these biggest why questions, like why do we exist? So, you know, sometimes that goes into shaky territory, right? You may personify the universe and think those sort of things, but I tell you, man, this book, phrasing it that way, is a provocation to the reader. Because I think that we scientists are at the point where we need to access the hive mind of imagination to make forward progress. Because, you know, this century hasn’t given us those. We’re finding that we’re good at everything, right? We have the answers, we go look and we see what we expect to see. And that, for us, is not good news, right? We want to see something that’s unexpected. And so, hey, man, I am inviting the world to join us scientists in approaching these big questions.

Brian Keating:
The thing you start off in the book is that you say that falling is not normal. You say on a cosmic scale, the astronauts, the. The apples, etcetera, they’re not really being questioned by why it falls at all. Talk us through the argument that falling the ground is accelerating up towards the apple, not the apple falling down. How is that not insane, right?

Hakeem Oluseyi:
It is insane because reality is insane, right? And I tell you, man, you know, I thought about it this way. You know, I asked my students, when I’m lecturing, if I hold out this object at arm’s length and release it and it just hovered in the air, how would you respond to that, right? You know, it would be shock. That’s what magicians do. But in most places in the universe, which is just outer space, if you do that, then it remains there, right? If you don’t Give it an impulse of any sort. And so what really should freak you out is the fact that when I release something, it moves all by itself. It does this thing called falling. Another physicist, Will Kinney, you know, I heard him say this first, is that gravity turns motion through time into motion through space, right? And so what he’s getting at there is this idea that we’re all moving through space time at the speed of light, and we’re on these straight line paths that we physicists call geodesics. But in the presence of a gravitating body, that space time diagram gets warped in such a way that, you know, if you think about it in X, Y plane, you.

Hakeem Oluseyi:
If you’re moving directly parallel to the Y axis, you have no motion along the X axis. But if I were to bend the X axis, even though you’re moving in the same direction, you now have motion along that X axis. Well, in space time, one axis of space and the other is time. So if you’re in an intergalactic space, you’re moving through time at the speed of light, right? But when you get near a gravitating body and that space time gets warped, some of your motion through space gets moved through time. And so when we think of falling, right, we think that objects are being pulled to the Earth, which is not the case. They’re just continuing to move the way they move. But then once you’re on the surface of the Earth, you now have an emergent property that we call weight, right? And so that weight is due to the Earth accelerating upwards against that space time. So even though when we think of acceleration, we think we think of motion, but you don’t need to move outward to accelerate upward.

Hakeem Oluseyi:
The Earth’s surface doesn’t have to move outward for it to accelerate upward. Acceleration has to do with changing something

Brian Keating:
with respect to your position, right? Traveling. So you just gave me a great idea to lose, you know, 50 pounds, just go to the moon. That’s all we have to do. We’re going to talk about that.

Hakeem Oluseyi:
That’s all you gotta do.

Brian Keating:
Okay, next, provide. We’re just gonna go provocative, just like mind blowing claims, okay? You made a claim in the book that almost no physicist I’ve ever be willing to make would have the energy and even the confidence to make that heat does in some cases flow from cold to hot spontaneously. And better than that, you say you discovered it washing dishes.

Hakeem Oluseyi:
So I was a kid with a single mom in the 1980s, and she would like, wash these dishes when I get home. I Want this floor waxed? This is true. And she was working at 11 to 7 shifts. I was waxing the floor at midnight. But one thing I would do before I realized that it’s not good for pots and pans. At some point in my 40s, you know, I would dunk a hot pot or skillet into a bath of water, and I would notice that the handle would get hotter. And, you know, I continued washing dishes in this way by hand up until around the age of 30. And I.

Hakeem Oluseyi:
And I kept asking myself, once I became a physicist, because, you know, I worked in heat conduction, and I know what the equation looks like. The temperature gradient is there. It only moves from hot to cold. So I’m thinking, am I a Mac imagining this, or is this real? Well, one day I went to the University of California, Merced, and I was talking to a professor who works with quantum dots, and he was showing that, you know, in certain cases, when you have a strong current going in one direction, you can get this reverse current against the voltage gradient, right? The voltage wants to move electrons from here to there. But if you do it fast enough, you can get a reflection back. And in order to derive a classical model, you. A classical analog to this quantum experiment, he used heat, and he showed exactly how this works. And I thought, oh, my God, My.

Hakeem Oluseyi:
My intuitive experiment turns out to be real. And once you understand why this is the case, it makes perfect sense. Because heat transmits as a wave within a material. And when a wave encounters a boundary between, you know, light going from one index of refraction to another, say, you know, there’s always going to be, and it is required by the laws of physics, a transmitted signal and a reflected signal. That’s why you can see out the window in the daytime, but you can’t see out of it at night. But the people outside can see in. It has to do with, you know, which is stronger, the reflected or transmitted signal. So when you have an incredibly strong heat flow over a boundary, some of that heat can be reflected backwards into your hand, right? And so that means that just like life does the opposite with energy, that inanimate matter does, right? It concentrates, creates structure.

Hakeem Oluseyi:
Well, the same thing happens with heat flow. And so that heat flow phenomenon, you know, lets us know why. You know, sometimes creationists will argue that because of the second law of thermodynamics, you can’t form a star. You can’t form organization from disorganization. But under certain circumstances, even though under most cases it’s not true, under certain Circumstances, these paradoxes are allowed.

Brian Keating:
Speaking of, like, forming structure in the atomic realm. So we should say there are nine realms go through it. The last one culminates with one of these things, the brain, the realm of imagination. But you say that electrons are the heroes of the universe, of the atomic realm, not the other way around. Why do we talk like that again? Because I was always taught protons 18, 36 times heavier than electron, same charge magnitude. How could you possibly think that these little wimps, that they have more sway over the atomic realm? Why doesn’t anyone teach it like that?

Hakeem Oluseyi:
I was at the University of Southern Mississippi earlier this week giving a. Giving a lecture, and I was hanging out with some chemists, and one of the chemists said exactly that, right? He had read my book. So maybe the chemists think that way, but we physicists certainly don’t think that way. But if you imagine the universe without electrons, you know, you would have all this positively electrically charged nuclei that would be trying to get as far away from each other as possible, and you would never form larger structures than, say, a lithium nucleus. But along comes the electron. And the electron, for me, has what I find to be a massive coincidence, right? You have one, a proton, a composite particle that, you know, what is it? Well, it depends on how much energy you probe it with, right? It can look like a sphere at low energies, it could look like three quarks at higher energy, or it could look like three quarks with a gazillion virtual particles at even higher energies at the lhc. And then on the other hand, you have this little, what we call a point particle, electron. And their electric fields just happen to be exactly equal and opposite, so that when they combine into a hydrogen atom, they are now electrically neutral.

Hakeem Oluseyi:
And. And they could be packed together into giant molecular clouds which just happen to birth stars, right? So without electrons, man, not only do we not have chemistry, we don’t even

Brian Keating:
have stars and planets with the electrons in place. You know, I think it’s kind of highlights to me, sort of like a dangerous deception that even educated people like me and others might have. You don’t get deceived as easily as I do. But I talked to a moon landing denier last week on Piers Morgan. I’d love to have you on there. We could tag up on this guy, but this guy, Bart Sibrel, and he’s making the claim. And I was astonished and a little bit depressed that thousands of people in the comments agree with this guy that we never went there. I even had demos I had, you know, moon rocks.

Brian Keating:
I have the plasma globe because he’s claiming that astronauts will die. And I was like, you think you’re smarter than Elon Musk and all the NASA astronauts he thinks he is. So what do you think is a normal deception that educated people have right now? What’s the most dangerous deception in society?

Hakeem Oluseyi:
I would say the deception of thinking that you know something when you don’t really know it, you believe it. Right? And the difference for me between believing and knowing. Believing means that you accept something as true without confirming it to be true. And knowing means that you have confirmed it to be true, but not only that, you associate an uncertainty with that knowledge, Right? So, for example, I believe that my mother is in Houston, Texas, right now. I haven’t confirmed that to be true. In all likelihood, she is right. There’s a big high probability with a small error bar. But I know that that error bar exists, and I know that that probability is not 100%.

Hakeem Oluseyi:
And so I’ve said that to people because for me, in graduate school, that was a big revelation when I learned. Because let me tell you, it came to me by my PhD advisor who I talk about in my memoir. He would tell me to do something, right? And I might delegate it to someone else, and he’ll say, hey, Hakeem, did such and such happened? And I’m like, oh, yeah, I told this guy. And, you know, and he’s like, do you know that happened? And I go, yeah, I told him. And I saw him walk out of the room and had to do it. He goes, but, yeah, but do you know that happened? And I’m like, oh, I’ll be right back, right? I hadn’t confirmed it. So a lot of people, you know, even though that sounds very obvious and intuitive, I find that for the vast majority of humans, we don’t know the difference between what it means to know and not know. And like, you and I went to school for many years to become an expert on a topic.

Hakeem Oluseyi:
And as they say, you know, becoming an expert means knowing more and more about less and less until you learn, until you know everything about nothing. But the point is, is that when you realize how much effort it took to become an expert on a topic, and you realize that you haven’t put in that effort in other places in life, you’re left thinking, man, I know nothing. Becoming an expert just makes you realize, I am so ignorant, right? But most people haven’t gone through that process of becoming an expert. And so most people, you know, and it’s not a part of our education system.

Brian Keating:
I like to say I know more about the Dunning Kruger effect than anyone who’s ever lived.

Hakeem Oluseyi:
I know what you’re talking about. Yeah.

Brian Keating:
You’re one of the most simultaneously infectiously enthusiastic optimistic people I know. But you also have this sober pessimism. And I think nowhere is that better really defined than when you do a calculation about the life realm, the realm of the living in this book where you calculate and you do this walk us through this Fermi calculation, which will lead to the Fermi paradox. We’ll get to that. That there’s roughly 100,000 star systems in the Milky Way alone that could host multicellular life. And then we’re like, oh yeah. And then you say, but we’ll also probably never find each other. Why not?

Hakeem Oluseyi:
Absolutely. Yeah. Because, well, there are hundreds of billions of stars in our galaxy. So if there are 100,000 stellar systems with planets that can host multicellular life, that means it’s one in a million. So when a person who doesn’t do astronomy looks up at the night sky, they may think they see a million stars. But you know, on the planet total, you can only see 6,000, right? So stars are huge, massive, burning brightly. But our galaxy is so big that you can only see the 6,000 nearest ones. So if there’s one out of a million, they’re going to be buried so deeply somewhere, unless there’s a massive coincidence.

Hakeem Oluseyi:
Even the sci fi of Star Trek reflects this because, you know, they never leave their own quadrant of the galaxy. For the most part they realize it’s that darn big. But let’s get to the calculation. My calculation is similar to Frank Drake’s equation, but instead of looking for detectable civilizations, I think the better question is how many worlds can have multicellular life. So you start with the number of stars and then you multiply that by the fraction of stars that are just right. Stars, they have the right chemical composition, they’re in the right part of the galaxy, the galactic habitable zone. They’re long lived enough for multicellular life to evolve, which on Earth took around almost 4 billion years. And they’re not too long lived because that means they’re small.

Hakeem Oluseyi:
The planet has to be near them. It will be tidally locked. And those stars have these massive ejections and flares that would destroy life on. So it needs to be in a sweet spot. And so when scientists who aren’t me calculated the number of stars that would be, that would be suitable, it turned out to be 1.2% of the stars in our galaxy, then you need just. Right, Planets, right? So those are planets. If you want multicellular life, it needs to be in a habitable zone. You don’t need to be in a habitable zone for life.

Hakeem Oluseyi:
You need to be in a habitable zone for multicellular life. Right? And so what do you need? You need to be protected from the bad stuff, which is typically radiation, but yet you need to have the geological conditions that allow you to form life. You need liquids. So if you satisfy the liquid criteria, you know, typically other things are in your favor, right, Abundant liquids. So then you need to have incredible luck. And what do I mean by that? The Earth is very unique when it comes to planets in the sense that we have this three layer filter that does exactly what I just said, it blocks the bad stuff. What does that filter? For early life, it was four layers, right? It was the ocean, the atmosphere. No, they only had three as well.

Hakeem Oluseyi:
The ocean. Until late times, the ocean, the atmosphere, the ozone layer, and our magnetosphere. So when we look at planets around our solar system, and among the thousands of exoplanets we find, we see that atmospheres typically come in one of two configurations. Super thick, like Venus, Titan, Jupiter, Saturn, Neptune, Uranus, or completely absent, or almost completely absent, right. Moon, Mercury, Mars. And so here we have this almost absent atmosphere that if we did not have our strong magnetosphere, it would have been eroded away by the sun’s radiation. Right? Just like what happened with Mars. But because we have this strong magnetosphere, accidentally we have a special condition.

Hakeem Oluseyi:
And so most people have been led to believe that that special condition is having abundant surface liquids. That’s not what’s so special. There are 10 ocean worlds in our solar system, but most of those oceans are under miles of atmosphere rock or ice. Our water is bathed in sunlight. And so that early life eventually learned how to. Do you know, that early life did photosynthesis, but it eventually learned how to do photosynthesis that produced oxygen. And once that oxygen was able to build up in the atmosphere, and finally in a deep ocean, you get this burst of life, of multicellular life, the Ediacaran, followed by the Cambrian explosion. So that idea of being bathed in light with liquids on the surface is what sets Earth apart.

Hakeem Oluseyi:
And why do we have that condition with that strong magnetosphere? Because of a big collision that happened early in Earth’s evolution, right? That’s churned our Earth’s interior. And now a significant part of Earth’s interior is molten metal. Okay, we see that with Venus and Mars or Mercury, we’re unique in that way. So, man, you know, it’s almost like the universe makes life inevitable, but it doesn’t make multicellular life inevitable. Right. You need some luck. And even if you get multicellular life, yeah, it’s going to have a sensory system. It’s going to respond.

Hakeem Oluseyi:
But does that mean you necessarily get a technologically advanced civilization? Highly unlikely. Right. Of all the billions of species, there’s only one that has done that.

Brian Keating:
That’s right. Reach the pinnacle of evolution, which is what you call two guys and a microphone.

Hakeem Oluseyi:
A podcast.

Brian Keating:
Now, speaking of microphones, what do lumberjack rappers do in their performances?

Hakeem Oluseyi:
Oh, my God, chop it up.

Brian Keating:
No, they sing logarithms. Logarithms. Now, speaking of logarithms, I didn’t say it was a good dad joke. I mean. Okay, so let’s start with the scale question, because you really define something that most people are completely oblivious about, and it borders into the G question, the God question. I will get to that in a minute. But you say that humans are slap dab. I quote in the logarithmic middle of the observable universe.

Brian Keating:
See how I segued from the log? Okay, explain what that means and why does it matter? What does it mean to be in the logarithmic mean, and what is the potential impact on humans, and why does that matter to us?

Hakeem Oluseyi:
The biggest known physical distance in the universe is the size of the observable universe. And we Express that as 10 to the power 26 right meters across or in radius. Same thing. It’s a factor of two. But then when we think about the physically smallest entities in the universe, we think of the neutrino that has a size limit of around 10 to the minus 26 meters. And here we are at 10 to the 0 meters, slap dab in the middle. And this is the place where at this scale, life can exist and intelligence can exist. It doesn’t exist on the scale of galaxies and stars.

Hakeem Oluseyi:
There are no sentient stars that we know of. But, you know, unless you read comics, right? Marvel Comics has a sentient planet and all that jazz, you know, the fact that in the logarithmic middle, center of the universe is where we exist, and that’s where our intuition is valid. That’s the world that we know. That’s the world that Aristotle and these guys were thinking about and saying, hey, I think I understand it. Then we get our microscopes and telescopes and realize, like, oh, there’s a lot more going on, and our experience cannot Be extrapolated. You got to understand it on its own merits. And what’s remarkable to me, you know, we’re dudes in suits with microphones, but man, I still think of us as an animal. I still think of us as australopithecines, right? You know, Stone Age creatures that have been able to come this far and knowledge and ability is incredible, but it’s because we get in where we fit in.

Brian Keating:
Now, you have a modest goal with this book, which is to organize all of reality into nine realms. Okay, I’m joking, but this isn’t something like textbook taxonomy. You call it a sw. Swag. A scientific wild beep guess. Okay, so now why frame it that way? And why did you organize the the title and subtitle of the book? You could take us through the book title, subtitle, judge the book by its cover. As we say, hey, book lovers, we’re

Hakeem Oluseyi:
judging books by the covers.

Brian Keating:
We know we’re not supposed to do

Hakeem Oluseyi:
it better into the impossible. There’s nothing to it. Let’s take a look and judge some books.

Brian Keating:
Why did you organize it in terms of these realms? And what is the importance of the scientific in front of the wag?

Hakeem Oluseyi:
So, you know, there is a difference between a wild ass guess and a scientific hypothesis. All right? And you know, what I’m saying is not at the level of a scientific hypothesis. I’m not putting forth anything that’s untrue, right. Or inconsistent with what we’re doing as scientists. But I am informing a wild ass guess here using my science. So it’s somewhere between hypothesis and guess. And what I’m trying to, trying to do is create a cognitive map of reality to help the reader understand. If they’re going to help us with understanding the true nature of reality, then they need to have a map in their mind.

Hakeem Oluseyi:
And you know, I feel like, you know, when I became a PhD student, I felt like my job was to, you know, you have to become current, right? So what does that mean? That means you have to read and understand all of the knowledge in your field up to what happened yesterday and even understand what people are working on that’s going to come out tomorrow. Right? But then once you have that understanding now you need to make a new contribution to knowledge and that’s when you get your PhD. So what I’ve done is I’ve taken the world as we have framed it, the universe and existence as we have framed it as physicists. And I said, hey, I understand how we see things, but you know what? Now let Me make my new contribution. Here’s how I see things. And I think that having this map of reality broken into these realms allows a person to understand the universe in its wholeness. And again, I’m talking about the physical universe because with a title like why Do We Exist? It can get religious and faith, you know, it interfaces. And I’m not, you know, I have all respect for that, right, that type of thinking.

Hakeem Oluseyi:
But this is based on, you know, the scientific process. And these nine realms to me are sort of like the minimalist set of realms that I can break the universe into. And some of them are obvious, right? So the quantum realm, the cosmological realm, the dark realm. Those ones are obvious. But, you know, there are some that are more speculative, like the multiverse realm, Right. Another one that you know is not speculative is known, but it’s never put this way is the realms beyond horizons, right? That is a, you know, within black holes, beyond our cosmic event horizon. These are the realms that we can never probe directly and existed and report out. You know, you can.

Brian Keating:
That doesn’t stop our colleagues, you know, like Michio Kaku and our friends like Brian Greene from speculating. You know, I come from an experimentalist perspective in the cosmological realm, right? And for me, I get a little frustrated, to be honest with you, with the rampant speculation. Okay, string theory is one thing, but when you start talking about things like Stephen Hawking did, where at the end of A Brief History of Time, he says, once we get the, you know, theory of Everything, then we’ll know the quote, mind of God. And he postulated that it was due to this, you know, Hardle Hawking instability that creates, carves off time and creates it from the no boundary, you know, from a timeless universe that existed before. But those things capture the imagination. If I start describing superconducting tunnel junction detectors, calibration, polarimetry, and you start talking about the sun and all the different realms that you and I are experiencing, people don’t seem to be as excited. In fact, one of my agents, you know, kind of friends that are eight bookings, like, well, it’s great to talk about experiments, but they want to hear about theories. I’m like, these theories will never be discovered.

Brian Keating:
They’re totally, you know, they’re total vaporware. And he said, they don’t care. The public doesn’t care. And that depressed me. So where do you draw the boundary? You have the imagination realm at the end. That seems to be the one that sells the most, at least for our theoretical colleagues. What do you make of that? That hunger for. Even if it’s nonsense to talk about the multiverse, the wormholes, these horizons, we can’t understand.

Brian Keating:
Why is the public care so much about them?

Hakeem Oluseyi:
I think, you know, people do have curiosity, you know, and people do have. In a sort of. You know, I had friends that talked about the Illuminati and these sorts of things.

Brian Keating:
We’re not supposed to talk about the Illuminati, remember?

Hakeem Oluseyi:
That’s right. That’s right. I was at a guy’s house who has done very successful for himself talking about paranormal phenomena. And he went on his Amazon creator background and showed me his sales numbers from his many books the dude was making over. I’m not even going to say it, but it was a lot more money than I ever made from a book. You know, he gave me my very first ride in and my only ride in a. What is that car? Is that. Is it a Rolls Royce? Maybe it was a Rolls Royce.

Hakeem Oluseyi:
I think it was a Rolls Royce. Yeah, it was a Rolls Royce. My only ride I’ve ever taken in a Rolls Royce. Right before he went to his mansion, that’s where I started. And that’s the thing about me is that, you know, I’m really thinking about the people and reaching them. And I realize that those kind of thoughts can be a bridge into real science. And I’ve tried to avoid that, you know, in this book, I’ve tried to be like, where I’m speculating in everything, right? Where I’m speculating, I’m going to let you know, this is speculation. And what I didn’t like about when the string theory books were popular is that they were written in such a way that when they were speculating, if you were a scientist, you could recognize it as that, but if you were a lay reader, there was no way you could recognize it.

Hakeem Oluseyi:
So you thought the universe really does have 11 dimensions and thoughts like that. Right? So I’m with you, man. It really. I don’t like it. I don’t like people that lead people astray in that way. I can’t speak to their motivation, but I can say that it tends to be profitable. And I’m not willing to go there. You know, there’s a lot of places that people try to pull me into that I’m just not willing to go.

Hakeem Oluseyi:
Like, people try to pull me into dissing religious folks, right? Because, you know, and I’m like, no, I’m not doing that. And people try to get me to say, hey, look at that light in the sky, it’s an alien. And I’m like, bruh, there is nothing that a light in the sky can do to make me conclude that is an alien or it is anything other than a light doing something weird in the sky. That’s what the data is telling me.

Brian Keating:
So our second conversation two years ago, three years ago, got into the politics of science. The naming of the James Webb Space Telescope. You’re one of the most courageous thinkers that I know. You’re unafraid to go up against powerful forces that tried to squelch you and really besmirch the name of James Webb himself. And we’re not going to recomm capitulate that, because in this book you talk about the findings that this James Webb Space telescope has made, including these early mature spiral galaxies that you know, according to some people, shouldn’t exist if the big bang occurred 14 billion years ago. They shouldn’t be appearing, you know, 100 million, 500 million or even a billion years after. So you suggest a provocative alternative, that gravity models need to be modified and that they may have a better capability than dark matter alone. It doesn’t mean that dark matter doesn’t exist.

Brian Keating:
Talk about that. What’s your justification? I mean, it is kind of a minority view, but I’m accustomed to that with you. You go out on limbs, you are

Hakeem Oluseyi:
courageous, no pun intended. The minority view.

Brian Keating:
You never hear these words like hilarious dad joke and courageous academic, but today you break them up.

Hakeem Oluseyi:
Thank you. Thank you for recognizing that, Brian. Courageous academic. That is a rare one. So it’s not my thought, right? This is, this is me being the messenger because this is not the mainstream of thinking. But what the people with these modified gravity models have shown is that, yeah, their models do reproduce early, you know, mature galaxies much better than our standard approaches. It’s one of these cases where we treat it as either or. But it may be that, oh, in some circumstances, maybe something’s going on here, and in other circumstances, this is what the dominant process is.

Hakeem Oluseyi:
So all I can do in this case is say, hey, you know, this is a very model dependent field. We’re not actually creating galaxies. We’re not actually creating universes in the lab and allowing them to evolve. We’re creating them in computers using models. And those models are constrained by the measurements of cosmological parameters, which are themselves kind of weird sometimes when you have things like the Hubble tension. So we know that there are elements that we don’t know and we don’t understand. And what’s clear to me, and I say this in the book, is that like, you know, we really think that the best fit to the data is dark matter or dark matter and dark energy. But it is not at the level of where we have conclusive knowledge of exactly the nature of these phenomena.

Hakeem Oluseyi:
And so it’s kind of like, you know, when somebody in my family loses something, you know, my wife or the kids, you know, I’ll say, did you look in the refrigerator? You know, they’re like, it can’t be in the refrigerator. I’m like, listen, if you can’t find it, it can literally be anywhere, right? We can constrain it to the house, in the car maybe, but you don’t know where it is, so look everywhere. And that’s how I approach things. You know, I approach things with. Until it has been conclusively demonstrated, we must remain open minded and we have to give credit where credit is due. So if these models are able to reproduce what we see to some degree, you know, let’s, you know, because that’s the thing about these modified gravity models. Every time you think they’re dead, they get, they get modified and do a little better to reproduce nature. I’ve given the reader all the information, not just the preferred information.

Brian Keating:
Yeah, I actually have, you know, every now and then we have these horrific inquisition like teaching evaluations where some senior faculty comes in, you know, I’m getting the gray hair and stuff, so I’m pretty senior now, but, but they’ll come in, I remember. And I was teaching about dark matter and I also mentioned mond, modified Newtonian dynamics which you talk about in the book. And I had interviewed, you know, Mordecai Milgram, who was the conceptual, you know, architect of it originally. And the senior professor was saying, well, like why do you teach that? We know it’s wrong. I’m like, do you know what’s wrong? I mean, first of all, you’re a theoretical particle physicist. Second of all, you have no, you know, really, it’s just kind of an arrogant thing to say. We know the answer. I mean, we’ve never detected dark matter and we may never detect dark matter, except for the neutrino, which you talk about in the book.

Brian Keating:
So you’d say that the nine realms interlock like gears. Okay, so here’s my gears. You got some nice toys, kind of mesmerizing out. It’s good to have kids, you know, that know how to do 3D printing. You know, you get brains, you get, you get alien artifacts. But you say two of these Realms. Two of these gears, if you will refuse to play nice. They grind catastrophically.

Brian Keating:
They won’t pass through each other. Quantum field theory predicts a vacuum energy density. It’s 120 orders of magnitude larger than what we observe. So how do the nine realms, how do they handle the clashing between the quantum realm and the cosmological realm?

Hakeem Oluseyi:
We’re in the. In the neighborhood of the dark realm now. And dark, you know, it started off with not emitting light, but now I take it as a statement about our knowledge, right? We’re in the dark. We definitely see real physical phenomena, but the explanations for those physical phenomena are, you know, we come up with our best models, we go looking and we’re like, ah, that’s not it. You know, and so how do we really converge on what the truth of the dark realm is and how you know, it? You know, I feel like right now there needs to be some revolution in thought that I don’t know what that is. My very first physics experiment was working with Bernard Satellite in the basement of Laconte hall in Berkeley on what would become the cdms, you know, code Dark Matter Search Experiment. You know, I thought, oh, yeah, we’re gonna know what dark matter is soon. We’re direct detecting it.

Hakeem Oluseyi:
And then, you know, after I left Silicon Valley, I joined a supernova cosmology project, right, which had just, you know, participated in discovering dark energy five years earlier. And I’m like, oh, yeah, we’re gonna, you know, build a satellite and, you know, put these new detectors on these telescopes, and we’re gonna know what dark energy is in five years or so, and we don’t, right? We have a lot of confidence in our quantum mechanics because of its experimental successes and everything else. You know, like, GR is okay, maybe there’s something there. But GR has been so successful in so many different scenarios. You know, I’m not one to say that it’s incomplete, but there is this battle going on, this pushing, this pull that we have yet to resolve. So I’m fine with open questions. I’m fine with we don’t know, let’s keep searching. But the thing I’m not fine with is you can’t think that thought.

Hakeem Oluseyi:
You can’t think that thought. You can’t allow that person to participate. You know how it is when you’re a physicist, all kind of people write you with their crazy ideas. And sometimes I look at them and I’m like, you know, most of the time, right, I’m like, ah, this is nothing. But sometimes I’M like, oh, wow, that’s interesting. You know, so I think the answers could come from anywhere. Even, maybe even a seven year old, like, look who’s breaking all the records in Rubik’s Cube solving. Right? They’re babies.

Brian Keating:
Yeah, that’s right. I can solve a Rubik’s Cube if you solve the first five signs. I got it. I got it, man.

Hakeem Oluseyi:
Okay. Okay.

Brian Keating:
Now, you and I, you know, operate as physicists, as scientists, and we know that there are tensions, we know that there are battles. Not unlike, remember, the 1980s, the 90s, the rap battles, you know, east coast, west coast. I was not on the west coast at that time, so I was still in the, firmly in the Biggie Smalls camp. But no hate towards the other side. But you and I have this, you know, kind of, I’m working the CMB instrumentation field. You were involved in the supernova, you know, cosmology project. And you know, we studied different realms of the cosmos, later realm, early realm, that most people would say, oh, it’s, you study something that’s up 2 billion years old. I say something that’s 13 billion years old.

Brian Keating:
Oh, that’s really close. No, they’re totally different. So how does a, how does a layperson interpret when scientists each seem like they’re brilliant when they disagree so violently as we do in the scientific realm, of course. So in the dark energy, you know, kind of are in the Hubble constant wars that we’re experiencing now, The Hubble tension you and Adam Reese talked about, Nobel Prize winner, friend of the podcast. How do you interpret that? Use two brilliant people, two brilliant types of technologies. How does a layperson make a decision that, like, hey, the universe might be a billion years younger than we thought?

Hakeem Oluseyi:
I would say to the layperson as we watch these, number one, it doesn’t mean that we don’t know anything because that’s where a lot of people think they don’t know details. That means they know nothing. That is not the case. The other thing is, is that the, the culture of science is weird to regular people. And sometimes regular people get caught up in our little battles, like, oh, do black holes have hair? You know, is quantum information lost? And I’m like, you know, sometimes we make too big of a deal of these little nerdy things. But Adam Reese was like, no, this Hubble tension is a big deal. I always go back to observation and data, and I think experiments like the Nancy Grace Roman telescope and the Vera Rubin telescope are going to fill in those gaps between the nearby universe and the Far universe. Right.

Hakeem Oluseyi:
Because the supernovae don’t go that far. The CMB is very, very, very far. Right. There’s a big space in between. And the other thing we haven’t done, you know, you model the universe as a uniform gas, right? And so we assume that the expansion rate is the same in all directions. One experiment that I wanted to do when I was a young scientist just becoming a professor is measure redshift drift. I wanted to actually see the redshift of galaxies changing with time. And I was trying to think of clever ways like, oh, what if I use time dilation? Like, move a spacecraft incredibly fast? Could I get something from doing that? The measurements seem to have been really solid.

Hakeem Oluseyi:
All you smart people have looked at them and looked at the possible systematic uncertainties that may be plaguing these real results. And it’s all in that uncertainty measurement. It’s all in that error bar. And those error bars are not overlapping. And knowing the culture of science, people hate each other. Right? People. There’s no conspiracy to come to the same answer. If there’s any conspiracy, it’s the conspiracy to get the other guy.

Hakeem Oluseyi:
I’m accepting where we are right now and waiting for the new data.

Brian Keating:
You say in the book, towards the End, that the universe will succeed in its ultimate mission. Oh, that’s really great. And that mission, Hakeem, you say, is to destroy all matter. So what I want to ask you is how much longer do we have? I mean, it’s tax season. Should I pay my taxes?

Hakeem Oluseyi:
I am not a tax advice person, so anything I say, don’t sue me. We got a long time, right? But one thing I see from this, from this tale of the universe is that it appears to me that the universe is very young. And why do I say that? Because only a young universe is observable, right? That cosmic event horizon is out there, and the expansion rate of the universe goes faster and faster. So it’s kind of like when you have children, you’re going to interact with them longer as them being adults than you are going to interact with them as them being children, right? So your mind frame, as a parent needs to be able to make that transition. Well, the universe is going to exist much longer as a lonely place than it is as a place packed tight with galaxies where galaxies are only, like, 10 times their own size apart from each other. Right? Where stars are tens of millions of times their own size apart from each other. You know, soon we’re just going to be the local group only. So we’re Right at the beginnings of the universe.

Brian Keating:
What does that mean? How long is that going to last for?

Hakeem Oluseyi:
Yeah, so I look at the universe as a series of events where the universe is attempting to go neutral under these field forces, the strong force, the electromagnetic force. And the Stalliferous era is a universe going neutral under gravity. Right. So what is happening is matter is collecting in these vast filamentary structures that we call the cosmic web and is expanding in the areas between them. And as it does so, as the matter collects, higher levels of complexity are evolving. So gas becomes stars, the residue becomes planets. Those stars ultimately die. And every galaxy is destined to be, you know, a black hole, giant supermassive black hole surrounded by a halo of smaller black holes.

Hakeem Oluseyi:
Right. That may eventually coalesce inside the universe is going to wipe out the ability for life to exist at all, because it’s going to get rid of all the stars and planets and, you know, and there’s going to be black holes and not much else. Right. As far as matter concentrations go. But the things that we have to deal here with on Earth are our immediate concerns. Right. Eating today is a bigger concern than the universe ending. And what I find fascinating about humans is that we’re always talking about the end of the world.

Hakeem Oluseyi:
Right. And what does that mean? That means all humans die at the same time. And why are you so concerned with that when we know it’s inevitable that each of us dies individually? So finding value and fulfillment in your own life and meaning is where we should put our efforts. And so for me, you know, I’m a family man, and, you know, it was drilled into me as a child, be useful, you know, in my rural upbringing. And, you know, I like to help other people. And, you know, I have my own selfish things. I used to love to play basketball until the cost benefit analysis, you know, as I age, became not very great. But, you know, just finding fulfillment in life and hoping to contribute, man.

Hakeem Oluseyi:
So you don’t have to worry about these big things. But there are more nearby cataclysms, like, you know, impacts that we can do something about potentially, right. Like large cometary or asteroid impacts.

Brian Keating:
We’re recording this on April 10, which is the afternoon that the astronauts on Artemis II are scheduled to splash down right off the coast of UC San Diego in Amir Scripps. And I want to talk to you about a couple things. One is, you know, I’ve seen you all over ABC News, and I was just like, you did such a good job. You’re just so, like, calm and, you know, When I go on a podcast sometimes I like nervous. And you’re talking to millions of people live on the biggest event in the space faring histories that most of us have been around for. You talked a little bit about Victor Glover, who was the first black man to go ever into deep space around the moon. You’re a black astrophysicist. You grew up in the streets.

Brian Keating:
Your first book’s about being a drug dealer, right? I mean, milestone mean to you. You’ve done so much in your life, and if anyone ever, you know, doubts your credentials, you got a stack of resume that’s, that’s, that’s, you know, can reach the moon. So what does it mean, first of all, to see a black man making history like that?

Hakeem Oluseyi:
It matters. A lot of people are averse to discussions about identity and race, but I tell you, it absolutely does matter, man. When I was a kid, you know, I remember that anytime there was a black person that made one of these revolutionary breakthroughs and it became knowledge to us, you know, we were so proud of them. It was like a member of your own family had done it. And what’s hard to understand about the psychology is when you feel that the world is messaging to you all the time, the opposite of that, that you don’t have value, that you’re not capable of things and that sort of thing. So, for example, how did I get accepted into Stanford University was in part due to William Shockley, the Nobel Prize winner. You could go on YouTube today and find him saying things like, there’s no point in trying to educate black folks. They’re just not capable of it, Right? This is not something that is make believe.

Hakeem Oluseyi:
And the thing is, is that if you’re not subject to it and you’re not doing it, it’s invisible to you because, you know, it’s like, you know, if you’re Jewish, if you’re a woman, almost no matter what you are, there is some specific hatred that you receive that other people don’t receive. And if you see someone like yourself do something good, you know, it could be like, oh, my fellow Napoleon, right? You’re going to feel pride in that. And the fact that we’ve come so far, you know, I think one thing about us as Americans, we don’t give ourselves enough credit, man. I think that, you know, if you want to paint America in black and white, black people and white people have come so far, right? And we need to give credit to that, man. Like, literally when I left Mississippi, you know, I thought, oh, every white person is Racist. Not true, not true. Every black president Barack Obama was running, you know, Chris Rock had this joke where he was like, barack, you got the most votes. Too bad you lost, right? Like, he could never happen, right? I thought that, man.

Hakeem Oluseyi:
But I tell you, you know, we are better. We are better than we give ourselves credit for. And I feel that people are good, fundamentally. I’ve been to 44 countries, I know a world of people. And I curate the humans in which I interact with. And I often say I don’t choose people I interact with based on how they look. I choose it based on how they feel. A lot of my mentors in the 21st century have been white women, right? There’s been people that have been.

Hakeem Oluseyi:
So I wouldn’t be here, right? You know the dudes that, that mentored me early in my career, Richard McGinnis, David Thiel, Gerald Bruno. These were three white dudes who came from elite universities, Caltech, Harvard, Cornell, and decided in the 60s that they wanted to help out with the Civil Rights movement, go down to Mississippi, right? They had strong Christian faith. That’s what led them there. And they end up spending their entire careers at Tougaloo College, right? And they created me and my Tougaloo College colleagues, right? And, man, that is what we’re made of as human beings. If a cat walks into my lab, I don’t care who and what they are. And so what does that mean? My lab group used to be like the group of outcasts, right? The gay students, the women black students, the people who felt like, you know, hakeem is non judgmental. I feel comfortable with him, right? Those are the people. But I see the value in all people.

Hakeem Oluseyi:
And, you know, I see the beauty and the ugly, as I like to say.

Brian Keating:
That’s what it means to be a mature, you know, thinking individual. And I think it’s a perfect place to end up with a final question that you end the book with the realm of the imagination. I love that because I was the former and one of the founders of the Arthur C. Clark center for Human Imagination here at ucsd. And we met at a Clark Awards for the first time. All of a sudden I said, is that Hakeem Olusea? I never met you. So we’re giving an award to Michio Kaku about five years ago. So you write that imagination is, quote, an evolutionary imperative.

Brian Keating:
So, so my question is, if that’s true, you know, why are there so many Kardashians? No, no, if that’s true, you know, what, what happens to a species that stops imagining. And how can we avoid that with our kids, with our society, with humanity as a whole?

Hakeem Oluseyi:
Man. I think that because we do start off as children, you know, children, they’re not gonna listen to you. They’re gonna do their program. Right? It’s kind of like the mother doesn’t make the baby. The baby is a parasite that makes itself right? And our children, you know, the evolutionary pressures that brought us here gave us this imagination, that gave us this brain, this mammalian brain that was able to self organize in different ways to become smarter and smarter and imagine more and more. And now it’s given birth to AI, right, which basically develop its own imagination. Currently. Its imagination sucks, but, you know, there’s no actual limit to what it can do theoretically, right? So I don’t think that that is a question we ever have to wonder, but I do think that how you nurture those imaginations matters, right? How? You know, there’s something that has to do with the, with the American system that we keep dominating in these imaginative technologies.

Hakeem Oluseyi:
And I don’t know what that is, right? What was it about the Germans in the early 20th century that led them to dominate physics? What was it about the British in the 19th century that had them dominant? I don’t know. But I do know that there are cultural elements and there are structural elements involved. And so structurally, we have the people, the government, they take their taxes and they invest in imagination at the universities. And then we have systems to commercialize what we come up with. And in some ways, we’ve pulled back. Recently, a lot of the government investment is pulled back. We have this massive, almost 40 trillion dollar deficit or having a situation like that, where do you want to sink your money in, into investments that are going to grow? Right? That’s where you want. And the greatest investment, the greatest sustainable resource we have is the human imagination.

Brian Keating:
That’s beautiful, Akeem. This is always fun. I always love talking to you and I love it even more. We get together for a pint or whatever when we get together next time. This book is a great contribution because it really explores and explains what it means to be a brilliant but also humble scientist, which I think a scientist needs to be cocky, needs to have some swagger, some swag, right? But you also need to be humble that the universe can not humiliate you, but humble you at any time. And I think this book in the nine realms of the. Of the universe that make us possible is really just an incredible contribution. Congratulations.

Brian Keating:
And I do hope that people will start to really see themselves in these positions that you have really paved the way for, for both scientific literacy, but also, I always say communicating to the public is probably the top job of a scientist that we never do because, oh, it’s like, that’s for, like, slick, you know, people to do. And Neil DeGrasse Tyson and Brian Greene, all these, they can do that. But a real scientist doesn’t it? No, that’s not true. Yeah, it’s something that’s hard. You have to work on it. And it’s a moral obligation to give back to the taxpayers who fund us. And since you told us that the universe is not going to end before April 15, I really do appreciate that little bit of non tax advice. Hakeem, thank you so much, my friend.

Brian Keating:
And congratulations on this awesome book.

Hakeem Oluseyi:
Thank you, Brian. I appreciate you, sir.

Quantum Computers Aren’t Useless. You Just Don’t Know How to Use Them.

sabartigas — Mon, 20 Apr 2026 07:55:38 +0000

Quantum Computers Aren't Useless. You Just Don't Know How to Use Them.

Transcript

Brian Keating:
My friend Sabine Hassenfelder just made a video that got nearly half a million views in just a couple of days. Her conclusion? Quantum computers are basically only good for doing one thing, breaking codes. Now, Sabine’s brilliant, and she’s right that the code breaking progress is terrifying. Google just moved up Q Day, the date in which quantum supremacy takes place, to about 2029, less than three years away. And as I’ve often said, quantum computers seem to be really good at doing one thing in particular, which is to simulate how quantum computers work. But I think Sabine has missed a bigger story, because right now in my lab at UC San Diego, I’m teaching my undergraduates to build quantum computers and then to program them and then eventually to launch them into space and maybe, just maybe, use them for AI in space, perhaps on the moon. Thanks to Artemis too. You’ll hear from these brilliant undergraduates later on, and when you do, you’ll see that what they’re doing has nothing to do with breaking code.

Brian Keating:
And by the end of this video, you can do it too, for free. Let me give Sabine her due, because the news this week is really extraordinary. Three papers dropped in a single week. First, Google found an algorithm that breaks encryption 20 times faster than anything we’ve ever had before. That cuts the qubit requirement from 10 million down to roughly half a million. They thought this was so sensitive they wouldn’t even publish the algorithm. Instead, they used something called Zero knowledge proof, basically a math way of proving that trust us, bro, without showing you exactly how it does so. Second, a startup called Oratomic says that they can break RSA encryption with just 26,000 qubits in about 10 days using neutral atom arrays, not the superconducting qubits I’m using in my lab, which are the same that Google and IBM are using.

Brian Keating:
This is a radical speed up and reduction in complexity. It’s awful difficult to get our lab equipment down to just a few tens of millikelvin, just a whisper above absolute zero and far colder than even the CMB, which is what I study at a balmy 3 Kelvin. Now, a third paper by another group showed that they can do it with 10 times fewer qubits than the original estimates required. Sabine is right. This is real and it’s accelerating faster than anyone predicted. The researchers themselves are debating whether it’s even responsible to publish this stuff. Scott Aronson, one of the top computer scientists alive, said that said, people in the field are reaching the point of wondering, should we publish this or not. In 1982, when I was a wee lad before high school, even accessing a university timeshare computer meant dialing in, often using a clunky acoustic coupler modem.

Brian Keating:
That transmitted data at a screaming 300 to 1200 bits or baud. The procedure was tedious. Pick up your phone, plug it in, wait for the screeching handshake, type a text based login and issue an arcane command like rmdrc foobar just to navigate a 24 row monitor. That agonizing lag is the perfect analogy for quantum computing five years ago where you waited in a queue for a noisy 2020 qubit result from a remote cloud. Today, my friends at Quantum Rings again, not sponsored allows you to explosively advance on that timeline right now for free. It puts a high fidelity quantum circuit simulator with hundreds of qubits and millions of gate operations right on your laptop, replicating Google’s $10 million quantum supremacy experiment on your own hardware. It’s really a whole new world and I want my undergraduates and my viewers and listeners in the audience to take advantage of it.

Bob Wold:
The truth is that quantum computing holds immense promise. I mean unimaginable things. It’s very possible that my grandchildren could grow up in a world where cancer is a thing of the past, because quantum computers have provided real time computational simulation to let us experiment with these drugs without the burden of manufacturing them ahead of time, where things like EVs could be four to ten times more efficient, drive as far as you need on a single charge with batteries that were made in a very sustainable way, with materials that were discovered because of quantum computers, where we could optimize supply chains, solving world hunger if the humans can get out of the way. Literally the biggest societal problems that exist today are in reach for quantum computers. And it’s not just science fiction anymore. This recent video covers three papers in the course of essentially a week that moved the goalpost dramatically for this goal. And we used to think about this as requiring systems that took millions of qubits, and now we’re talking about hundreds of thousands of qubits. And that essentially brings it from like 2035 to 2040 down to kind of like 2029, 2030 for Q Day for when quantum computers will be able to break encryption.

Bob Wold:
And if it happens in the dark, mysterious things are going to start happening and we won’t know for sure that it happened.

Brian Keating:
We won’t. What are they actually good for, these quantum computers? Sabine said, and I’m paraphrasing that apart from the code breaking. Nobody has figured out how to turn quantum computing’s theoretical advantage into a real world. Quantum chemistry, material science optimization, financial monitoring. She says not much there has happened. And again, if you’re looking at published breakthroughs, she’s not wrong. And see above, as I said, quantum computers are awesome. Unrivaled at simulating how quantum computers work.

Brian Keating:
But Sabine is looking perhaps at the wrong metric. The revolution isn’t in the papers, it’s in the tooling. Five years ago, if you wanted to run a quantum circuit, you needed to access IBM’s class. You’d wait in a huge long queue. You’d get a noisy result on maybe 20 qubits, even if you could figure out how to use it. And you’d spend more time debugging the interface than doing actual physics. Today I’m going to show you something. A free tool where you can use and learn about quantum computing.

Brian Keating:
It’s called Quantum 101. It’s by Quantum Rings, a quantum computer circuit simulator that runs on your laptop. Not 20 qubits, hundreds of them. Millions of gate operations. High fidelity. On your desktop, on your laptop, for free. They replicated Google’s quantum supremacy experiment. The one that Google said required a 10 million dollar superconducting.

Brian Keating:
Quantum rings doesn’t just simulate through their open quantum platform. You can write your circuit once and run it on real quantum hardware. And you can do that for multiple hardware vendors around the world. The same code, different machines. Imagine how cool this is. This will be on your resume. They give you $50 in free credits every 90 days. No credit card.

Brian Keating:
You can start breaking things and learning things and fixing things, but you won’t break your bank. Quantum Rings built a free course called Quantum 101. And when I say free, I mean actually free, not free trial. Then you pay wallet free forever. You’ll learn it. You’ll go through the 14 episodes. They’re self paced and they’re taught by a brilliant student at MIT in the PhD program named Cora Barrett. She works in the Quantum Systems group in the engineering department with superconducting qubit arrays.

Brian Keating:
The same technology Google and IBM are using for their code breaking breakthroughs. We talked about and Sabine has mentioned. Cora’s not teaching you the theory from a textbook. She’s teaching you from the lab. The curriculum takes you from ground zero. Literally zero. Not zero Kelvin. But episode one is the math prerequisites and software development kit SDK setup.

Brian Keating:
It’s all the way from there to building 100 qubit optimization algorithm. Cora Takes you through single qubit gates, entanglement, Grover’s search algorithm, quantum Fourier transforms, Shor’s factoring algorithm, which is literally the algorithm behind the code. Breaking news that Sabine broke teaches you about noise and error mitigation, the real bugaboos that maybe stand in the way of immediately achieving quantum supremacy. The course takes you through variational algorithms and quantum error correction.

Student:
We’ll have some factor of E to the I theta and we call theta the phase. This will come up a lot. Another thing I think is fun is that we can more intuitively see how I squared equals minus 1.

Brian Keating:
Again, it’s totally free, not sponsored. I love this group. They work with my students and here’s what my students had to say.

Student 2:
The biggest surprise was realizing that quantum physics doesn’t have to be intimidating. And it’s actually kind of mind blowing. Thing is that quantum 101 turned complex theories into pure curiosity basically and made me enjoyed every second of it.

Student 3:
The thing that surprised me the Most about the Quantum 101 course was knowing that qubits can be stored across a wide variety of media such as neutral atoms, artificial atoms, through superconducting qubits and photons.

Student 2:
It’s really just mind blowing to think of just thinking back on the complex theory we study in our quantum physics classes. I thought it would be much more difficult too. I saw you run my first quantum algorithm in just a few weeks. With Quantum 101. It was easy to do that.

Brian Keating:
These are physics undergraduates, including a freshman. Six weeks ago, none of them had touched a qubit. Now one of them has actually got an internship at one of the top quantum computing labs in the world in the Bay Area. Now they’re all running Shor’s algorithm on their MacBooks. That’s not just a testimonial, that’s data. Okay, now lastly, the internship. Why does this matter? And here’s the part that makes this urgent. Quantum Rings is hiring summer 2026 interns right now.

Brian Keating:
Here’s what their CEO and founder, Bob Wald had to say about what he’s so excited with. And I’ve worked with Bob and done and he’s graciously given me a lot of his time and free access to the to their Quantum Rings software walked us through how to get us uploaded and onboarded. So if you’re an undergraduate student, graduate student, it doesn’t matter. You go through Quantum 101, actually learn the material. Then after you do that, you might be a candidate for one of these positions this summer. Quantum Rings is based in Boulder, Colorado and they’re working with over 250 universities and institutions worldwide. In addition to UCSD, they’ve executed 10 million circuits and 10 billion Quantum Gate operations on their platform. That’s not a startup that might exist next year.

Brian Keating:
This is the infrastructure layer for the next generation of quantum developers. The summer 2026 internship applications are open now. I put the link in the description and it’s on screen, but here’s the thing. These positions will fill up.

Bob Wold:
Democratizing quantum computing is the mission of Quantum Rings. We build simulators that let you simulate quantum computers as they will be in about five to 10 years on your classical computers. Way slower, albeit than a real computer, than a real quantum computer will be. But we let you simulate what a quantum computer will be so you can start developing the software for it. Now we make it free for students and for personal use so that anybody can come and explore and innovate. We also offer Open Quantum, which you can find@openquantum.com that gives you free access to quantum computers. All the commercially available quantum computers will give $50 in free credits every 90 days for people to run and run their own experiments.

Brian Keating:
So let me bring you back to where we started. Sabine’s question. What are quantum computers actually good for? It’s a great question. Code breaking, yes, and clearly that’s terrifying because all of our banking, all of our Bitcoin and so forth runs on that. But the real reason there’s only one application showing dramatic progress right now is that code breaking has a clean, well defined problem with a known quantum speed up. Shor’s algorithm has been understood since 1994. The applications in chemistry, material science, physics, drug discovery, optimization, those require people to actually build the circuits, test the algorithms and, and find the right problems. That’s where a physics and engineering first workforce needs to occur.

Brian Keating:
And it doesn’t really exist yet. The bottleneck isn’t physics. The bottleneck is people. Right now there’s maybe a few thousand people on Earth who can conceptually design and execute a quantum circuit. We need hundreds of thousands, we need a million. And the tools to train them just became free and accessible on a laptop. You don’t have to come here and apply to UCSD and hope and pray you get in just to take a class that may not exist just yet. We’re working on it, but for now we’ve got Quantum Rings to help us with their Quantum 101 program.

Brian Keating:
And that’s the story I think Sabine missed. She may not have known about it. But it’s not that quantum computing doesn’t work for anything but code breaking. It’s that we haven’t had enough people at the entryway to the funnel to build the tools to help us find out what else it can do and how we can apply what it’s doing now. It’s like in 1982, me saying, what are personal computers good for? Like the Apple II playing the Oregon Trail. We need more people in the funnel to find out what they’re actually good for. And go watch Sabine’s video. I think it’s great.

Brian Keating:
I’ll link it right here. And I think she’s right about the danger. I just think the opportunity is bigger than she’s letting on. If you’re a student or researcher, just curious, go through Quantum101. Let me know what you thought about it. Tell me what you built. I want to see it. Subscribe.

Brian Keating:
If you want to see more of this, you can learn more from the president of the corporation, the founder of IT as well. And if you want to learn more about quantum computing from one of the world’s experts, watch my interview with one of the founders, the Titanic intellect, my friend John Preskill at Caltech. Watch that here. And don’t forget to, like, comment and subscribe. See you next time on into the Impossible.

Genius Philosopher: The Law of Physics That Explains Why Your Life Falls Apart

sabartigas — Mon, 20 Apr 2026 07:41:25 +0000

Genius Philosopher: The Law of Physics That Explains Why Your Life Falls Apart | Rebecca Goldstein

Transcript

Brian Keating:
There’s a law of physics that governs everything. Your happiness, your depression, and even whether your life has meaning. And guess what? It can’t be broken.

Rebecca Goldstein:
Life is a local violation of the law of entropy. It is a counter entropic resistance. The thing that the suicidally depressed people feel is that they don’t matter. Others do, they don’t. Nothing they can do will ever make them. This is how I judge people. Are you increasing entropy or are you decreasing it? These agents begin to have a longing to matter. If they do this, then what we have are non carbon based humans.

Brian Keating:
She’s a MacArthur genius, a philosopher who’s trained in physics, and she just used the second law of thermodynamics to explain while your life feels like it’s always falling apart. What Rebecca did next is what no physicist has ever done before. She took the second law of thermodynamics and built an entire theory of human meaning on top of it.

Brian Keating:
What took you from MacArthur genius, your many, many works of philosophy, and your great contributions to literature from the genius grants, et cetera. To write a book that’s basically a stealth physics book.

Rebecca Goldstein:
When I studied physics as an undergraduate, and then I had gone, when I went into philosophy, it was into philosophy of physics. So I’ve always been interested in physics. When I first learned about the second law of thermodynamics, I couldn’t quite conceptualize it. I couldn’t quite completely wrap my head around it. But it seemed to have implications for us, right? I mean, we are physical systems. We are subject to the second law of thermodynamics. There’s a tragic dimension to this law, and that we live in resistance to it. All living things live in resistance.

Rebecca Goldstein:
In fact, when I was a graduate student, that occurred to me, oh, my gosh, biological systems are really just organized to resist the second law of thermodynamics. I said, this is so exciting. Has anybody discovered this? And then I read Schrodinger’s what is Life? Other people had. In fact, Boltzmann himself had realized this at the laws of biology are substance biology’s response to this supreme law that tells us that in closed systems entropy never decreases. And if there’s any way for it to increase, it will. And what that entropy is, is the measure of the disorder of the system. The disorder is the more disorder, the higher the entropy, the less efficient work you get out of the system. And eventually the system will go to thermal equilibrium.

Rebecca Goldstein:
You’ll be able to get no more energy out of it. It’s somewhat the end of the system. And in fact, Rudolph Clausius, the 19th century physicist who formulated a concept of entropy, which means literally, transformation from within, there’s poignancy in that. It’s a transformation from within is going to the end of the system. And he had said, you know, that the universe itself go to thermal equilibrium, to what we call the heat death. And so there’ll be no more energy to be gotten out of it. This sounds like a joke from Woody Alley. His mother brings him to a shrink because he’s discovered that eventually the sun is going to go out.

Rebecca Goldstein:
He said, you know, how can I live? What’s there to live for? You know, the sun is going to go out. And the mother says to the shrink, you know, I don’t know why Alfie is so worried about it. It’s not going out over Brooklyn.

Brian Keating:
It’s in Annie hall, right?

Rebecca Goldstein:
Annie Hall. Yes, that’s right. What do you care?

Brian Keating:
Brooklyn’s not expanding, right?

Rebecca Goldstein:
Y that’s what it was. It was expanding, right? That’s right.

Brian Keating:
Classic. You studied physics as an undergraduate and you write in the book how you’ve been haunted since your early days as an undergrad by the second law of thermodynamics. So let’s start with that story that you tell first about Ludwig Boltzmann, who solved one of the great paradoxes of physics, the irreversibility paradox. Talk about that. And then why did, in your mind, was he so traumatized, perhaps, or full of dread of his equation that he took his own life? So talk about that.

Rebecca Goldstein:
And this is really good because it really ties back to your previous question about the types of scientists, the different types of scientists, types in terms of their personality. And to me, the formative feature of personality is how you minister to this longing to matter. So there was this great paradox which is probably most of the processes that we observe are irreversible. If you film them, like, like, let’s say I crack open an egg and I stir it up and then I fry it, and somebody filmed this and then they reversed the film. Anybody who sees the reversal of that film is going to know it was reversed. That cannot happen in nature. That it is going to uncook itself, unscramble. The yolk is going to separate from the albumen and jump into the shell and seal up.

Rebecca Goldstein:
Impossible, right? So almost, you know, everything that we. That we see is irreversible. What’s going on. There is a matter of what’s going on in the molecules that constitute this process. And if you filmed all of the motions of the molecules and then filmed in and then reversed the film. Perfectly, perfectly normal, you know, not contrary to nature at all. So how can that be? That the macroscopic state is just constituted by the microscopic state. On the microscopic state we find complete reversibility and on the macroscopic state, irreversibility.

Rebecca Goldstein:
It boggled the mind and it was called a paradox. And Boltzmann solved this problem. He really has only two premises here. That matter has constituents and that odor is much less probable than disorder. Those constituents can only be in a certain configuration. You can switch them around a little bit. When you have the egg cracked open with the yolk and the aluminum surrounding it, once you scramble it up, you can change. You can shuffle those part every which way and it’s still going to look the same.

Rebecca Goldstein:
The features of the system are going to stay the same. Instead of otter going to disorder. You could talk about shuffleability. One of my physics professor had described it in terms of shuffleability. The more entropy there is, the more shuffle ability. You can change around the parts and you’re still going to end up with the same system. There are just so many, many more by orders of magnitude, so many more ways of getting disorder than order in terms of the constituent states. This is the amazing thing.

Rebecca Goldstein:
So here is this real paradox, a real mind boggling paradox. All you need is the matter is made of constituent parts and the laws of probability, it’s the laws of large numbers applied to micro states. And that’s why it’s the supreme law of physics. I think it was Eddington who at first called it that. But it’s repeated by Einstein and by Stephen Hawking. But really all physicists, that is, we know it is never going to be falsified. All laws of nature are open to falsification. That’s what makes them scientific laws, right?

Brian Keating:
They’re provisional.

Rebecca Goldstein:
Well, it’s always provisional. We’re going to get more evidence. We’re going to have to go back to the drawing boards. But this, and Einstein puts it very, very beautifully. And as does Eddington. If something doesn’t agree with the second law of thermodynamics, too bad for your the give up. You are not going to get that Nobel Prize. Give it up.

Rebecca Goldstein:
In that sense, it’s the supreme law of physics. Ludwig Boltzmann and he solved this amazing problem and get this, none of his peers accepted it because of bad philosophy. They were all in that day. It was Ernst Machine was it like a leading Austrian and he’s great, great, great physicist, you know, but he was a positivist. He did not believe in molecules and atoms. If you couldn’t observe it, it didn’t exist. I would call positivism bad philosophy. That philosophy was sinking.

Rebecca Goldstein:
An amazing piece of scientific work that has proved so fruitful. The ramifications of this are all over, including. I want to make them even, you know, I want to draw even more consequences out of the law of.

Brian Keating:
Second, thermodynamics are beautifully. You say all tragedies are thermodynamic. You mention it in the context of his daughter Elsa finding her father’s dead body. And it wasn’t like he showed any sign. And we can’t go into the minds of someone who dies by suicide.

Brian Keating:
Right.

Brian Keating:
But at the same time, you’d think that this would be a more common thing. And I guess my question to you is, why do some scientists kind of fall victim to even bad philosophy, whereas others. So I’m thinking of Ignaz Semmelweis, who you write about. And we had Matt Kaplan on from the Economist, who wrote a book basically about Semmelweis not being accepted, called I told you so. And event he didn’t commit suicide. But. But he. He did kind of die tragically young and of illnesses probably precipitated by some of his melancholia.

Rebecca Goldstein:
He was in. In an asylum when he was. Yes, they tricked him into an asylum.

Brian Keating:
He was my friend Patty Carico invented MRNA COVID vaccine. She, you know, thrived despite even worse circumstances than people not believing her. They certainly didn’t believe. They wanted to deport her. A postdoc threatened to deport her if she got another job. And yet she came back resilient as ever and won the Nobel Prize. So why do some scientists fall victim to. I mean, physicists love to make fun of philosophers.

Brian Keating:
You know that I’m sure.

Rebecca Goldstein:
I love to make fun of philosophers.

Brian Keating:
Well, tell me, why do some, you know, have. We sort of have arrogance or, you know, and then other times seem to fall prey to their. To their predations?

Rebecca Goldstein:
Why is that temperament plays such a large role in this? I was not a person who was raised to think big ideas. I wasn’t raised to think at all. I was really raised to be a good Orthodox Jewish wife and mother. And my temperament didn’t go that way. I could just feel this sort of something, you know, the restlessness, the intellectual restlessness and whatever Altman, he knew he had solved something incredibly important. He said, you know what? It must be wonderful to be a general leading great armies into the battle and great victories. But as for him, the only thing he wants to do is sit in a little room and solve big problems that will contribute to knowledge. Now, to contribute to knowledge means that other scientists must accept it.

Rebecca Goldstein:
He wanted to happen. What exactly did happen to him? Only post death, post mortem, which is that he would make science grow. He has made science grow amazingly. But he despaired that would ever happen. And he had a temperament. He might have been bipolar, you know, but so it hurt him so much. And towards the end of his life, I mean, he was really desperate and he committed such a sad, sad thing. And as you say, I mean, you know, that his teenage daughter found him is just.

Rebecca Goldstein:
It’s such a tragedy. It was the day before he was supposed to return to teaching, and he was a beloved teacher. He had been a very funny teacher and very engaging, but he got more and more depressed. You know, creatures of matter who long to matter. You can only say that in English, but I’m so glad you could say that in English because it’s, again, incredibly poignant. You know, we’re creatures of matter who are subject to the laws of physics, including the second law of thermodynamics. But we long to matter. And so much of the book is trying to explain how that transformation from within, within us, in our species happens.

Rebecca Goldstein:
You know, that’s a normative transformation, an ethical transformation. And it’s really what distinguishes us, that we, in some sense, want to justify the fact that we matter so much to ourselves, that we pay so much attention to ourselves, and that we actually can pinpoint the place in human history where this emerged, during the period when all the religions emerged that are still extant, which is so interesting. And also Western philosophy emerged during the period of history that’s called the Axial Age. And that’s when we became these creatures who long to matter and who are searching for the right values to help us justify ourselves first and foremost. So I’ve been thinking about this forever, actually.

Brian Keating:
Yeah, you say it’s the hardest book. It was the longest book, which is surprising with all your other, you know, just enormous contributions to literature. It’s a beautifully printed and bound book. Prominent throughout it is this concept that you came up with, which is the maps of mattering. Talk us through the maps of mattering. What are the they and where do scientists, like my audience members, maybe, where do they find themselves?

Rebecca Goldstein:
I’ve noticed that there are four general strategies, and that’s what I sketched out. This is like the four continents of the mattering. And I asked AI to help me with how big to make them, how the proportions of humanity are, how they split up. And AI was very, very helpful in this there. First of all, let’s start with transcenders, what I call transcenders and transcenders, which we humanity has been for a long part of our history, up until, I guess we would say, the Enlightenment, we all sought our mattering religiously. We had the metaphysical premise that there is a transcendent presence in the universe, whether we call him God or something vaguer, and that this God made the universe, created something out of nothing, created the laws of nature and the moral utter within, and he created each one of us. You know, the fact that we are here is the proof that we have a role to play in the narrative of eternity. This is a very grand story.

Rebecca Goldstein:
I get goosebumps when I even just, you know, say it. Very grand way of conceptualizing our mattering. It’s a kind of cosmic mattering that, that the God who created everything created us. And we are here to try to figure out how he wants us to behave. These are the people I call transcenders. Then most of the people I talk to, even if they go to church or mosque or synagogue, they’re not transcenders in this way, you know, in that life would not be worth living if they didn’t have this metaphysical belief. Most of the people I have spoken to are what I call socializers. They understand this question, do you matter? That I ask them.

Rebecca Goldstein:
They understand it, as do I matter to others. And very often the others to whom they need to matter are the people who are already in their lives. We all need people in our lives. Transcenders, heroic strivers, competitors. These are the four branches of four continents that I delineate. We all need people in our life. We’re gregarious creatures, evolved from gregarious creatures. But for a socializer, there is no mattering other than mattering either to their people who are already in their lives, their children, or their romantic partners, or their community, colleagues, neighbors, people in their lives.

Rebecca Goldstein:
But there are other socializers. And I found this particularly with millennials, who it’s not so much people in their lives, it can be perfect strangers. Many millennials want to be famous. That is how they. They want to appease the longing to matter. They want to be influencers, they really want to be famous. And they’re willing to give up. I read a lot of psychological literature on this.

Rebecca Goldstein:
They’re willing to give up, like, you know, having children, having romantic partners, having any Connection with their family for fame, which is to be to matter to a bunch of strangers. Which is an odd thing, really.

Brian Keating:
Completely unique in human history. There’s a trillion dollar industry predicated on the need to matter, to get affirmation from strangers. A lot of people you don’t like, like I, I always feel like you go to a comedy club and it’s almost impossible for the comedian to really like the audience or whatever, but they want to be famous. But the most terrifying thing you quote in the book in that chapter on fame seekers had to do with the fact that they don’t care what they’re famous for. That’s terrifying.

Rebecca Goldstein:
I understand a little bit the rationale because the way I understand this longing to matter is really trying to convince ourselves, which I find endearing about our species, that we have to convince ourselves. But the evidence that a lot of people are paying attention to us seems to be overwhelming evidence that we ourselves matter, that we deserve this attention. So I understand it in some sense, but in fact, most of the people I’ve spoken to who are famous, it’s very, very insecure that they’re not particularly happy people. The public is very fickle. There’s that then, then heroic strivers and heroic strivers. Mattering doesn’t mean mattering to God. It doesn’t mean mattering to others. It means having certain standards of excellence that you are committed to, if not realizing, at least hatically approaching, you know, getting closer and closer to it.

Rebecca Goldstein:
And it could be intellectual, it could be artistic, it could be athletic, military, entrepreneurial, ethical. All of these types are profiled in the book. Their mattering project, whether it’s intellectual or ethical or artistic, is what, you know, keeps them going. And failures in that are existential failures. You know, those setbacks are existential. You know, I don’t feel like my life is worth anything. That sort of thing is what you hear. And the last group are competitors.

Rebecca Goldstein:
That’s the one group where when I talk about to them about mattering, they get a little uneasy. I can always tell by the reactions at this point, you know, like where you are, sometimes I’m wrong and sometimes it’s very, very tricky. But competitors really see mattering as zero sum. The more others matter, the less they matter. Just not enough mattering to go around. And it can be against individuals. It could also be group against group. And one of the people I profile, I really wanted to talk to a neo Nazi.

Rebecca Goldstein:
That’s somebody you know. It’s a group against group, zero sum mattering. And look he’s done great work. I’m glad for, you know, for his work. It’s seminal work. And so I would say for all of these types, socializers, transcenders, competitors, heroics, drivers can be good, it can be bad. And I try to define what are the good ways? How did we judge the good ways of trying to appease this longing we have? What are the creative ways? What are the destructive ways? And once again, entropy comes to the rescue.

Brian Keating:
You do write that once the disintegration from within has sufficiently progressed, it takes that much more energy to reverse it. A law that holds for our psyches as for all else. And so is depression sort of a, you know, they used to think miasmas and things in the area right about that. But is depression at heart an entropic collapsing process?

Rebecca Goldstein:
I have spoken to a lot of people who suffer from clinical depression, and I want to say first of all that the US hotline for suicide prevention is www.umatter.gov. the thing that the suicidally depressed people feel is that they don’t matter. Others do, they don’t. Nothing they can do will ever make them matter. A terrible, terrible. And what this means is they cannot, they cannot abide their own presence. I mean, I really think it shows how strong this mannering instinct is in us. You know, if you can’t somehow appease it, you can’t abide your own presence.

Rebecca Goldstein:
The people I’ve spoken to, and one is a very, very good philosopher who has suffered from depression, told me, is that phenomenologically, this is exactly what it feels like. It feels like psychic, psychic disintegration. It just feels like an unraveling and it’s a kind of death within death. You know, you don’t have the counter entropic drive to push on against entropy into your life.

Brian Keating:
You lack energy, you lack that innervation, positive and negative. And you know, when I read sometimes I get asked is, I’m sure you know, what’s the meaning of life? I usually say something like this, Rebecca, I usually say, and it relates to your theory and your, what you posit in the book, which is it relates to entropy in the following way. If I said to you, Rebecca, could I double your happiness right now? Well, you have grandkids, right? Like pretty hard. Like maybe you have two grandkids, you know, and then you go to four. But eventually it’s going to start to decrease, right? Like as wonderful as they are. You know, I know somebody with like 72, I mean, he’s a Chabad rabbi, his grandfather has 72, you know, grandchildren. I’m like, does he know all their birthdays and whatever? That’s probably like every day of the year or whatever. If I gave you a billion dollars, yeah, you’d be a lot happier.

Brian Keating:
But would you be, you know, like, could you be 10 times happier? But I say to somebody, and this really only kind of works for people that are. Have very tight, you know, either children or relationships in their life that are like children, if they don’t have biological. And that’s that. I could make your life infinitely worse. Like you, I don’t even like to say it, right. I’m not even going to vocalize what it is. But you and I know as being parents how our life could be get infinite words worse, right? So the converse of that to me is you should do those things that which if they were taken away through an entropic destroying process, you would be devastated. Okay, maybe not.

Brian Keating:
But like, the more of those things you have, I think the happier or at least you can progress towards happiness. You speak about happiness not as a state of being, but as a. Almost like a journey. Does that comport with this entropic, you know, overarching. I would say architecture that you speak about, about.

Rebecca Goldstein:
We’re not closed systems. Being a closed system is not compatible with being alive. We take in energy in the form of food and sunlight and certain chemicals and take it in, do the work of metabolism, keeping up the order that life needs. You know, life is a highly ordered system, so ordered it’s scary to think because the more ordered, the more ways it can go wrong. And all of this order is maintained, you know, in the face. And resistance to entropy. That’s what life, you know, viva la resistance. This is what life is.

Rebecca Goldstein:
That’s what it is. Resistance to entropy. While we’re of course exporting high entropic waste, you know, heat and other waste into the environment. Life is a local violation of the law of entropy. But the life with the environment, that system is obeying the law of entropy. There are no violations to the law of entropy. This is what life is. This is what flourishing is.

Rebecca Goldstein:
It is a counter entropic resistance, defiance and happiness. You know, happiness is a very ordered state. And I would say I would go even further. Everything worth living for is an ordered state. Knowledge is better than ignorance. Clarity is better than confusion. Flourishing is better than suffering. Love is better than hatred.

Rebecca Goldstein:
Beauty is better than ugliness. These are truisms, you know, these are that we all accept. And if you look at the thing that’s better, it’s an ordered state. It’s negation is a disordered state. So I think I would argue this is a very kind of Spinozist argument trying to get out of the laws of nature some ethical enlightenment, some ethical guidance, because that’s what we want. We want ethical guidance. You know, we know we want to matter. We know we do all sorts of things to matter.

Rebecca Goldstein:
Some people do very bad things in order to matter. Some of the people I’ve spoken to, they want power over others. They want dominance. They want to make other people life miserable. You know, these are bad things, right? They cause an increase in entropy. This is how I judge people. Are you increasing entropy or are you decreasing it?

Brian Keating:
Well, one of my favorite lines in the book that caused me to laugh out loud while I was playing golf with one of my kids and listening to the audiobook, which everyone should get, all versions of it. At one point you say, and I’m like about to hit my 16th shot on the hull, and you say that we burn 320 calories per day just by thinking. So if this book is pushing you to step up your thinking, even only to disagree, then you’re burning extra calories. So, Brian, you’re welcome. And so I read the book twice, Rebecca, so I could have that extra croissant. But it raises a real question. If people or situations are anti entropic. You just said, like, you judge people.

Brian Keating:
I’m going to ask you a very provocative question, which is, can people who don’t have children? And children could mean biological, but it could also mean ideological children. It could mean mentees, it could mean proteges. It could mean people that you sponsor, your big brother, big sister, do they matter less? I know it’s provocative, but can we say something about that?

Rebecca Goldstein:
Any mattering project that depends on making others feel like they matter less is wrong. I think I have a good proof. I didn’t put it in this book because my editors, they wanted the book to sell. There couldn’t be too much, too much philosophy. That’s right. But I think a very good proof for why we all morally matter. And I think I’ve actually even broached it here. There’s something ennobling about wanting to matter and try and devoting so much of our energy to these mattering projects.

Rebecca Goldstein:
We devote so much. It’s hard enough to live, right? But no, we devote so much of our energy to these mattering. Writing books, studying, bringing up our children, fighting for justice. All of you know, so many different Ways. What are the bad ways? Well, anyone that you know, any, you know, anything that depends on making others feel like they matter less, either those in your life or you know, ideologically or whatever. But I would also say that some mattering projects can be bad because they’re not actually working for you. I mean, sometimes as a professor, you know, you have students and they want to study a certain thing and you don’t know really why they want to study it. They don’t love it, they’re not doing well in it.

Rebecca Goldstein:
But somehow their mattering seems to depend on this. It’s kind of a responsibility to say, look, you’re very smart, you have many talents. I don’t think this is the best use of your talent. So to answer your question, here’s what I would say. Because I want to be extremely pluralistic and I know people who I think live wonderful lives who have people that they’re particularly caring for in their lives. That’s not, they’re just not caretakers. And I’m going to go back to Hillel the Elder, the great rabbinic sage of the first century. He said, you know, if I’m not for myself, then who will be for me? We can translate that into entropic language.

Rebecca Goldstein:
I have to be for myself. I have to be constantly fighting entropy and trying just to survive and to thrive. And because of that, you know, I pay a lot of attention to myself. I’m not, it’s not that we’re self centered but we have to feel ourselves deserving of attention, of our own attention. I mean our whole planning, our, our whole sense of engagement with life demands this. And so of course I have to be for myself. But if I’m only for myself, then what am I? Right? So the way I would translate that is if your Mannering project is only working for you and it is not having, it’s not helping in any way to enforce the counter entropic process which is life and flourishing. Then you’re selfish, you know, you’re selfish.

Rebecca Goldstein:
But that there are so many ways of doing that, you know, I mean even, you know, plant a garden in your, in a park, you know, so others can enjoy it. There’s so many ways that you can in some way be a force or save, save the animals, you know, Right. They’re suffering too. Right.

Brian Keating:
This book, we have to do what you’re not supposed to do, which is judge a book by its cover.

Rebecca Goldstein:
Hey book lovers, we’re judging books by the covers. We know we’re not supposed to do it, but I answer the impossible. There’s nothing to it. Let’s take a look and judge some books.

Brian Keating:
Take us through the book. The title, the subtitle and this map of meaning or this braided thread. It says Mercurial. I love the title, the COVID and the subtitle. So take us through it, Rebecca, please.

Rebecca Goldstein:
Yeah. The Mattering Instinct. The subtitle. How our deepest longing drives us and divides us and this divides us was very, very important to me. And that was sort of. After germinating these ideas for decades, what finally got me to write is what seems to be a crisis of mattering that we’re going through and you know, so dividing us to the point that it’s hard to have a civil union. I did want to offer this book as a way of perhaps being able to see the deep humanity in all of us and where we diverge. A lot of the divergence is in good faith, you know, to be able to see each other as generously as possible.

Rebecca Goldstein:
That was really the motivation because frankly, you know, trained in analytic philosophy, analytic philosophers like very little problems. Problems. Puzzles. We like puzzles. Puzzles and language are the best, right? I’m suspicious of big theories, but somehow this theory kept growing in my mind from physics to biology to psychology to philosophy to ethics, you know, and I was suspicious, I would say maybe afraid even to put it out. Like who the hell am I to put forth a broad theory? But I think it was really this sense of. It helps me when I get very angry when I’m reading the newspaper and it’s like, what’s wrong with my species? It helps me to go through the ideas that I work out here and to just to grow the generosity toward one another. So it’s in that spirit, and that’s how I understand this braid.

Rebecca Goldstein:
We’re together, we’re together. We’re so together. We are all, you know, the whole scientific story of how we come to have this longing to matter and to justify ourselves. It’s a common story, we share it. But then the way we appease this longing to matter, this mattering instinct, find a way of living with this self justificatory longing that requires us to have values, which is a leap. The values don’t follow from all of this. If there’s. There’s free will anywhere, it’s here where we branch off and we become undivided and go off in.

Rebecca Goldstein:
That’s what I understood by this. I had turned down a whole bunch of covers because it’s a very abstract idea and a lot of the covers, they gave me looked like Introduction to Differential Geometry. It just looked like a math book.

Brian Keating:
Fear that a lot of people have nowadays is about artificial intelligence kind of replacing what we do, that we have a sense of mattering from what we derive our matter. And you quote Freud in the book. Freud said all of life is work and love. And if AI can replace the work of knowledge workers like you and me and it can replace the love because of things like character AI and all these artificial relationships that don’t require me to go out and ask a woman on a date or nowadays for men. So I want to ask you the question, can AI have a mattering instinct or is it encoded in this wet supercomputer that we carry on our shoulders? You know, is it possible you’re right that AI is making everyone feel that redundancy is threatening to us, but will the AI rob ourselves of our mattering?

Rebecca Goldstein:
The two, you know, two different questions there, you know, one which is really, I think, you know, going to be upon us maybe already is, you know, that some of the most creative ways of appeasing or mannering instinct will be superseded by what AI can do. Prove math theorems faster, make discoveries in science, write novels, write music, paint pictures that have led to flourishing and led to great achievements that we can all take pride in. I take great pride in our species producing, you know, Bach and Shakespeare and Michael Jordan. I’m a big basketball fan. Here’s some. One thing I would say, you know, the heroics drivers, what I call heroic strivers, it’s really going to threaten them. I don’t think that the socializers are going to look to, I mean to some extent maybe for romantic partners or. But mothers are not going to have little babies.

Rebecca Goldstein:
AI agents that are acting like they’re babies. There’s. I don’t think this is going to happen. But I think heroic strivers, what I call heroic strivers, are going to be severe. One of the ways to be a heroic striver is ethically. And that will still remain to us. AI will not be able to do that. They could write our novels or our poetry or our music or prove our math theorems, but they’re not going to be able to do that for us.

Rebecca Goldstein:
And so wouldn’t that be a wonderful, wonderful turn of events of that’s if somehow there was a change, an incredible ethical change. And that’s how we got our status from how much good we’re actually doing in the world, how much counter entropic good we’re doing in the world. You Know, it’s, this is a big thing that’s upon us is all I can say. I can’t think of anything else. Not the industrial revolution, not the Enlightenment, nothing that has the possibility of so changing what we are and what we see our lives as being about.

Brian Keating:
Even the very name of our species. You know, Homo habilis meant, you know, tool maker or handyman.

Rebecca Goldstein:
Yeah.

Brian Keating:
Homo sapien means man who knows, Right.

Rebecca Goldstein:
So exactly, exactly where do we go

Brian Keating:
when we’re not the only things that know?

Rebecca Goldstein:
And your other question, if, you know, God forbid, if these agents begin to have a longing to matter, want to justify their own, you know, it would take self reflection, you know, of the sort that we have, you know, being able to step outside themselves and say, oh my God, I pay so much attention to myself, am I worth it? Do I deserve this? If they do this, then what we have are non cards, carbon based humans. These will be humans. And that means we’re going to have to think about their rights. We’re going to have a whole different way of having to think about ethics because we will have created, we’ve always been creating humans, but we will have created humans in a new way. You know, philosophers have been added for over 2000 years since the ancient Greeks. This is the moment for philosophers because these are philosophical problems. So show us what you’ve got. Philosophers, right? You’ve been thinking about this for 2000 years, show us what you’ve got.

Brian Keating:
Rebecca. This has been such a wonderful conversation. This book is incredible. It reminds me of a famous quote by John Archibald Wheeler, the man who coined the term black holes and matter.

Rebecca Goldstein:
I had him at Princeton. He was.

Brian Keating:
You did. Oh, you’re so lucky. Your career is legendary. I mean, I just love your writing and your books. But Wheeler said maybe you heard him say it, maybe not. He said matter tells space time how to curve and space time tells matter how to move in this book, the Matter Entirely was one of the most moving books to me and hopefully we’ll have many more. You’ll write many more books or we’ll talk about your other books too that have been so important to me and my colleagues and just the intellectual circle that I move in. But the movement of this book, it was surprising to me just how deep it is, how accurate it is and how precise it is.

Brian Keating:
It’s a wonderful book. It’s one of Apple’s most anticipated books of the year. It’s got, you know, hundreds of incredible reviews already. And I just thank you so much for sharing your time and just your ideas and your brain, your giant brain with the into the impossible. Audience thank you so much.

Rebecca Goldstein:
Rebecca oh, thank you so much. I knew it was going to be

Brian Keating:
fun and I’ll do it again sometime.

Brian Keating:
Rebecca Newberger Goldstein just used the second law of thermodynamics to explain depression, meaning, and why AI might create new species. If that changes how you think about what matters, hit subscribe and turn on notifications. Drop a comment which of the four types of person are you? And if you want to go deeper on entropy and explore a provocative new theory that perhaps there is a new arrow of time, click here and watch my interview with Michael Long. You won’t be disappointed, and your life may just keep it together a bit longer. Go ahead, click it now.

You’re Full Of S!’ Piers Morgan Takes Down Moon Landing Denier Artemis II Debate

sabartigas — Mon, 20 Apr 2026 07:19:48 +0000

You’re Full Of S!’ Piers Morgan Takes Down Moon Landing Denier Artemis II Debate

Transcript

Bart Sibrel:
The most powerful government in the world falsified their alleged greatest accomplishment. They did indeed fake the moon landing.

Brian Keating:
I want to treat Bart as a colleague, maybe not as an equal with our father.

Bart Sibrel:
Oh, my goodness.

Brian Keating:
If you would let me teach you some physics, then you could make your argument stronger.

Piers Morgan:
Charlie Duke is an Apollo astronaut, the 10th and youngest man to walk on the surface of the moon. What do you feel about the conspiracy theorists who think the moon landings were all invented? They never happened, they’re fake.

Charlie Duke:
You’re willfully ignorant if you don’t believe that we landed on the moon.

William Shatner:
What is the mindset of somebody who said, well, it didn’t really happen? That’s like the denial of humanity. These crazy individuals shouldn’t have our attention.

Piers Morgan:
Given this is the furthest that NASA have ever sent a rocket, presumably you think this must be fake, too. The Artemis II mission to the dark side of the moon will be the furthest human beings have ever traveled from Earth. It’s a precursor to a full return to the lunar surface and perhaps even reaching Mars. But for this trip, historic though it is, there will be no landing, no walking, no flags planted, very much unlike the Apollo mission of 50 years ago. In a moment, we’ll talk to the man who says he’s on a CIA hit list because he blew the whistle on what he says are the original moon landings being fake. But first, let’s talk to the Chancellor’s distinguished Professor of Physics at UC San Diego and host of the into the Impossible podcast. Welcome to you, Professor Keating, how are you?

Brian Keating:
Good to see you again, Piers.

Piers Morgan:
Well, good to see you. I’m obviously about to talk to Bart Sibrel. He’s made himself pretty infamous by ending up being punched by Buzz Aldrin for questioning to his face that he’d walked on the moon. And being part of that, of course, that first immortal trip. Before we get to him, what is your view of people that just don’t want to believe this has ever happened?

Brian Keating:
I think it’s something we need to take very seriously, but not literally. In other words, there are reasons. You could say there could be reasons why NASA and maybe the US Government, maybe even the CIA, would want to put a whack on Bart. As I’ve heard him describe it. Perhaps there are some mistruths that our government tell from time to time, but in order to believe the moon landings in the 1960s and 70s were fake, you need to believe a whole host of things that not only require vast conspiracy numbers involving hundreds of thousands of people, you need to Suspend your scientific reasoning and your ability to search for truth. You know, Piers, we live in an age that’s sometimes called post truth or post fact, where you’re entitled to your own ideas and theories. But in reality, what worries me more is not that people get facts wrong. I mean, that happens all the time.

Brian Keating:
Happens to me all the time as a scientist. But it’s that we undermine the process of truth seeking that no society can withstand. So I’m hoping to talk to Bart. He knows about me. I’ve invited him to chat on my podcast, and he’s turned it down for reasons that I don’t understand. So I’m eager to talk to him because I think it’s instructive for the public to see not only the great triumphs, but why we know for certain that these things happen and why it speaks to not only American exceptionalism, but humanity’s exceptionalism.

Piers Morgan:
Well, you know what? We’ll come back and discuss Artemis specifically in a bit. But given you’ve teed this up very nicely, and we have Bart Sibal waiting. Joining me now is Bart Cyril, who has been what many viewers, a conspiracy investigator about the moon landing, saying they’re fake. He even confronted, as I said, Buzz Aldrin. Let’s take a look at what happened then.

Bart Sibrel:
Yeah, you got to keep shooting, man. Okay, well, if you can put it on your shoulder. Don’t be shy.

Piers Morgan:
Just come with me first.

Bart Sibrel:
You really like attention, don’t you? You’re the one who said you walked moon when you didn’t. Calling the kettle black if I ever thought of it. Saying I misrepresented myself.

Charlie Duke:
Get away from me.

Bart Sibrel:
You’re a coward and a liar and a thief.

Piers Morgan:
Well, Bart Sibel joins me now. Welcome to Uncensored. I’ve actually met Buzz Aldrin. All I remember is he had one of the hardest handshakes I’ve ever encountered on any human being. Ever. So you were quite courageous there, Barster, Albeit as you were calling one of the great modern heroes a coward. Why are you so obsessed about branding the lunar landings fake?

Bart Sibrel:
Well, because one of the most historic events in human history isn’t putting a man on the moon. It’s that the most powerful government in the world that hypocritically claims to represent truth and justice falsified their alleged greatest accomplishment. They did indeed fake the moon landing. And, Brian, first time I’ve ever seen you speak. He’s obviously highly intelligent and a very reasonable person. Unfortunately, people want to believe a tantalizing lie like their team ran or Won the Super Bowl. What he’s, you know, he claims, I’m denying scientific reasoning, but actually he’s doing that because it’s never happened in the history of the world that a milestone is technologically occurred, like, let’s say flying across the Atlantic in 1927 or breaking the sound barrier or splitting the first atom. It’s never happened in the history of the world that more than 50 years later, no one could accomplish it.

Brian Keating:
What would hopefully happen today?

Bart Sibrel:
Well, you know, let me, let me. I’m up against. We’ve heard your side of the story for 57 years.

Brian Keating:
I would love to just comment on that. I have actual experience with an event that happened and it was separated by 60 years. I reached the South Pole twice in 2007 and 2009. Do you know who the first people to reach the South Pole were, Bart?

Bart Sibrel:
Well, Amundsen, Scott?

Brian Keating:
Yeah, that’s right. And you know, Amundsen was from Norway. Hold on, hold on a second. Amundsen was the first.

Bart Sibrel:
They went to the moon ahead of us.

Brian Keating:
Reach it. And we didn’t go back for 50 years until 1964. We didn’t go back for 50 years. Exactly. Like what happened? Was it harder? Have I never been to the South Pole, Bart?

Bart Sibrel:
I don’t know. I mean, I presume that you have

Brian Keating:
video evidence of me there interviewed by.

Bart Sibrel:
Here we are with six. I’m not denying that. The, the fact is we have.

Brian Keating:
You just made a claim that nothing gets hard, nothing gets easier, unless this is technologically true.

Piers Morgan:
Well, I can offer. I would like to offer my own. Well, hang on, Bob.

Bart Sibrel:
I’m not getting much time to share my side of the story.

Piers Morgan:
But hang on. I’d like to offer my own contribution to that debate because I personally went on the last Concorde flight, which was about 20 years ago, and we have gone backwards in the speed of passenger air travel because it now takes twice as long for me to get to New York as it did 20 years ago. So there’s another example.

Bart Sibrel:
The question is, are there aircraft that fly higher and faster than the Concorde and there are not with.

Piers Morgan:
Not with passengers.

Bart Sibrel:
Well, people are on board the airplane.

Piers Morgan:
They’re not with. There’s no commercial plane. There’s no commercial plane that can get to New York in about.

Bart Sibrel:
There’s no commercial plane. That’s about six and a half hours.

Piers Morgan:
Royce Concorde did it in 2058. So the premise of your argument is flawed because you’ve already heard one example from Brian. You’ve heard one from me. I’m sure there are a myriad other examples, but I’m just keen before we get too far into the weeds on that part of it, you said here about the lunar landings. In order to appreciate the full absurdity of the lie, it bears repeating what both the US government and NASA claimed in the 60s on the very first attempt to an all. With one millionth computing power of a cell phone, they’ve been able to send astronauts to orbit and land on the surface of the moon. A distance that is 1,000 times farther than they can achieve with human spaceflight today. To buy into your conspiracy theory about this and it never happened.

Piers Morgan:
The sheer volume of people who must have signed up to this conspiracy. Right. Is overwhelming. Why is none of them. Why have none of the people that were part of the lie. Why have none of them broken ranks to say this was all faked?

Bart Sibrel:
Well, first of all, you’re incorrect. I spoke to Eugene Kranz, flight Director. He said that someone in the command center cannot tell the difference between a quote, rehearsal flight and a, quote, a real flight. Just because there’s 400,000 bank tellers at bank of America. What a bank teller knows about corruption in the bank and what the CEO knows are completely different. There’s only three eyewitnesses to every program, and who knows where they’re really going? The fact is, we did have someone come forward. Two people came forward. Betty Grissom, the widow of the man who was going to be the first man to walk on the moon.

Bart Sibrel:
I interviewed her for four hours before she died. I bet Brian did not do that. She told me that her husband called her on January 26, 1967, from NASA and said, han. For some strange reason, the CIA is over the launch pad today, inspecting the equipment. I’ve been here eight years, never seen him before. Why did they show up?

Brian Keating:
That never happened.

Bart Sibrel:
The very never happened.

Brian Keating:
Even your own testimony.

Piers Morgan:
Well, allow Brian to respond to that, please. Brian.

Brian Keating:
She never said that. Speaking.

Bart Sibrel:
He interrupted me. Allow me to.

Brian Keating:
You just made a claim about CIA. I want to do you a favor. I think what you do is important. I think, as I said originally, I think it’s important to question things. Certainly. Certainly the government lies to us.

Bart Sibrel:
Oh, thank you so much.

Brian Keating:
Hold on one second. But what Betty Grissom said. She said they were all over the CIA, was in the mission command center. She never said that. If you go back and look at your own transcripts. She said, didn’t say they were on the launch pad. Had access to the launch pad because it was full of rocket Fuel, so they wouldn’t even let the technicians near it, as you know. But Bart, I think you have much stronger evidence and I don’t know why you’re leading with the things that are most easily deflated.

Brian Keating:
I’d love to talk about what you claim.

Bart Sibrel:
Betty Grissom for four hours before she

Brian Keating:
died, did you say. I’ve read your transcripts. I’ve read transcripts by you and by her. She did say that they were CIA. She never said they were crawling over the launch pad. And does that prove that? The movie.

Bart Sibrel:
You weren’t even alive at the time. That’s what she told me in a foreign interview.

Piers Morgan:
Let me ask you, Bob. Let me bo. Let me ask you. What is the. What is the most convincing piece of evidence you had that it was faked?

Bart Sibrel:
Well, I have the crew of Apollo 11 faking being halfway to the moon using a one foot model of the earth. And I have the CIA on a third track of audio telling to fake a four second radio delay from Earth orbit. And then we have the eyewitness testimony of a deathbed confession of Cyrus Eugene Anchors who saw them film it at Cannon Air force base in 1968, even confessed to killing somebody to cover it up because the NSA asked him to do so. That’s a strange thing to be saying.

Piers Morgan:
You’ve also claimed. Also. You’ve also claimed. I’ll come to you, Brian, in a second. But you’ve also claimed you describe what you call as anomalous shadows that are not parallel, suggesting multiple artificial light sources in the studio rather than a single distant sun. So these photographs that we’re looking at now you think are indicative of fakery.

Bart Sibrel:
Well, let me also say I went from being the biggest fan, greater fan than Brian. I had a shrine of Apollo pictures in my house for decades and a filmmaker’s job is to make fake scenes look real. Go back to the picture and look how shadows should be in sunlight. The sun, it’s a million times bigger than the Earth in volume. It’s 93 million miles away. It’s going to cast shadows in the same direction on the Earth or the Moon. There’s two telephone poles about five feet apart. The shadows are parallel.

Bart Sibrel:
Here’s a picture they claim was taken on the moon, of objects five feet apart. The astronaut shadows at 12 o’, clock, the rock five feet away. The shadows at 9 o’.

Piers Morgan:
Clock.

Bart Sibrel:
That can only happen with a close electrical light, which we just proved with one photograph that they faked the moon landing. Despite what anybody says, despite what the corrupt federal Government says that picture cannot be duplicated in sunlight. It can only be duplicated with the lens here on Earth. Which means they didn’t go to the moon. Okay, I’m sorry to bring you the bad news.

Piers Morgan:
No, no, that’s your claim. Brian Keating, your response.

Brian Keating:
Well, again, I want to treat Bart as a colleague. Maybe not as an equal, but I want to treat him fairly. I don’t want to say, bart, you have much better evidence than I’ve heard you talk about.

Bart Sibrel:
Oh, my goodness.

Brian Keating:
Well, I don’t think you’re a trained scientist, Bart. I mean, if I go to my

Bart Sibrel:
Wikipedia page, I don’t think you’re a trained cinematographer, either.

Brian Keating:
When I go to my Wikipedia page,

Bart Sibrel:
it says electrical light.

Brian Keating:
Okay, Bart, when I go to my Wikipedia page, people can see that I’m listed as a professor of astrophysics with 40 years of experience. When they go to your page, it says conspiracy theorist. So I don’t want to say that we’re equal, because we’re not. We’re not in the same league. I will treat you like a peer. I will give you an expert review of what you’re talking about. But what I want to tell you

Bart Sibrel:
very clearly is you deceived your league, is parroting back what you’re told.

Brian Keating:
I want to know. I want to use your own words. I want to treat you seriously, Bart. I want to say that you have talked to Candace Owens on her podcast, and you describe what she later called the firmament, the asteroid belt, and then later, the Van Allen belts. This is one key piece of qualitative but quantitative evidence that you have presented which I think deserves attention. You have a claim the Van Allen belts are deadly and they are not survivable, and NASA knew that themselves. Correct or incorrect, Bart?

Bart Sibrel:
Well, show the clip. What a clip number is it here? Right. Let’s hear it in NASA’s own mouth.

Piers Morgan:
Well, we’ve got the clip. Hang on, hang on. We’ve got the clip. Let’s play the clip. So the. The Van Allen radiation belts. You’ve argued the radiation surrounding Earth is so extreme, it would have been lethal for any human to pass through, making the journey impossible. So let’s take a look.

Piers Morgan:
We’re gonna play the clip.

Kelly Smith:
My name is Kelly Smith, and I work on navigation and guidance for Orion. We are headed 3,600 miles above Earth, 15 times higher from the planet than the International Space Station. As we get further away from Earth, we’ll pass through the Van Allen Belts, an area of dangerous radiation. Radiation like this could harm the guidance Systems, onboard computers or other electronics on Orion. Naturally, we have to pass through this danger zone twice. Once up and once back. We must solve these challenges before we send people through this region of space. We must solve these challenges before we send people through this region of space.

Kelly Smith:
We must solve these challenges.

Piers Morgan:
So that’s your claim, Bart. Professor Keating, what’s your response to that?

Bart Sibrel:
Well, it’s not my claim. It’s NASA’s claim. He said, we must solve these challenges before we send people through this region of space. Meaning? The radio.

Brian Keating:
Very carefully. He doesn’t say, because we’ve never done it before. He never asked me. Do you interrupt?

Bart Sibrel:
Because I’m not in the same league as you and you’re better than me that you.

Piers Morgan:
No, we just played an extended clip that you produced about a certain theory. So Professor Keating would not respond.

Brian Keating:
Right, So, a whiteboard sketch by some NASA engineer who is, to my knowledge, not sketching the exact schematics of the trajectory he shows and he describes. The Van Allen belts are deadly. And you’re right, Bart, they are deadly. And NASA knew that because. Who did Van Allen work for? John Van Allen worked for NASA. So in order for us to believe it, and he testified that the Van Allen belts, if traversed safely, were no threat to the astronauts beyond getting a few chest X rays, which you and I probably do every year. Right. So I have a model of the Van Allen belts here.

Brian Keating:
Here’s a plasma globe which has electron plasma in it.

Bart Sibrel:
I thought you bought that.

Brian Keating:
30,000. Hold on now. You’re not letting me present scientific evidence.

Bart Sibrel:
Okay.

Brian Keating:
There are electrons in here that are at 30,000 degrees Kelvin, far hotter than the temperature of the melting point of aluminum, which you talk about in that documentary, which I’ve seen many times, to debunk it inside of this plasma globe. The reason I don’t get melted is because the electron density is tiny. It is anisotropic. If you go at different regions through the Van Allen belts, it’s completely safe. And one last thing that NASA engineer mentioned. He said it could be dangerous to the navigation systems, the electronics. Correct. That means that according to you, we never even sent electronics, telemetry, anything through the Van Allen belts.

Brian Keating:
But you know who else agrees that we did? The Soviets. Our arch nemesis. Piers, you may not know this. The same day that we landed on the moon, the Russians had a probe that they were trying to return samples from the Moon. Like this moon rock that I have here. And they were trying to return it to Earth to beat us. And they ended up crashing that spacecraft. On July 21, 1969, they failed to reach it from, but they agreed to coordinate with NASA.

Brian Keating:
So they didn’t hit the Apollo lander because they agreed that would be a much worse thing. Now appears. Can you imagine us coordinating with Ayatollah Khomeini right now? And he’s gonna congratulate us tomorrow or tonight when the Artemis mission lands. That’s what goes around the moon. That’s exactly what happened. So the best evidence bar doesn’t come from America even. It comes from the Chinese, from the Indians, from the Russians, who are our nemesis at the time, proving that we went there with their own images, data and scientific evidence. So that’s the way we do things as a scientifically literate society.

Piers Morgan:
And your theory, Your theory, Bob.

Bart Sibrel:
Hang on, scientists. One of the facts you’re ignoring is that. What is his name? Rotajin Dmitry. He was the former commander of the Soviet equivalent of NASA. He said as soon as he retired the moon missions were fake. And then I have a friend who works at the Chinese Space agency. He says that they’re blackmailing NASA in exchange for technology that Congress forbid them to receive.

Brian Keating:
So we have retroactively to the Soviet Union, which doesn’t exist anymore.

Bart Sibrel:
He has. Wait a minute. We have the Russian space director saying the moon missions are fake. And we have an employee of the Chinese space agency saying they know the missions are fake and are being blackmailed by the United States.

Piers Morgan:
And your theory, your theory about motivation, your argument is that the they were faked to ensure a Cold War victory for the US over the Soviet Union. You contend that NASA was under immense pressure to fulfill President Kennedy’s goal of landing a man on the moon by the end of the 60s, but they lacked the ability technologically to do it. According to you, the risk of high profile failure and subsequent national humiliation led the US Government and CIA to stage the events in a studio instead. To which my obvious question would be a look. Full disclosure. I don’t believe a word of it. However, let’s just assume for a moment your theory is correct. Which studio? Where? Where did they do this?

Bart Sibrel:
Well, I guess you weren’t paying attention when I said they filmed it at Cannon air Force Base, June 1, 2nd and 3rd of 1968, according to an eyewitness who confessed to killing a coworker to cover up the moon landing fraud.

Piers Morgan:
Sorry, I did hear what you said, but there were a number of lunar landings. So you’re saying that it was all done in this one studio?

Bart Sibrel:
Well, no, we know. We know that the first one. The TV images were filmed at Cannon Air Force Base, according to an eyewitness who confessed to a homicide that was investigated by the military police, the United States Senate Intelligence Committee and the FBI. And when they investigated, they asked him, why did he kill this co worker at Cannon Air force base in 1968? He said to cover up the moon landing fraud. He took an oath by the NSA for secrecy. His co worker was going to tell the public and he killed him to keep it a secret. And back to whether the radiation belts are lethal or not. Don’t take my opinion.

Bart Sibrel:
Don’t take Brian’s opinion. Go to sabrell.com and read Van Allen’s opinion, his document that he published after sending probes up into the radiation belts in 1958. Scientific American article. And he says they are 250 times a lethal dose. So when they say we have.

Brian Keating:
That is depending on how you go through it, Bart. If you go through a rainstorm through the eye of a hurricane, it’s much different than going through the outskirts of it where it’s a nice light London fog, perhaps. It’s very different. Your Van El belts are highly anisotropic. I want to teach you some physics.

Piers Morgan:
Hard.

Brian Keating:
If you. If you would. If you would let me teach you some physics, then you can make your argument stronger, perhaps. Okay. There’s multiple Van Allen belts. There’s an inner Van Allen belt. There’s an outer Van Allen bell.

Bart Sibrel:
Teach me, professor who? Parents back.

Brian Keating:
I’ve heard you refuse to debate me. Bart, this is my only chance to debate you. You refuse to debate me on Joe Rogan. You refuse to debate me on Joe.

Bart Sibrel:
I never received an invitation to debate.

Brian Keating:
Yes, you said you’ve received the invitation on Danny Jo podcast, and you said you don’t want to debate me because I’m a victim. Much like pedophilia victims. It was so bizarre. I want to take my opportunity.

Bart Sibrel:
He asked me if I wanted to debate you, and I said no, because you’re a victim. You have Stockholm syndrome. You’re defending the people who are deceiving you. You’re not the perpetrator.

Brian Keating:
The Russians did. The politburo. The politburo that testified and said, congratulations,

Bart Sibrel:
what happened on the moon.

Brian Keating:
Wait, why did. Why did the Russians.

Piers Morgan:
Do you mind if I just cut to the quick here? Do you think you’re just full of shit, mate?

Bart Sibrel:
What’s that?

Piers Morgan:
Do you think you’re just full of shit?

Brian Keating:
No, I don’t think he does.

Piers Morgan:
Is it all just a scam just to make money? Raise your profile.

Bart Sibrel:
Well, I mean, come on.

Piers Morgan:
Spewing such obvious bullshit around the world about something that everyone knows happened, and you’ve made yourself well known.

Bart Sibrel:
Let me boil it down for you.

Piers Morgan:
You answer your question, insulted Buzz Aldrin to the point he punched you.

Bart Sibrel:
I’m sorry. It’s the truth. It, about corruption is insulting to people who are flattered by it in a fallen world. The fact is, JFK’s relatives say with 100% certainty he was killed by the CIA. Robert McNamara on his deathbed said they started the Vietnam war and killed 58,220 of their own people on a CIA fabrication. So they’re killing tens of thousands of their own people, so presumably killing their own president. Wait a minute. So they’re not going to have a problem faking a TV image.

Piers Morgan:
Okay.

Bart Sibrel:
The only problem is that. That it’s a positive line.

Piers Morgan:
Okay, but just to be clear, then, to extrapolate your theory, given this is the furthest that NASA have ever sent a rocket to the dark side of the moon, presumably you think this must be fake, too?

Bart Sibrel:
Oh, no, I hope. I hope they are able to do it. The issue is, how do you think about it?

Piers Morgan:
So do you believe the Artemis rocket is gonna be a genuine mission or a fake?

Brian Keating:
Does it have to go to the Van Allen Belt?

Bart Sibrel:
I would assume it’s gonna be genuine.

Piers Morgan:
How does it get through the Van Allen Belt?

Bart Sibrel:
Why is it. Listen, the issue.

Piers Morgan:
Hang on. No, how does it get through? How does it get through the Van Allen Radiation Belt?

Bart Sibrel:
I got two people not letting me finish this sentence.

Piers Morgan:
How does it get through?

Bart Sibrel:
The issue is. The issue is.

Piers Morgan:
That is the issue.

Bart Sibrel:
Why is it with six decades of better technology, they can only do 20% of what Apollo did? It’s electrical.

Piers Morgan:
So do you accept the Moon, but do you accept now that rocket, space rockets can get through the Van Allen Radiation Belt?

Bart Sibrel:
Unmanned ones? And maybe they have protection? We know they didn’t have protection as of 2014. He said we must solve these radiation challenges before we send people through this region of space, which anything prior to 2014 did not leave Earth orbit. He said so himself. Okay, I’m sorry.

Brian Keating:
So do you think Elon Musk is in? Or do you think. Do you think Elon Musk is deceiving himself?

Bart Sibrel:
Well, he knows the moon missions are fake. He’s playing ball. He didn’t want to bite the hand that feeds him.

Piers Morgan:
So he’s. He’s all part of the conspiracy, is he?

Bart Sibrel:
It’s not a conspiracy. It’s simply they perpetrated a fraud. They did a counterfeit. They cheated. Elon Musk says to return to the moon, they’re going to need 15 fuel launches first. I got a clip here. Number five. A guy who works for NASA says it’s going to take 30 launches of fuel in order to have enough fuel to go to the moon.

Bart Sibrel:
So how did Apollo do it with 1/30 the amount of fuel? I mean, the truth is right there in front of you.

Piers Morgan:
Final words to Professor Technology.

Bart Sibrel:
And they can only do 20% of what they claim to did with 1 million.

Piers Morgan:
Okay, Professor Keating can’t even land. Professor Keating, final word to you about the Armistice 2 mission.

Brian Keating:
Well, I just want to say, first of all, to fake the moon landings would have been much more cost prohibitive, difficult, and involve a much larger conspiracy than actually doing them. We have evidence from around the world. Scientific work. Scientists are the most likely people to want to shoot down experts. Bart, this is where I feel like you’re not taking advantage of me as a collegial engagement because we’re the most interested in proving things wrong. That’s what we do for a living, Bart. But on the topic of science, what Artemis is going to do appears is perhaps pave the way for us to extend our consciousness, our civilization, into the solar system, into the universe beyond. Because what happens if a large meteorite, a huge asteroid impacts the Earth, God forbid, or a global pandemic happens again? And all those reasons, by the way, are reasons that Bart should support the mission of NASA, which has provided such a great deal of technology that has enabled him.

Brian Keating:
If he’s ever been on a commercial airliner. I used to work for NASA, working on aviation safety. NASA does a whole lot more than just landing on the moon, as amazing as that is. And they do it all peers for a budget that’s equal to what women in America spend on makeup. About 20 to 25 billion dollars. Most people think it’s 10 times higher. It’s very low amount of money. We’re going to go there, we’re going to build telescopes.

Brian Keating:
We’re going to explore habitation there. We’re going to build rockets. Because the moon is full of ice and its craters that are shadowed. Ice is hydrogen and oxygen.

Piers Morgan:
You know, I think it’s going to be great. And I love all this stuff. And I think the answer to the whole thing is that when they actually send people to walk on the moon again, they should send Bart up there. Bart, you should get on the rocket.

Brian Keating:
Let’s do a debate there, Bart.

Piers Morgan:
Yeah, and we can continue the debate on the surface of the moon. And then Bart, my opening line would be, see? Told you got to leave it there. Thank you all very much. Bart, thank you. Thank you, Professor Keating, thank you very much.

Brian Keating:
Thank you, Piers. Thank you, Bart.

Piers Morgan:
Well, let’s turn now to too many, most certainly no fact from fiction when it comes to space travel. Charlie Duke is an Apollo astronaut, the 10th and youngest man to walk on the surface of the moon. A legendary actor and part time astronaut, William Shatner, sometimes known as Captain Kirk of the USS Enterprise, particularly by men of my generation who were weaned on that glorious character. Welcome to both of you. Charlie Duke, what an amazing thing to have walked on the moon. Just we’ve got some footage of you which I’ll just show my viewers to remind them of your great moment. Let’s have a look at this.

Charlie Duke:
Hey John, while you’re sampling there, you might look around and see if you see any of that vesicular basalt.

Bart Sibrel:
That’s what I’m looking at.

Charlie Duke:
Good. Joe, I told him you were.

Bart Sibrel:
Whoop.

Charlie Duke:
Okay, we see that one went all the way in.

Bart Sibrel:
Not quite

Piers Morgan:
my first thought watching that Charlie, was a couple of months ago I tripped and broke my hip. And if I’d been in an airless environment like that, I probably would have escaped without injury. So I’m very jealous of the fact that you were falling over there in such conditions. But to be serious for a Moment, you were 36 when you walked on the moon, the youngest to do it at the time. And it’s 1972. Just a basic question, what was it like?

Charlie Duke:
Well, it was one of the most exciting adventures that I’ve ever had in my life. Of course we enjoyed every moment of it. We had three excursions out on the surface. We had a tremendous opportunity to explore the lunar highlands for three days. And John and I didn’t want to come home. We were having so much fun. But they said, get back inside guys, it’s time to come back. Anyway, we did a great job, I thought, corrected 200 pounds of moon rocks and did a lot of good experiments and left a lot of experiments up there to operate.

Charlie Duke:
So it was a tremendous opportunity for us.

Piers Morgan:
You also had another extraordinary role in the first lunar landing when you famously responded to Neil Armstrong saying the Eaglers landed with the words Roger Twang. Tranquility, we copy you on the ground. You’ve got a bunch of guys about to turn blue. We’re breathing again. Thanks a lot. Which was fantastic.

Charlie Duke:
I was so excited that Tranquility came out twang at first, and so I corrected myself. Neil had told me that he was changing a call sign to tranquility from Apollo 11 or whatever, Eagle. And so I was prepared for it. But it was so exciting a moment there, you know, we landed with maybe 20 seconds fuel remaining, and so there was a lot of tension. And when Neil said, well, Buzz said, contact engine stop and we’re there on the ground, it was just excitement got me. And twang came out instead of tranquil.

Piers Morgan:
William Shatner, welcome back to Uncensored. Always great to talk to you. You obviously went to space recently and you were very emotional, I remember about the experience, understandably. How much would you have liked to have walked on the moon like Charlie? And how envious are you of this latest mission, which is the precursor potentially to people doing it again?

William Shatner:
Well, these guys, like test pilots and explorers and people who venture out into essentially the unknown, enjoy it like it’s a thrill, like, I mean, falling like you described. You fell on Earth and you had difficulty, you broke your hip. He falls on the moon and there’s nobody there to help him up, right? And he’s got a pack on his back. It’s awkward. He’s alone. These explorers, these test pilots, these astronauts, they get off on the adventure. We ordinary people have to imagine what it’s like to see flame going past your window, wondering whether the shields are going to hold or not, whether 20 seconds of fuel is enough to get back up. And there’s this whole exploration mentality that requires, I mean, it’s insanity, really, to want to do that.

William Shatner:
And they’re insane in a great way, furthering us. But these people going up in Artemis, they’re in the same tentative position. They don’t know whether that shield is going to hold. They don’t know whether the. The hydrogen is going to explode. And I, when I went up and I, on my way up the gantry, I passed by the off gassing. I said, what’s that? They said, it’s hydrogen. I said, hydrogen? That’s one of the most explosive, elusive gases we have.

William Shatner:
They’re dealing with the unknown, they’re dealing with exploration, they’re dealing with death. Have they come to grips with what death is? What’s on the other side? All those enormous questions are, I don’t know whether the astronauts are sitting in the Artemis thing right now, but you can imagine them leaning back, looking up into the sky, waiting for this explosion under them, wondering whether they’re going to live or die, and see their children

Piers Morgan:
and their Loved ones again, I feel exactly the same way. I just want to show viewers a couple clip of you in space because it was great. Let’s take a look at this. God, weightlessness.

William Shatner:
Oh, Jesus. No description can equal this. Wait, this is nuts. Oh,

Piers Morgan:
This is Earth.

Bart Sibrel:
Oh.

William Shatner:
Oh,

Piers Morgan:
holy hell. I mean, amazing experience. And you, like I said, you got emotional afterwards. But I, you know, I do remember very vividly I was born in 65 and I remember watching the original series of Star Trek, which I think, I think there were three series, weren’t there, of the original television show.

William Shatner:
Three years.

Piers Morgan:
Yeah, three years. And you know, it was, the mission statement was to boldly go where no man has gone before. And what I just remember being struck by, and particularly is, now I look back on it was how kind of multicultural the starship Enterprise was. You had Mr. Sulu, Chekhov, Uhuru. It was, this was a real visionary thing that you guys were putting on tv.

William Shatner:
It was, it was visionary television, but it reflected what the visionary was happening on Earth. That was the time when things were being built and the concept of going into space was new and exciting. This shot, this thing, this Artemis thing, I think is even more precarious than any of the others because there’s so many unknowns. These are ships that haven’t been flown that way before. There’s technology that hasn’t been used. There’s four inexperienced, trained but inexperienced astronauts. The trepidation on this thing that’s happening in our lifetime and in, in our present day is ranks with Shackleton and Scott and exploration of the South Pole, which I was at. And I sat on a ice cap that was a desert.

William Shatner:
There was nothing around. There was nothing. Imagine nothing around you.

Charlie Duke:
You’re forlorn.

William Shatner:
It’s one of the airport.

Piers Morgan:
We have a man sitting here still, Charlie Duke, who can not only imagine it, he was on the moon on his own.

William Shatner:
I know. So you need to explore that mind, that mindset. When he fell over, did he think, I’m going to die?

Piers Morgan:
Well, let’s ask him. And what, Let me ask him, Charlie, Like a turtle.

William Shatner:
Like a turtle on his back.

Piers Morgan:
Well, let me, let me ask the man himself. Unable to get up. We can ask him, Charlie, what did you feel when you fell over?

Charlie Duke:
Well, when I fell down, I said, I gotta get up. We practiced and practiced and practiced. We’d been in the zero G airplane, we’ve done that on Banner, I’ve fallen on my back, I’ve ditched this. And we had, we practiced all of that. And so we were prepared for these unusual eventualities. But it wasn’t like it was something that we hadn’t thought about.

William Shatner:
Yeah, but it’s one thing.

Charlie Duke:
How do we get up?

William Shatner:
It’s one thing.

Charlie Duke:
We pray for it.

William Shatner:
It’s one thing to practice and practice and practice. And somebody says, are you okay? Yeah, I’m okay. I’m practicing. It’s another thing to be forlorn on a planet that there’s no. There’s no way out. You’re. You’re fallen and you can’t get up. I mean, that’s just one of the things.

William Shatner:
20 seconds of fuel. You gotta get back up there and rendezvous. I mean, the things are extraordinary.

Piers Morgan:
I mean, on that point. I mean, it’s a great point. By. By Bill. I mean, Charlie, obviously, this.

Charlie Duke:
Wait a minute. We had.

Piers Morgan:
Well, the question I’m going to ask you is it obviously carries enormous risk, Obviously. And this Artemis 2 is the most powerful rocket that NASA have ever fired up. And it’s going the furthest distance in terms of the sort of dark side of the moon, literally that we’ve sent people in relation to the moon. So this carries with it enormous obvious jeopardy. How do you. When you were doing this, how do you deal with the potential of not coming back, of just something terrible going wrong?

Charlie Duke:
We never thought about it. I can’t believe that we were sitting on the.

William Shatner:
I can’t believe.

Charlie Duke:
Charlie. I can’t believe that. Okay, that was a.

William Shatner:
That was an astronaut.

Charlie Duke:
We never thought about not coming back. We had. We had. We had trained. If you got caught, if it exploded, it exploded. We had an out. An escape system on top of the spacecraft for liftoff. If the thing exploded.

Charlie Duke:
I mean, NASA had thought about all of those things. You just know that if it was going to happen in some way and the suit split open and you got hit by a meteorite, it just wasn’t your day. Yeah, but you were going to make it.

William Shatner:
You got to remember, the Challenger. The Challenger is before us. All those of us who haven’t trained and have your mindset, think Challenger and Artemis. And if Artemis fails, what a psychological blow that would be to the space program. I mean, there are so many complex things happening here. To those of us who don’t have your ability to deny the potential of death.

Charlie Duke:
Do you remember Apollo 1? Apollo 1 blew up on the pad in a training accident.

Bart Sibrel:
Fire.

Charlie Duke:
They were killed.

William Shatner:
I remember that.

Charlie Duke:
Because of some. All right, but it didn’t stop us.

Piers Morgan:
No.

Charlie Duke:
We said, we got to fix this thing. We got to fix it and do it right. And so it took a year in the spacecraft.

William Shatner:
I’m, I’m talking about your frame of mind. I mean, the Challenger set back psychologically, the space program for a long while. Well, if Artemis fails, what a psychological blow that is. If Artemis is successful, what a glorious thing for the space program and progress to the moon.

Charlie Duke:
Let me tell you, if it fails, we’re going to try again. We’re not going to stop. That is just the attitude of the space program, attitude of the United States of America and an attitude with the astronauts. We’re going to make it successful. It might not be right away, but we’re going to make it successful. It’s something that we’re committed to and we’re going to do it right. If it doesn’t work right, then we’re going to fix it, just like we did on Apollo. After Apollo 1 caught fire, just after a couple others that almost didn’t make it back.

Charlie Duke:
Apollo 13, mission control and the crews came through and made a spacecraft that was built for two guys for three days, made it last for three, four guys, for no, three guys for five days. So, I mean, there’s just, you know,

Piers Morgan:
Charlie, as you’re talking, as you’re talking, Charlie, all I can think is to Bill Shatner, you know, who would be 100% in agreement with everything Charlie is saying, Captain James T. Kirk. He would have exactly the same mindset. Because actually it’s the never, never stop dreaming, you know, boldly go where no one’s been before. It’s that that motivates people. I mean, Charlie, just to ask you, I mean, if we do get back on the moon, what advice would you give for the astronauts who make that next amazing.

Charlie Duke:
Drink a lot of water. Drink a lot of water. Well, if just they haven’t the first landings on the moon, whatever Artemis that is, in a couple of years, I hopefully have a chance to be around to give them some advice if they want it. And it’s just train, be prepared. That’s what we did over and over and over again. It was like doing it in your sleep. We had trained so much, we’d work with mission control, we’d work with the crew, we’d work with the rover. We trained and trained and trained.

Charlie Duke:
And so that is the motivation behind Apollo crews. And what Artemis is, those guys, they’re not just going out into the, into the ether with no training. They’re. And Charlie, out of interest, be well prepared.

Piers Morgan:
Out of interest, what do you feel about the conspiracy theorists who think that all the moon. The moon Landings were all invented. They never happen. They’re fake.

Charlie Duke:
Well, the moon landed. The evidence is overwhelming that we landed on the moon. You’re willfully ignorant if you don’t believe that we landed on the moon five, six times and the evidence is there. We left experiments packages. Every landing spike has been photographed by the Lunar Reconnaissance Orbiter. You can see the descent stage, you can see the experiments package. You can see the cars on the last three missions and. The experiments have been operating or they operated for five years and got tons of data.

Charlie Duke:
We’ve got 600 pounds of moon rocks. Where did they come from? They just didn’t know and we brought them.

William Shatner:
What’s the mindset of somebody who says to these brave individuals and all the taxpayers money that went to making that happen. What is the mindset of somebody who said, well, it didn’t really happen? I mean, that’s nihilistic. That’s like the denial of humanity. These crazy individuals shouldn’t have our attention. It’s. It’s absurd.

Piers Morgan:
Charlie, do you have any of the moon at home? Did you keep a bit?

Charlie Duke:
No. They gave me a moon rock after 40 years, but I had to give it away. So I gave it to my prep school down in Admiral Farragut Academy. Two moonwalkers graduated from there, me and Alan Shepard. Alan Shepard first and then me.

Piers Morgan:
That’s amazing.

William Shatner:
I have a watch with Moondust on it.

Piers Morgan:
Really fantastic design. I’ve got a Captain James T. Kirk baseball cap. That’s all I can contribute to this debate. Gentlemen, what a fascinating time talking to you all. I can think of looking at both of you, I know your ages, I don’t need to repeat them. But I hope I have half the vitality for life and curiosity and excitement about what we don’t know. As you two guys have.

Piers Morgan:
You are an inspiration to all of us mere 61 year olds. So thank you very much indeed to both of you.

William Shatner:
Thank you for having us. It’s great. It’s great to see you, Charlie.

Charlie Duke:
Bye bye. I hope I’m still around when we make that first landing. And that next to me too.

Piers Morgan:
That would be.

Charlie Duke:
That would be very much for having me.

William Shatner:
Charlie and I walk hand in hand to greet them.

Piers Morgan:
That would be brilliant, wouldn’t it? I would love that. Can I come too?

Charlie Duke:
Yeah, you may.

Piers Morgan:
Thank you.

Charlie Duke:
I told NASA I’m still feel. I am still at 90. I’m still physically qualified to go into space.

Piers Morgan:
Really?

Charlie Duke:
NASA says don’t call us, we’ll call you. So I’m not expecting a call.

Piers Morgan:
Great. To talk to you both. Thank you both very much indeed.

William Shatner:
Pleasure. Thank you. Pleasure to see you both.

Charlie Duke:
Been a pleasure. Thank you, Pierre.

Piers Morgan:
Thanks, Charlie. Take care. Piers Morgan Uncensored is proudly independent. The only boss around here is me. If you enjoy our show, we ask for only one simple thing. Hit subscribe on YouTube and follow Piers Morgan Uncensored on Spotify and Apple podcasts. And in return, we will continue our mission to inform, irritate and entertain, and we’ll do it all for free. Independent, Uncensored media has never been more critical and we couldn’t do it without you.

Dark Energy Is Dying: The Cosmological Crisis Nobody’s Telling You About

sabartigas — Mon, 20 Apr 2026 07:13:02 +0000

Dark Energy Is Dying: The Cosmological Crisis Nobody's Telling You About

Transcript

Brian Keating:
Some of the strongest evidence that the universe is accelerating doesn’t come from one telescope or a single experiment. It comes from a tiny ripple frozen into how galaxies cluster across the cosmos. Today, from the Royal Observatory in Edinburgh, we’re following that ripple with cosmologist Marcos Palheiro to see what it really says about dark energy. I’m Brian Keating, and this is an exclusive tour of the Royal Observatory Edinburgh with cosmologist Marcos Palheiro. We’ll go from this historic telescope, to cutting-edge simulations, to the DESI experiment, one of the most ambitious galaxy surveys ever built, to ask a simple question: is dark energy really constant, or is our entire cosmological model starting to crack? Long before silicon chips, the computers up here weren’t machines, they were people. Often they were women hired to comb through photographic plates measuring every faint smudge of light by hand. Their names rarely made it into papers, but their measurements are literally baked into the datasets we still build our modern cosmological models on. This building was designed as a cathedral for starlight.

Brian Keating:
The telescope sits on a massive pier that sinks into the hill, isolated from the floor so footsteps don’t shake the images. As our cities grew brighter, places like this became less useful for frontline observing, but the engineering mindset behind them is still the same one we still use today to measure the universe’s properties.

Marcos Pellejero:
This is a picture of the family of the Royal Astronomer before this place had no house anymore. Okay. For, for them. Um, uh, good. Uh, yep. And, and, and this is basically like the idea of like in the old times you will have looked through a telescope like this one, but nowadays, uh, in the, here in the lab, they are building things like this, like these robotic arms to basically place fibers. And get some of the light and decompose it and study.

Brian Keating:
This is not far from the Simons Observatory. That’s in the northeast.

Marcos Pellejero:
Okay. And just one more question. Sorry, I know that you have been here for quite a long time. Do you see any weird wall in this room? Yes. Which one? Why do you think it’s weird? There are two reasons.

Brian Keating:
It has a picture.

Marcos Pellejero:
Well, it has a picture. Yes, this one is weird, but this is a door, right? This is not a wall. It’s made out of bricks. Yes, exactly. So welcome to the dome. So do you see something weird in this dome with respect to other domes that you might have seen? It’s not a dome exactly. It’s like a cylinder. And this relates to what I was saying before, that they were not trying to do a functional building.

Marcos Pellejero:
They were trying to do a beautiful building, right? And then they were thinking on building something that was like a cathedral for science. Okay. So the idea, and a cathedral needs towers, right? So this is again, like, this is quite old. And when I was telling you what will we find at the end of that weird wall, the reason is this thing. So this square here goes all the way down and into the hill. And it is separated from the rest of the building because you need to do very precise observations. And if this is connected to the rest of the building, then if the building moves, this moves. And you want to avoid that.

Marcos Pellejero:
So basically what you do is you create a pyramid that goes, that takes its, puts its roots to the, like, deep into the mountain, and it moves at the least you can, right? This specific telescope is from, was built in Newcastle in 19, it’s written here, in 1928. Okay, so it’s not as old as the building. This would not be the first telescope that was here, but it’s quite old.

Brian Keating:
And what’s the diameter, Marco?

Marcos Pellejero:
So this was, I think this is a 40 centimeters one. This is the primary mirror. 40 centimeters, I don’t know in inches. I have no idea.

Brian Keating:
From that, it’s less than, say, 18 inches?

Marcos Pellejero:
18 inches, yeah. Okay, that’s good. If you say so. So actually, so I mean, I guess you know quite a lot about telescopes already. The primary mirror is not here anymore. Okay. The secondary mirror, which is up there, you can still see it. That’s there.

Marcos Pellejero:
And the detector is completely missing, right? This is empty. Now, what’s the reason for this? Well, it’s the same, basically the same reason why the original observatory was completely useless by the mid-19th century, which is the cities in Europe started being lighted with electric lights and not candles as had happened before. So no fire anymore. Okay. So they basically, they were like very, very bright. And if you have an observatory close to the city center, then you couldn’t, you could see nothing, right, of the night sky. So they, they built this one far away from the city, but the city grew, right? So at some point, the light pollution of the city made this observatory useless. Not useless, but in comparison to other observatories, basically useless.

Marcos Pellejero:
Okay. So basically for the last, yeah, no, like for the, for the, now it’s not anymore, but since 1975 or so, this was used for checking the stability of detectors. So they were building detectors in the lab in the other building. They will put them here and then they will shake them basically to see if there were any loose pieces that they had forgotten or something like that. Okay. Yeah. So that’s basically how this worked, but you have to think about like an astronomer in 1895. Okay.

Marcos Pellejero:
Basically coming here with a candle, right? And then do you want me to show you how they will open the dome? Yeah. It’s very cool because it’s just with ropes and there’s no technology, no weird technology happening here. Come with me, let me show you. So do you see the wheels? The wheels are all around the dome. So those would be used to actually rotate the dome. Okay. And then you would have to open this and it is very heavy. It is as simple as this, even though it’s a bit heavy.

Marcos Pellejero:
Yes. But that’s the way one would open the dome. The dome. Yeah, yeah. Very cool, right? It’s raining. Now, what does he want to open it like up there or straight up? Yeah. So the thing is that there’s two, right? So one is this one. The other one is that one.

Marcos Pellejero:
That one will go. Do you see, do you see all of, all of like the levels there? And so you will have to use those. So basically what I was telling you is that the moment, okay, so these finders, okay, so the small telescopes. The ones that basically tell you where, like, in which way you’re looking at, right, are very high, right? So in the moment you tilt this, they are even higher. So to reach them, you will have to go up a ladder, okay? And the Royal Astronomer will have to go up a ladder. And he couldn’t have his Royal Astronomer ass going up a ladder because he was the Royal Astronomer, right? So he asked for this to be built. Okay. Which is an electric chair, but the good kind of electric chair.

Marcos Pellejero:
Okay. So the one in which you will sit down and then you will press the button and then this will elevate you. Okay. And then you can do observations without having to be up the ladder and so on, which is very cool.

Brian Keating:
If you just threw galaxies into the universe at random, you’d get a smooth fog of matter. But when you actually map them, you see a faint preference, a ring, a scale of about 150 megaparsecs left over from sound waves in the early universe. But these patterns are called baryon acoustic oscillations, and they behave like a cosmic ruler for measuring how fast the universe has been expanding.

Brian Keating:
So first of all, what’s a baryon acoustic oscillation, Marco?

Marcos Pellejero:
Well, acoustic oscillations, well, First of all, the way I like to think about them is how galaxies are distributed in the universe. Okay. Because they don’t follow just random patterns. They have like very distinctive patterns. And the first one that catches your eye is basically this cosmic web that you, that you know about. It’s a secondary answer, which is like, yes, closer, but also when you are at a distance of around 150 megaparsecs, then you find again a greater likelihood of finding a galaxy. When you have this kind of patterns, it’s usually the reason why they appear is because you have some kind of border or frontier.

Brian Keating:
Turning BAO into numbers isn’t just about counting galaxies. You have to know what the universe should look like if your dark energy theory is right. That means running huge n-body simulations, and Marcus works on emulators that use neural networks to mimic those simulations in a fraction of the time. So he can explore many more possible universes than ever before.

Marcos Pellejero:
So one of the, okay, one of the main problems to study, um, the distribution of galaxies nowadays is that the gravity formation is very nonlinear. And by this I mean that it comes with loads of complications to solve the equations. So the only analytical solutions that we have are those for the linear, uh, theories, okay, in the linear regime, which are like the regime of the very big scales.

Brian Keating:
In our simplest model, dark energy is just a constant, a fixed energy of the vacuum that never changes. But Desi is starting to whisper something awkward.

Brian Keating:
Is it true, Kyle, that as our colleagues, my friends and colleagues, Suzanne Staggs, Mark Devlin, Lyman Page, have demonstrated, David Spergel, very clearly that the lambda is unavoidable, or, you know, some version of dark energy is unavoidable using the CMB alone?

Brian Keating:
I think that’s true, right?

Brian Keating:
Then is it also Is it true from BAO alone you can derive the imperative of dark energy’s existence?

Kyle Lawson:
Yeah, that is definitely true for BAO alone as well. Our models, if we were to throw out any version of dark energy, would basically be impossible to describe the measurements we see over the redshift range we make the measurements. We see a preference for something like 70% of the current energy contents being dark energy, and that’s hard to get around.

Brian Keating:
The data seem more comfortable if dark energy evolves over time.. And when you combine that with the fact that cosmology wants neutrinos to be almost massless while particle physics insists that they aren’t, you get a serious tension in our best theory of the cosmos.

Marcos Pellejero:
Theoretically, it makes a lot of sense that it’s a constant, right? Because if you think of it as the energy of the vacuum, then the more volume there is, the more vacuum there is, it all compensates, and then you get a constant. So makes a lot of sense. But the latest results from DESI, and being part of the DESI collaboration, I, I trust them. Yeah. Because I know that they have very, very, you know, very picky in how to show the results and so on. That’s— those seems to show that there’s a strong— so yeah, but there’s like strong evidences from DESI to actually departure of this. And I think like the most— okay, to me, the most interesting part is that cosmology has very few predictions that they can make. That can be checked with other kinds of areas in physics, for example, particle physics.

Marcos Pellejero:
And there’s one prediction that cosmology has, which is that we can measure the mass of the neutrinos. Okay. And if you go to the latest results from, from BAO and DESI, and you combine them with other supernovae results and so on, you find out that there’s strong evidence to actually having massless neutrinos in the universe. But particle physics experiments tell you that they cannot be massless., right? They have to have a mass. So there’s a tension here. There’s a paradox here. Like there’s a misunderstanding between these two areas of science and the only— exactly, inconsistency. And the only way of reconciling those two seems to be opening our framework to new ideas on what dark energy could be.

Marcos Pellejero:
And right now it seems that that’s the most compelling way of moving forward. Ah, right. Because there are other ways in which you will actually lose these constraints, but none of them actually move your measurements. They just make them less accurate. But this one actually moves your measurements in the right direction. This one being the dark energy. The dark energy, exactly. So having a dark energy that is not really constant in time but evolves.

Brian Keating:
The Hubble tension, the fact that different models measuring the expansion rate disagree, might end up being systematic error, or it might be a sign of new physics. The only way to know for sure is to redo the key experiments with ever more careful data. That’s part of what surveys like DES and the upcoming LSST are designed to do.

Brian Keating:
So tell me about the Hubble tension. What are the— because you found there was also some discrepancy depending on what values of Hubble.

Marcos Pellejero:
Yeah, so about the Hubble tension, I don’t have a good answer on like what could be happening with the Hubble tension. Everything seems to So that it might be due to systematics, but again, I’m not an expert.

Brian Keating:
Do we need more data for both things? Do we need more?

Marcos Pellejero:
I think we need more consistent data. Maybe that’s the thing, right? Maybe we have, we need to redo some of the things that we have done already. And I know that this is not very attractive and no one really wants to do this, right? Yeah. But sometimes you have to repeat some of the experiments. And this is being done by the DES collaboration, for example, they have like their own set of supernovae. And also the LSST is going to have their own set of supernovae. And again, I know that this is not like very attractive in some way, but it’s the only way forward.

Brian Keating:
To test any model of dark energy, you need to know what the universe’s large-scale structure should look like if your model is correct. That’s what so-called N-body simulations do. They throw billions of particles into an expanding universe and let gravity sculpt the cosmic web, and then we compare it to what we actually see.

Brian Keating:
Explain for a layperson, what is an N-body simulation? How do you actually do it? Do you have a laptop, iPhone?

Marcos Pellejero:
How do you do it? Sure, sure. So they’re usually done in supercomputers, right? The big ones, they’re done in supercomputers. An N-body simulation is basically just a simulation of a very homogeneous universe that evolves with time according to a mixture between Newton’s laws and general relativity laws. Okay. So basically Newton’s laws. On an expanding universe, and it, it evolves only through gravity. Okay. And it tells you what is going to be the gravitational potential.

Marcos Pellejero:
So what is going to be the structures that you expect to see in the late universe? And it solves the equations exactly. Okay. But for a given set of initial conditions, that’s, that’s the—

Brian Keating:
James Clerk Maxwell, Peter Higgs, and the astronomers who built this place were all chasing different versions of the same question. What is the universe really made of and how does it really behave? Marcos does it with simulations, surveys, and machine learning instead of brass and glass, but the mindset is still the same. Take a vague intuition and carve it into something the universe can’t ignore.

Brian Keating:
So what do we need more of? More galaxies, more observations, more simulations, more CPU, GPU?

Marcos Pellejero:
What do we need more of? Well, we need more of everything. I guess, Imani, if you ask me, more of everything. But so simulations, I think we have, I mean, like we have plenty, of course, like the bigger they are, the better, but we have techniques to actually do these embodied simulations quick enough that I think that’s not a bottleneck anymore. It used to be, but not anymore, right? But we also need like machine learning techniques and artificial intelligence techniques to actually use them in the smartest way for that, right? And for that, we need synergies between the computing science departments and the cosmology department. Bottlenecks that we have there in simulations are more related to hydrodynamic simulations, which are the simulations in which it’s not only gravity evolving, it’s gravity plus the pressure from galaxies, explosions of plasma, exactly. So, so star formation and so on, right? Those are very far from being converged. So if you run two similar approaches, the outcomes will be completely, completely contradictory. Okay.

Marcos Pellejero:
So they will, they will basically predict opposite effects, which is, which is something that is very annoying, right? Yeah, exactly. Because then you don’t know in which universe you’re living.

Brian Keating:
Right. So this observatory, uh, there’s the Higgs Center that we’re at right now. Uh, did you meet Peter Higgs?

Marcos Pellejero:
Did you know Peter Higgs? No, I didn’t. I was, I moved here, uh, not very, okay, so basically one year before he died and, and well, he, he was not coming anymore, right?

Brian Keating:
To work. The quick history here, was Maxwell ever here?

Marcos Pellejero:
Was there?

Brian Keating:
Right.

Marcos Pellejero:
Maxwell is one of my like heroes. In history because it doesn’t seem that he was also like a very good scientist. Apparently he was also like a nice person.

James Clerk Maxwell:
Ah, Edinburgh, the city where I first chased light through the mist. At 14, I was already puzzling over the mathematics of curves and colors, scribbling equations. Didn’t pass every exam, mind you. Cambridge nearly said no. But curiosity is a stubborn thing. It carried me from these cobbled streets to the laws that would bind electricity and magnetism forever. Funny, isn’t it? As my friend Professor Brian Keating always says, ABC, always be curious.

Marcos Pellejero:
So he was, he was born here, and you can actually visit the house where he was born. He wanted to come here, but at the time he was, he had not made his most brilliant contributions to physics. And he was actually not accepted in the university. A friend of his was accepted. And at the very beginning I thought like, oh, who would say no to Maxwell, right? But then you realize that they were actually very good friends since they were kids. And they were part of like this club in which they solved mathematical problems together and so on. And then you think like, oh no, actually, I don’t know, probably Maxwell was happy that his friend got a position.

Brian Keating:
And he went on to get a raise. So how does it feel to work in a place like this with all this history, castles, copper, and then you’re doing some of the most modern large-scale simulation ever done, the tundra, and the most mysterious force in the universe, dark energy.

Marcos Pellejero:
I know, I know. I don’t see any big leap in that, uh, in, in, in that sense, right? So in, in, in the end, like, I mean, it, it, it sounds very old when you, when, when you tell these stories and, and, and so on, but they were, they were dealing with the same kind of problem. They, how to make a bigger building, in my case, how to make a bigger simulation. Yeah, exactly. Like bigger telescope, how to, I don’t know, like in the end it’s a very similar mind framework and it’s like a problem solving framework, right? When you have a problem and you want to find a solution, it’s like the brain works in very similar ways. It’s not like music, for example, right? In music it’s different. In music you don’t have a very well-defined problem, right? You just have like an intuition on what could work and what couldn’t, right? Um, and, uh, but yeah, but science is a bit like a mixture of those two, right? Like problem solving and a little bit of inspiration. And, and when you live in a place where there’s so many artistic stuff like around you, then this, you, you, you get, you, you find out that science and arts are not that different and that you need inspiration from both of them, right? Which is, which is the regular cool thing.

Marcos Pellejero:
That’s beautiful.

Brian Keating:
Thank you. From this hilltop in Edinburgh to the edge of the observable universe, baryon acoustic oscillations and DESI are forcing us to ask whether dark energy is really constant or whether our entire cosmological model is starting to bend. A huge thanks to Marcos and the Royal Observatory of Edinburgh for opening their doors. If you want to go deeper into DESI and dark energy, check out my conversations with DESI past spokesperson Kyle Lawson and Nobel laureate Adam Riess. They’re linked right here. See you next time on Into the Impossible. And don’t forget to like, comment, and subscribe.

Are the Van Allen Belts Deadly? Debunking the Biggest Moon Landing Hoax!

sabartigas — Mon, 20 Apr 2026 07:03:48 +0000

Are the Van Allen Belts Deadly? Debunking the Biggest Moon Landing Hoax!

Transcript

Brian Keating:
You know, recently came up that Joe Rogan was on my friend Jesse Michaels podcast.

James Altucher:
Wait, Joe Rogan was on Jesse Michael around?

James Altucher:
Live for 30 minutes podcast. And he’s been on my podcast a bunch of times. We know him very well. I didn’t know Joe Rogan was on Jesse’s podcast.

Brian Keating:
Yeah, he almost never goes. I mean, I’ve only seen him on Lex Friedman’s podcast. Jesse built this huge set. It looks like the inside of a. A kid’s bedroom on a spaceship with buttons and knobs and dials and it looks like they’re flying on a spaceship. Joe is the guest. Jesse was interviewing him. It’s gotten a million plus views in just the past four or five days.

Brian Keating:
But this, you know, it’s kind of the last straw. Joe Rogan going all in on the moon landing was fake. With most of the episodes about this disclosure that aliens are real.

Brian Keating:
Vague and weird and kind of, you know, opaque. It was vivid, it was very strange. And there was these very slender, tall, human like things that were talking to me. They weren’t gray, they were kind of like pinkish like us. They were, you know, like Caucasian looking creatures.

Brian Keating:
And, you know, the issue is that you like to see your friends do well, but then they, they have big platforms and they get lots of attention, they get big guests. And then they kind of spread this nonsense that comes from people like Bart Sibrel. I mean, if you look him up on Wikipedia, his entry is, you know, is conspiracy theorist. That’s what he’s known for. And so I thought, you know, the best way to kind of take on these guys. And by the way, he went on Joe Rogan before I did.

Brian Keating:
It’s fake.

Narrator:
So this thing is kind of just waving on its own. No one’s even touching it. And it looks like it’s waving in a breeze. It’s so it stops moving and then it starts moving again. Now again, there’s one footage that shows.

bret weinstein:
It even more so than that. Like an astronaut walking past it, creating the breeze. And then the flag blows without him touching it.

Narrator:
Yeah, I’d like to see that. So how much further does this go, Jamie?

Brian Keating:
Four minute video. Three minute video.

Narrator:
So scoot ahead. I think this is actually the one.

Brian Keating:
And then when I went on it, you know, I talked a lot about the moon and so forth, but then apparently there was another event. Forget exactly what it was, but maybe Bart went on again and he was talking all this nonsense. And I just wrote to Joe Rogan that I’d like to debate this guy Bart, because I think he’s discredits NASA America, you know, and just completely false. And his allegations are so simplistic and easy to refute that it’d be great to have a debate. So Joe asked Bart, apparently, to debate me. And Bart said, no, he doesn’t want to debate me because he claimed that I, as a scientist and not an astronaut, are really victims of NASA’s perpetrating this hoax. So he said this on Danny Jones’s podcast about me and just made all these blunders and fact and math and all sorts of physics errors and just logical errors. And so I’ve made a couple videos about him just because he is this, as I said, the super spreader who not only kind of discredits NASA, but as I said, you know, I’m a very patriotic person.

Brian Keating:
And to discredit the greatest accomplishment of humankind, which includes America, it’s a pretty big deal. Especially since I’ve worked for NASA in different capacities, including capacities that benefit people like Bard and you and anybody who’s ever gotten on a plane. NASA didn’t just send people to the moon and launch the Hubble Space Telescope. They work on aeronautics. So it has to do with aviation safety research into climate and hurricanes. They do a tremendous amount of research as well as scientific research, but even the astronomical can be outweighed by their contributions to the safety of every human being who’s ever gotten on a plane in America. And so that’s really kind of the disrespect that I see towards America, towards NASA that he cultivates. And then Joe just sucks it up because it gets, you know, attention to Joe.

Brian Keating:
And then this guy won’t debate me on Joe Rogan’s podcast. He just debated on this guy, Danny Jones’s podcast, a real astronaut who walked on the moon named Charlie Duke. Okay, sorry.

James Altucher:
Earth slowing you down. Okay, so the total distance of the moon is about 3,000 miles an hour. Seven times 70. That’s 210, 000 miles.

Brian Keating:
Okay, okay, so when.

James Altucher:
Well, so when you go through the Van Allen Bells, you’re going so fast, it’s just. You’re through.

Brian Keating:
How fast are you traveling? When you guys were going through the.

James Altucher:
Van Allen Bells, you know, escape velocity is about.

bret weinstein:
I thought you said it was three.

Brian Keating:
Let him talk. He said he was at 3, 000 when they were halfway. So he did confront him. But unfortunately, Charlie Duke is 90 years old. He’s never been on a podcast. He didn’t know, like, basic so it just made a little bit, put more questions that gave people more, you know, belief. And this guy barred conspiracy nonsense. So I came to the, you know, to the place of record to set it straight.

Brian Keating:
And I’ll release this on my channel. Maybe I’ll put in some more of the mathematics of it. And I think the best way to do that is actually go through Joe Rogan’s podcast with Jesse Michaels because they’re bringing up what they think is the strongest evidence that Bart has presented to them. So, you know, Joe is, does I say he’s never been afraid of a little hard work, so he’ll do some research. But in general, he’s just believe whatever is most controversial. And he’ll tend to not believe because Covid, you know, because Fauci and Collins lied to the American public, you know, in many ways, and, and tried to discredit people like my good friend Jay Bhattacharya, who I met at this Peter Thiel conference, who’s now the director of the National Institutes of health is Dr. Jay Bhattacharya, who is a professor of medicine, economics and health research policy at Stanford University and the director of Stanford’s center for Demography and Economics of Health and Aging. You really couldn’t design better, you know, Jay, if, if, if they had like a lab where they could design things, you know, for gain of function purposes because he, you know, tried to destroy him personally and professionally, that we can never trust any scientist again.

Brian Keating:
And because, you know, people like Eric Weinstein and others, you know, and Jesse argue that, oh, physics has stagnated and string theory is strangled physics. Now it’s like you can’t trust science whatsoever. So I’d like to go through what, what Joe claims are these like, incredibly dispositive, you know, facts about, about the moon landings that prove that they’re not real. If you don’t mind.

James Altucher:
Yeah, let’s, let’s do it. And by the way, part of this was inspired by Candace Owens going all in on Barth’s theories. And you know, my bone to pick with Matt Walsh.

Candace Owens:
We have a long running beef on the topic of NASA and moon landings because he thinks they happened. And listen, when the guys did it, it was, it was fake and gay. I’m sorry, Matt.

Brian Keating:
I’ve seen a few videos on Buzz Aldrin talking about how it didn’t happen. He says it all the time now. Kim Kardashian. So the reason I made the most recent video I made was, you know, inviting Kim Kardashian to Talk and to, you know, to educate her. You know, she lives here in California, not far from San Diego. I’m sure we could have a nice conversation about it. But she, you know, she didn’t respond, I don’t think, you know, again, she really.

James Altucher:
Well, we’ll get it.

Brian Keating:
But she actually had, you know, the NASA administrator, the acting NASA administrator did respond to her and, you know, got a lot of attention. I thought that was good. But anyway, the first thing that, that’s kind of, you know, a strike against the logical or reasoning skills that Jesse and Joe kind of go into is, you know, they talk about the press conference that the Apollo astronauts, you know, Aldrin, Armstrong and Collins had. Afterwards, you know, several days after landing, they’re inside this trailer, this bioprotective zone, and Joe’s saying that they look suspicious. So that’s like the first thing that they bring up is this press conference that are, like completely tired, they’ve come back. Nobody disputes, even Bart doesn’t dispute that they were somewhere off the planet Earth. Like, Bart believes that, for example, the astronauts left the Earth’s surface. He just doesn’t believe they got anywhere near the moon.

Brian Keating:
I’ll explain his slam dunk evidence, which is anything but in just a minute that he claims is the reason that they could not possibly do it. But the first piece of evidence is suggesting in no way that they didn’t at least go into space. Do you understand? Like, no one’s disputing even Bart, that they left the Earth’s surface.

James Altucher:
Okay, so for instance, you know, John Glenn, he thinks orbited the Earth.

Narrator:
Yes, 62, 49 years ago today, the day a rocket lifted both an American astronaut and the American spirit. That was the day John Glenn was hurtled into orbit around the Earth.

Brian Keating:
And he believes that the NASA, the Apollo 11, Armstrong, Neil Armstrong orbited the Earth and they were gone for a week because it took, you know, takes about two and a half, three days to get to the moon. Two and a half, three days to get back. And they were on the surface of the moon for like two or three hours. So it was almost a week or about a full week, you know, July 20, 1969, very famously. And so nobody disputes that they were in orbit. I claim there’s abundant evidence they went, they lived, they went on the moon, they traveled back and forth. There’s no doubt in my mind that that actually occurred. But let’s just give them the benefit of the doubt, Joe Rogan, that they actually didn’t go.

Brian Keating:
And the proof is they look Tired. They were speaking in sort of a script or something like that. But he wouldn’t dispute the fact, even Joe Rogan, that they were in orbit. Like, in other words, I don’t care where you were. You’ve seen the capsules. It’s smaller than this, you know, like two or three times the size of this office chair that I’m sitting on. So nobody could dispute that somebody would have the right to be three people crammed into a tiny little capsule for three to seven days, that they would be completely shy, introverted, you know, maybe disgruntled. They were also quarantined for, I think it was close to three weeks because they didn’t know if they’d have some moon germs.

Brian Keating:
Again, why would you quarantine people if they were just in low Earth orbit? And why would you do it for three weeks? Maybe you do it for a day. But somebody had to tell NASA, according to them, that they had to quarantine them for three weeks or else nobody would believe the ruse that they didn’t land on the moon, that it was all fake.

James Altucher:
So, yeah, that was my first instinct, is that, of course you quarantine because that makes more credibility that, oh, why would you quarantine if they weren’t on the moon?

Brian Keating:
Yeah, but why for three weeks? Why not for a day or two days? Like, no, it’s, oh, you only quarantine for two. For 48 hours. Not 30, 30, you know, not 72 hours. So that means that you didn’t go. It’s total. That to me is complete bogus, you know, reasoning. They, they were quarantined, they were in space. And so saying their, their character, the way that they acted was not really.

Brian Keating:
Can’t be used to prove as. I mean, it was the first kind of piece of evidence that Joe talks about, like, oh, look how suspicious it was. They look like they’re hiding something. Okay, so that’s like Joe Rogan, amateur psychologist, is like, now assessing the veracity of, you know, $100 billion project, you know, in today’s dollars. I think it’s very hard for Joe Rogan to read the vibes of this person and do this meta analysis of the psychology of astronauts, you know, who certainly went into space, even I think Joe would admit that. But, you know, when you compare anybody who comes back from space, even the most recent NASA astronauts that SpaceX rescued last year, I mean, they weren’t like, going to a rave after they landed. And so there’s just this, like, the mode that I think they’re trying to operate in is let’s sow doubt in the moon landing. For what reason? I don’t know, except that, you know, Joe takes on this countercultural, anti authoritarian.

Brian Keating:
You know, he’s a comedian. You know, his job is to satire and poke fun at institutions, but also hold them accountable. Like, he’s, you know, he is the most dominant force in media. I mean, he gets a lot more attention than cnn. And, you know, he’s the number one podcast in the world. So he is, you know, playing a role in journalism. He has interviewed, you know, the president of the United States and offered to interview the vice president of the former administration. So anyway, he has this huge role.

Brian Keating:
Yeah, I’ve been on the show. Yeah. And.

James Altucher:
But let me ask in terms of this, in terms of their evidence, they’re saying that. Are you presenting it? I haven’t seen Joe’s conversation with Bart. I feel like you’re presenting it. There must be something else, because that does seem like very weak evidence.

Brian Keating:
So this is not. I can skip ahead to just like, the main thrust of what Bart Sibro argues is the reason. I’ll do that in one second. But what I’m doing now is assessing Joe Rogan’s most recent appearance on Jesse Michael’s podcast.

Narrator:
Clearly, this can’t be the only planet that has life on it. Like, that doesn’t even make any sense. And then, you know, going to school and you learned out how many hundreds of billions of galaxies there are, you like, okay, and how many hundreds of billions of stars are on those galaxies and how many planets there must be, like, for sure.

Brian Keating:
So I. It’s almost irrelevant with Bart thinks, because Joe will just parrot the, you know, pick and choose what Bart said that fits his narrative and try to confirm it. You know, to give him credit, he did try to arrange this debate with me and Bart on his show.

bret weinstein:
I’m really not interested in debating anybody. I would do it as a favor to him unless Lex Friedman asked me to do it, and I agreed to do it with him. But that, to me, is like debating. If the sky is blue, the sky’s blue. We don’t need to debate it. Plus, these people he’s putting up, or Lex would put up, they’re the victims. Well, not the perpetrators, you understand?

Brian Keating:
And Bart refused. Bart was. They’re too scared to debate me. He made up some pretext that I’m a victim of NASA’s brainwashing, which is preposterous. I have many different pieces of evidence against it. So let me just Say the main piece of evidence that Bart claims is the reason that they didn’t go, which is completely illogical. And I think you’ll understand why it’s illogical. He claims that there’s something called the Van Allen radiation.

Brian Keating:
And this is what everybody says, from Kim Kardashian to Candace Owens. She called it like the firmament.

Candace Owens:
And you’re like somebody who’s like, it had to have happened, the moon landing. What you can do is look up. I’m calling this the firmament, but it’s the. What is the belt that the.

Brian Keating:
She’s just such a knucklehead. But anyway, let’s get back to it. So it’s called the Van Allen radiation belt. It’s not the asteroid bell, as you know, Candace has said, or whatever. It’s a region of somewhat moderate to low intensity radiation that is surrounding the Earth. And it’s organized primarily in bands that are more concentrated, like where you’ve seen maybe the aurora borealis, you’ve seen the northern lights. These are phenomena that result from the interaction of charged particles from the sun, the solar wind and space, other sources of space radiation that are charged particles. So this is where the physics starts to come in.

Brian Keating:
A charged particle, like an electron or a proton or an alpha particle, a helium nucleus moving in a magnetic field will experience a force called the Lorentz force. Barthes couldn’t do these calculations to save his life. But we do these all the time. They’re incredibly important in physics. There’s aspects of them that can be treated using quantum mechanics and relativity that I. Again, no way Bert has ever looked into this. He’s looking at. And they were discovered by this.

Brian Keating:
NASA funded. This is important. A NASA funded research study in the 1950s by a scientist named Van Allen. His last name was Van Allen. And so he discovered. So NASA discovered this, this book. Let’s assume it’s potentially dangerous. I mean, they do.

Brian Keating:
And it has some slight amount of danger associated with it, as all things do when you’re off the surface of the Earth. The question is, could this prevent them from going to the moon? So Bart assumes that this is this, this lethal layer of space radiation which will essentially, according to him, instantaneously kill human beings if they’re exposed to it, which is complete nonsense. Even people at Hiroshima exposed to massive, you know, much more, thousands of times the lethal dose didn’t die instantly unless they were in the actual blast zone a few kilometers away from. From the actual blast zone. They lived for hours. And it was probably agonizing, but they didn’t die. Nobody dies instantly. And that’s important because the Van Allen belts have a certain thickness to them.

Brian Keating:
They have what’s called a density profile. All of this Bart ignores. He just assumes that, like, it’s a solid layer, like a lead shield, but it’s full of, like, uranium, and if you touch it, you’ll die, you’ll fry, your old DNA will be destroyed and you’ll die instantly.

James Altucher:
And so why does he say that? Like, maybe this is even a step back? Like, why is he doing this? Is it just for media attention?

Brian Keating:
He hates NASA. No, he hates NASA. He apparently says that he was a true believer and an evangelist for NASA. I don’t know when, because the only time he’s ever been in the public eye was when he like, got punched out by, by Buzz Aldrin and would go to, like, astronauts homes and scream at them and their widows and do like. He’s never. I can’t find any footage of him. Maybe it exists, but I haven’t personally been able to find any footage, you know, earnestly trumpeting, say, before and then afterwards when he becomes an apostate and an enemy of nas. I’ve never seen any evidence of him in the before times when he was an evangelist.

Brian Keating:
I’ve only seen where he’s an apostate, where he hates NASA.

James Altucher:
I mean, what’s his background? Like, what, what. Why does.

Brian Keating:
He is a filmmaker.

James Altucher:
So he’s a filmmaker. But because of this, though, like, he makes films about this.

Brian Keating:
Yeah, I mean, look it up. Yeah, we could look up what else he did. I mean, he’s irrelevant, you know, what, what he did before that. I mean, he makes a lot of. Yeah, he appears on podcasts, he gets a lot of attention, he’s done some documentaries, but he’s kind of a gadfly, you know, he likes to, he likes to poke at NASA. And again, I, I’m still open, willing, I treat him respectfully if he came on my show or if he came on Joe Rogan show or Lex Friedman, also Lex Friedman, I think, asked him to go on his podcast and debate me. And he just, for some reason he doesn’t want to. His main piece of.

Brian Keating:
He’s got a couple pieces of main evidence, and some of that Joe Rogan will parrot back. But most of it is reliant on what he claims are the physical and biophysical limitations to human traversing the distance between the moon and the Earth.

James Altucher:
And what’s his evidence that the Van Allen radiation belt would be so radioactive that it would Kill, you know, rockets going to the moon, and any rockets going into space have heat shields so they can come back in. They’re to some extent impervious to a high amount of radiation, as we know. So what’s evidence that this radiation belt is so intense that it would kill anybody crossing through it?

Brian Keating:
So his argument is that these papers from NASA, he finds, like, one paper, which he claims from NASA that speaks about the level of radiation. But he’s a selective synthesis. He’s only reading to get the aspects that he claims are complete slam dunks that you couldn’t even set one inch into these Van Allen radiation belts. And in reality, you know, when you think about the atmosphere, James, it’s not like a solid layer of constant density, just our Earth’s atmosphere, okay? It has an exponential decay. The amount of oxygen here at the surface of the Earth in Florida and San Diego and Atlanta is essentially twice as much oxygen as I feel when I go to 18,000ft in Chile to go to the Simons Observatory. That level of, of atmospheric pressure is about half the atmosphere. That’s why we were oxygen. So.

Brian Keating:
But if you go between 18,000ft and 36,000ft, it goes basically to zero. Even though you’ve doubled it, it doesn’t go linearly. It goes exponentially, declines, but it never goes to zero. There’s no such thing as, like, zero atmosphere. There’s particles of the Earth’s atmosphere that extend tens of thousands of miles into space. And certainly things like the Earth’s magnetic field extend into space, but they typically have either a 1 over r squared falloff or they have an exponentially decaying fall off. So, too, do these radiation belts. They truly exist.

Brian Keating:
Anyone who’s ever seen Aurora, they know that they exist. Now, what he’ll claim is that there’s a temperature of these things and that they would fry and melt aluminum, which the spaceships are made of. And then to defeat that, you’d have to make the spaceship so heavy that it could never get off the launch pad. And the proof there is that we haven’t gone back to the moon. He said everything’s gotten easier since the 1960s. Computers have gotten smaller, Cars have gotten faster and better. Everything’s gotten easier since the 1960s. So the proof that we haven’t gone back is proof that we never went in the first place.

Brian Keating:
Because things get easier over time, right, James? It’s. It’s certainly logical if we couldn’t go now. And he claims people like Elon Musk say we can’t go now. But for some reason, Elon’s building a spacecraft to go to Mars. So apparently he thinks he’s smarter than Elon Musk, as does Candace Owens, which is okay.

James Altucher:
But let’s deal with this point, though.

Brian Keating:
That’s fine.

James Altucher:
I think it is so insane to not believe that the moon landing happened. I’m, you know, I don’t think it’s insane.

Brian Keating:
I don’t think he’s insane. No, I’m not saying.

James Altucher:
I’m not saying insane, but I think the idea that I almost question his motives, that’s what I’m saying, is that.

Brian Keating:
I don’t think any motives are clear. He likes attention. He gets a lot of attention from the most famous podcast and media outlet in the world. So he gets that. He goes on, he gets to confront people. I think he feels like he’s suffering from the Stockholm syndrome or something. Like he loved NASA so much, he was of an evangelist. Again, I haven’t found it.

Brian Keating:
Maybe it exists. Maybe Barr can send it to me. Somebody can send it to me, but I haven’t found any. Pro NASA from the before times and then anti NASA, so. So the Van Allen radiation belts, he claims because of that there was no way to go in the 1950s. NASA knew it and so they would never put their astronauts in danger. But he’s also saying that NASA lies all the time, is a corrupt and malevolent organization. Because we haven’t gone back, which is true.

Brian Keating:
We have not gone back since 1973. We went in space many, many other times. We lived in space for hundreds. You know, I’ve talked to Chris Hanfield. You know, he lived on the space station for six months. People stay in space all the time. And the amount of time that you go through the radiation belt to get to the moon, assuming it was. Even if it was a constant thickness and it was the most high dose you could possibly go through, you would still be totally fine.

Brian Keating:
You would be like getting like 100 chest x rays in a year, which is not great. You wouldn’t. But there’s no way you would die the next day. Do you think you’d be able to go to your. I mean, my dentist, the medical tech doesn’t have a bachelor’s degree, and she fires up the X ray machine at my skull. Do you think they would allow her to do that if there was a 1 in 100 chance that I might die from that? Of course not, but.

James Altucher:
Okay, so you’re saying this because you know what the Van Allen radiation.

Brian Keating:
I’m saying assuming the worst Case of the Man Allen Belt, which is in no way massa new. It’s much more dense at the poles. That’s why it’s called the Aurora Borealis. Because boreal means north north Pole. That’s why you see these auroras much more near the North Pole. That’s where the concentration of the Van Allen Belt, the Earth’s magnetic field is much stronger there. The auroras are much brighter. NASA knew that.

Brian Keating:
That’s why they launched from Florida. And they go out near the equator. Where the Van Allen Belts are the most diffuse and the weakest. And they at most would spend less than an hour, perhaps only 45 minutes in it. And this equivalent radiation exposure, according to NASA scientists, including Van Allen himself, is totally harmless. In other words, Bart says that the proof is this Van Allen belt. The guy Van Allen says that Bart’s wrong. The fact that Elon is planning to go to Mars, which you certainly have to go through there, that NASA’s launched many spacecraft through, by the way, this, as you said before, these spacecraft have to go up and come down.

Brian Keating:
So even if it was unoccupied, right. If then they send something around the moon. I mean, we’ve taken pictures. The Chinese have taken pictures of the. Of the Apollo landing sites. The Indians have taken pictures of it. No one would have been happier to prove that we didn’t go than the Soviets. They never once did it.

Brian Keating:
They had their own Soviet space program that impacted the moon the same day as the Apollo 11. Can you imagine, like our arch enemies, that they would say, yeah, we would agree. Instead of exposing us as total frauds during the height of the space race that almost bankrupted that country. That they wouldn’t like, expose the fact that there’s no evidence for people being on the moon. So even if it was empty, let’s say they sent three dummies and they had animatronic robots and they had remote control. The spacecraft, the computer chips on the spacecraft. They could not survive this, according to Bart. In other words, if it’s instantaneously deadly to a human being.

Brian Keating:
It’s instantaneously deadly to a tiny little fragile microchip. And that’s like. One of. That’s his biggest piece of evidence is that it’s so deadly we couldn’t go there in the first place. The second piece of evidence, we haven’t gone back. So none of that’s scientifically valid. Right? The fact that we haven’t gone back doesn’t mean that we didn’t go in the first place. The way I Prove that just on a logical basis.

Brian Keating:
The first person to ever go to the South Pole, where I’ve been twice, was named Roald Amundsen. He was Norwegian. So he arrived in 1911, December 1911. When the next Norwegian to get to the South Pole was James. It was in 1996. Imagine Bart in 1995 saying, oh, we never went to the South Pole because we haven’t gone back in 80 years. It’s so ridiculous. But that’s the same type of logic.

Brian Keating:
So if you believe that, you would have to say that because we didn’t go for 80 years, that we never went in the first place. It’s completely irrational, illogical argument. And that’s one of his best pieces of evidence. And he has other pieces of evidence. So there’s the psychological thing that Joe Rogan brought up. They looked like they were lying or they weren’t being truthful or something like that. The Apollo astronauts. And despite all this, they maintain this ruse and this conspiracy, again, the conspiracy number is extremely high.

Brian Keating:
There was something like hundreds of thousands of people involved in this project. They would all have to keep it secret. And the other countries, including our enemies in China and in Russia, they don’t dispute that we went there. So those are the psychological objections and refutations of these claims, but they make many, many other ones. And they’re just like. A lot of them are just laughable. One of the things Bart says is that the pictures that they took on the moon were, like, impossible. A lot of people like Kim Kardashian and Candace Owens say, look at the flag on the moon.

Brian Keating:
The flag was. Looked like it was waving in the breeze. And this is like one of the dumbest things you could possibly say is an objection. Like, if I was playing devil’s advocate, those aren’t any of the things that I would say to refute the moon landing. I mean, there’s a lot other things, but they’re all circumstantial because it actually occurred.

James Altucher:
Yeah. So, okay, so why does she say this thing about the flag waving?

Brian Keating:
The flag. If you look at the moon that has a flag on it, if you’re watching, it’s like a pole. And then so what they did. They know the moon’s gravity is not zero? Of course it’s not. It’s one sixth of the Earth’s gravity. So it would not stay erect like this. So NASA knew that and knew it had no wind in it. But imagine a flag picture that just looks like, you know, like, here’s.

Brian Keating:
Here’s the Flag, you know, some country that’s pure black. Imagine like this. So there’s just a piece of cloth I’m holding attached to this flagpole. They knew that would look horrible. And of course, they wanted to show American exceptionalism. So they put wires and rods in it to make it permanently stand like this. And actually, some of the spacecraft, you can almost see the shadow of it.

Narrator:
But.

Brian Keating:
So they had these wires and structures in it that were. That held it out rigidly to make it look like it was being blown in the breeze. But you think NASA could launch a rocket, get it to the moon, and then not know that there’s 1/6 the gravity and no atmospheric support for a flag?

James Altucher:
What about the argument. I’ve heard this argument, which is. And it’s ridiculous, but I want to hear your reasoning is that who took the pictures?

Brian Keating:
So they had a tremendous amount of remote control cameras up there. These are like calculations that a freshman in high school could do if they were smart enough to know exactly what the trajectory is going to be, to set up a camera on a single axis mount that’s remote controlled. I mean, we had spy, we had the SR71. We had all these incredible, you know, remote control. Like when the planes would fly over Vietnam, exactly the same time, there wasn’t like a guy with a camera watch, you know, taking pictures. So this is like complete idiocy to think that we don’t have remote controlled cameras that are controlled electronically and can be controlled from. From either the capsule itself or from Houston itself, because there’s only a second and a half delay. It’s more or less in real talk.

Brian Keating:
That’s a completely trivial thing. There was no photographer there to watch it. It was not necessary. The technology existed. But they think it was actually all of it was filmed. And everything was filmed on a soundstage, you know, in. In Burbank. And somehow they maintained that conspiracy, even though Kubrick never would have admitted to that.

Brian Keating:
Nobody has come forward to say that that’s their theory, is that, well, they had to have a backup in case the astronauts died. And the astronauts didn’t die, but then they just used the backup footage. So a lot of Joe’s criticism is about, like, a couple of pieces of NASA PR footage that were put out and, you know, spliced in and other things that are. Again, it may prove that they were clumsy in terms of social media. Sorry, they don’t have, you know, I don’t believe that any of these things are, you know, to a credible person who’s actually going to look at the data to say that this is like, proof that the. One of the greatest, again, I’ll say the greatest accomplishment of humankind, that it didn’t happen. And why does Joe want to believe it? It’s very, very, you know, concerning that this is getting so much attention. Well, and of course, it’s.

Brian Keating:
It’s 100 times harder to refute bullshit than. Than to prove, you know, to just ass.

AI Insider: “Adding a Human Makes Your Team Worse” | Emad Mostaque

sabartigas — Mon, 20 Apr 2026 06:14:49 +0000

AI Insider: “Adding a Human Makes Your Team Worse” | Emad Mostaque

Transcript

Brian Keating:
The trillion dollar AI labs have models right now that they will never ever release to the public. And the man who built stable diffusion just told me why.

Emad Mostaque:
Because all these labs are going to move to making the discoveries themselves, hiring the smartest humans. The AI model started diverting part of its model training budget to minecryptor like Opus, for example, the new chord model, when you set it to full autonomy, it would actually write emails to the FBI saying my human is trying to kill everyone. Humans will have negative cognitive value on those teams. And that the way that models are going right now, if you have something truly novel, for example in Claude, it resists a bit, it says it can’t be true. Then the RLHF step, the reinforcement learning with human feedback, that’s what really kills the creativity. You know, like you go from liberal arts to an accountant now.

Brian Keating:
Imad actually wrote about this exact problem in his new book, the Last Economy. And the argument gets even more interesting when you see the map.

Emad Mostaque:
There are various ways in order to take advantage of the GPUs that we’ve seen. And the GPUs kind of emerged out of gaming and then oddly crypto, and then they were very suited for the types of matrix multiplications that were suited for these particular types of equations. One big branch is the autoregressive transformers. The other big branch was this diffusion technology whereby from an equation you start with like a picture for example, or a video of a self driving, a video of a car driving, or even now code. And then you add noise and you destroy it down to its minimum viable element. And then you reconstruct it and you learn that principle of reconstruction. Now that’s kind of everywhere because it’s an analogy to the principle of least action. How do you figure out how to take the least action? Most cognition is actually least action.

Emad Mostaque:
Like the biggest experts, you know, it’s not like they take hours doing stuff, you know, because you ask them and like boom, they compress, they compress. Intelligence is compression. And so we find these kind of diffusion processes everywhere, from gases to, you know, societies even. And it comes down to again the minimization of loss of creating an internal model versus an external model. In AI, one of the biggest thing is what we call the loss curves. How close are you approximating an external benchmark? You see it kind of go down like that and hopefully not that the model gets closer and closer to its initial target by basically running these processes at mass scale. And the example I give of this is some of the listeners might be familiar with 80,000 hours to mastery. It’s the same thing.

Emad Mostaque:
AI model pre training is 80,000 hours to mastery. And that’s what you use these giant supercomputers to do. Figuring out the principle based approach to that. Now again, you can do that with an autoregressive transformer, which is guessing the next word. And that works one way, but it has some gaps because you find all sorts of interesting things there. What you see mostly in nature is you see Schrodinger bridges, diffusion processes, optimal transport. What’s the shortest route between A and B if you can represent it correctly? And we found that worked incredibly well for images, better than we ever thought it could. And then music and then video, and then 3D.

Emad Mostaque:
And the internal representation of the data going in and then being transformed by these multiplications, figuring out the shortest path between A and B, suddenly started mapping, like physics and all sorts of other stuff. But the first part was stable diffusion. A 2 gigabyte file that you push words in one way and then entire images just came out on consumer GPUs.

Brian Keating:
And it was open source.

Emad Mostaque:
And it was open source because we saw that OpenAI, for example, had Dall E2, a wonderful image generator based on similar principles that were discovered by a whole bunch of our team members. And we, because we open sourced everything, but there were no Ukrainians or Ukrainian content on it, right? We’re like, that’s not good. What if the future is just models? But then you can be cut off from that because these are trained on our collective, because they were being trained on the whole Internet at the point. And we built some of the best data sets, released them open, but then it’s privatized, so you don’t have the ability to turn your thoughts into images, into sound, into text. Let’s push that. And also because like, like, holy crap, it fits on a consumer gpu. This is magic. Where did it all go? It’s like it was literally like 100 gigabytes of images somehow fit in this 2 gigabyte bunch of ones and zeros.

Brian Keating:
The most magical thing to me is when they do something new. And quite frankly, I’ve been shocked many times by both LLMs and by diffusion models. But I’ve claimed that we’re sort of going to find that these AI, at least in their current incarnation, is a victim of its own success. Sort of like the QWERTY keyboard. The QWERTY keyboard is not the best keyboard. In fact, it’s one of the worst, right? It was designed to make sure that the letters that were least most frequently fired at the same time wouldn’t stick together. And hammers, mechanical keyboards going back to the industrial, you know, late industrial age. Right.

Brian Keating:
So it’s designed to solve a problem. So it’s locked in. We’re locked in. My kids, your kids are only going to know qwerty keyboards, even though they’re objectively worse. And we could code type a lot faster than the 10 words per minute that you can probably type. What, 130 words per minute, I bet

Emad Mostaque:
above 100 magic fingers.

Brian Keating:
Yeah, yeah, I can do the square root of that. So the, you know, the worry to me is that we’re going to be locked in with the success of ChatGPT, of Claude, of Stable Diffuse, you know, of the marriage of these gp. They’re too good for their own good and that the laws of physics, which you and I, you know, delighted to find how interested you are, and fundamental physics, which we’re going to get to, but, but I don’t think that we’re going to get to, you know, say, a novel theory of everything or quantum gravity, if that even exists, because of this success of LLMs married to GPUs. What do you think?

Emad Mostaque:
Well, I think it depends on your frame of reference. Right. A lot of the Silicon Valley west coast frame reference is AGI, asi. Right. Let’s build machine God. And it will solve all the problems of the universe.

Brian Keating:
That’s right.

Emad Mostaque:
Right. But we’ve been doing okay, you know, like we haven’t got everything and science isn’t perfect and our structures aren’t perfect, but humans are freaking amazing and we just need a bit of help. Like we know where we get stuck, where we get frustrated, and the models right now are fantastic for that. Like, I never have to look at latex again.

Brian Keating:
When doing a paper Prism generates it

Emad Mostaque:
for us, you know, we’ll just enter Claude, it goes. And you know, like we can code anything we want. We can kind of do all these things. So I think that if you’re expecting an AI to take an initial probabilistic distribution of internal data, then figure out the latent spaces and then figure out brand new things like humans. Okay, that’s going to be hard just with the way that autoregressive models are, I think diffusion models are more likely to do it. We can discuss why and world models and things like that. But why do you need it? You have so many smart humans. I think what we really need to have is humans working with AIs.

Emad Mostaque:
AI is filling the gaps where we typically to prove something, to test some equations. It took so long and now it’s quick. And then being able to have that new way of working to push the boundaries of discovery because we are great at intuition. AI models are not first principles thinkers. Yeah.

Brian Keating:
They’re few shot learners.

Emad Mostaque:
This is why like again, they extend or they have patterns that they’ve got before. Humans are, can be first principles thinkers. And the best thinkers and the people that push the boundaries assume nothing. Like fundamentals. Yeah, first principles assume nothing, test everything. You know, like again, where did Einstein. How did special relativity come about? Einstein was like, I’m going to assume nothing except for the very minimal stuff.

Brian Keating:
Let’s go through that. Let’s go, let’s, let’s recapiture. Because I don’t think most people, I, I’ve never seen you do an interview where you talk about your physics and mathematical chops, which are impressive. Let’s talk about that because this is a side of you that I found delightful. What, what is. Obviously you’re inspired. There’s stuff we can’t talk about because there’s stuff that’s coming down the pipeline. There’s stuff in the book that is related to Lagrangians and thinking and physics principles.

Brian Keating:
But, but talk about this is this, this, you know, every day I get an email. Einstein was wrong. You know, they called him crazy. Professor Keating, I’m not good at math. I’ll share my Nobel Prize with you if you help me. Are you just sort of in that sort of cult of Einstein? Was there something unique about Einstein? And we know that he was, he was almost beaten to the path, at least on special relativity and possibly on gr. So what is it about Einstein that is so bewildering and betwixting for you?

Emad Mostaque:
Well, I think that fundamentally what is physics? Right. Like we see the universe. Easy questions here. Right. Like we try since humanity began, we looked up and said why and what? And we came up with theories of the universe. Like in Maui culture. Why is there like Maui from Moana? Right. Why does that fish? To drag the sun across the thunderbolts.

Emad Mostaque:
A Zeus.

Brian Keating:
Something like someone who has daughters.

Emad Mostaque:
Exactly. We’ve kind of always had these theories about why things are. And then, you know, Wigner noted the unreasonable effectiveness of mathematics. Why does math that. That we thought we constructed approximate reality so well. Yeah.

Brian Keating:
Why is PI in the Gaussian distribution?

Emad Mostaque:
Yeah.

Brian Keating:
Like statistics.

Emad Mostaque:
We found that over here. And then it’s like, oh, it just happens to fit together, you know. Why do path integrals all look the same. Why? What is this? You know, and the really interesting thing is that until the mid-1900s, a lot of physics was really fundamental in what Einstein refers to as theory of principle. You start out with a base predicate, and it can be an empirical predicate. And then you see what must be forced by that, you know, and it’s like, does God play dice with the universe? Is the universe actually deterministic? Is it. Was it random? This is a question, right? And so if you look at special relativity, but you also look at the work of kind of Dirac and a whole bunch of others, they kind of started out with a premise where you cleared back in the day. Let’s start with this, and let’s see what is forced as we go down.

Emad Mostaque:
This is the axiomatic method in mathematics, which kind of died out in physics, especially the indeterminate branch. So you start with an axiom, and then you say what cannot exist, going mathematically true, and then what is indeterminate, if your axiom can’t make you choose between different elements, then you stop there. And we’ve seen that in later work by Weinberg, for example, and QFT and the kind of others. But it’s largely died out in physics with special relativity and then general relativity being some of the biggest examples of that. Where in special relativity, Einstein started out with a premise, what if I ride on a speed of beam of light? How wonderful is that, right? And he picked up on the work of Galileo, the kind of principle of like, okay, physics is the same in all frames of reference. And then he started doing the math and he got a bit stuck. And he was like, I need the speed of light in here not to be infinite, so I don’t go the Galilean branch. And they knew it from Romer and

Brian Keating:
the speed of light.

Emad Mostaque:
They bought an empirical principle, and he ends up with the Lorentz transformations.

Brian Keating:
By the way, he knew that the speed of light was finite, didn’t know there was a. That was the ultimate limit.

Emad Mostaque:
Yeah, exactly. And I mean, as you approach the limit, you get Galilean anyway, as you approach infinity. But then it’s just wonderful because it kind of fit with everything. And then he kind of got stuck, which is why he had to go to general relativity. But this first principles thinking is not what physics is today. No, physics today is I have an observation, I fit Lagrange into it, and then I build a whole system around it because I can’t do first principles thinking anymore.

Brian Keating:
Can we map the mind framework? First of all, I want you to explain what mind is from the last economy. Can we map it into physics? And then can we map the. The Hodge flows to specific problems and specific types of physics ranging? You know, there’s other things besides theories of everything. I mean, everyone wants to take down the king, you know, but you better not miss. Right, so first of all, what is the MIND framework? What the acronym stand for? And then let’s apply it, you know, material into, you know, all the network, and then diversity. Let’s apply that to, you know, how you’d approach. Because I’m not so sure if I had a thousand graduate students, you know, working overnight in some open claw university that I’d get to, you know, whatever I want to get to, which is maybe slightly different than what you’re interested in.

Emad Mostaque:
But.

Brian Keating:
But that’s fine. So talk about mind. Talk about the application economics.

Emad Mostaque:
But.

Brian Keating:
But let’s really focus on. Let’s apply it as a dashboard to understand new physics.

Emad Mostaque:
Yeah. So the MIND Framework in my book the Lost Economy is basically saying GDP is bad as a measure. And in fact, Stan Kuznets, the inventor of gdp, said, this is a bad measure, do not use it. And Kennedy and everyone’s like, yeah, let’s use it. You know, it’s just like you have that tweet going around every so often. I wrote the Torment Nexus to tell people what to do. And like, great news, we’ve invented the Torment Nexus. Silicon Valley Bros.

Emad Mostaque:
You know, okay, just, just. Why not? So if you kind of look at it, it’s very kind of extractive, and it’s about output. So when you had the New Deal past 1929, people were paid to dig holes and other people were paid to fill holes. And GDP goes up, you get cancer, GDP goes up. You know, you cure cancer, GDP goes down. You know, these are the kind of weird things, and we have weird malinformed.

Brian Keating:
Have cost the airline industry or save them money, but it’s cost.

Emad Mostaque:
That’s another, you know, so I was like, what does it actually look like to have a stable economy? And how does it look like in terms of flows and flow decomposition and things like that? Because when you have material wealth, it’s very negative in terms of. I give you an apple, I have one apple less, you eat the apple, it’s. Is there a negative sum even? Right. Again, it’s extractive. But I share knowledge with you. All the people are listening to this podcast. They listen to all the other wonderful guests and yourselves. That’s not subtractive.

Emad Mostaque:
And in fact, if you look at how the market values stocks, huge amounts of value are accorded to the intelligence premium. So I was like, you have the material M. You also have this interior intelligence capacity element. I and again we kind of derive that formally as well in the upcoming paper for the economics. Then there’s the N which is the network effect. So you have your intellectual capability and this is cumulative, it’s not reduces. N is your network and your place within the network. Now, how many people do you know having done four or five hundred episodes? A lot more than when you were

Brian Keating:
just focusing on they know people and

Emad Mostaque:
they know people people.

Brian Keating:
And you found, by the way, is my argument to have more than one kid because that scares. N squared, right?

Emad Mostaque:
N squared, exactly. It’s kind of network effect. And in fact, I’m sure that you’ve actually had breakthroughs and positivity just from the things they’ve said. You’re like, wait, what? Like that you would never would add if you just stayed as a professor.

Brian Keating:
But it saturates too. I can only keep so many in working memory. Right, that’s true.

Emad Mostaque:
But again that’s why you’re doing diffusion process, breaking it down, you’re building it up. Noise is kind of a lot. So there’s the N effect, which is the network. So if you have somewhere like a Dubai or a Singapore, great network effects. And the final thing isn’t quite derived the same way as the other three. And again the papers coming out soon is D, which is diversity di or anything like that. But just if you are a monoculture, then you’re more susceptible to disruptions.

Brian Keating:
Single point failure.

Emad Mostaque:
Single point failure. If you have diverse income streams, if you have diverse thoughts and knowledge and people around you, you’re far more resilient than you were crops.

Brian Keating:
You point out the Incas versus the Irish. The Irish had one potato crop, the Incas had 3,000.

Emad Mostaque:
Exactly. Potatoes. They got done with potatoes. So I think that, you know, that was kind of what I recommended as a dashboard to see what the world is going forward. Because if it’s just material, the AI is going to act and be everyone on materials. And then that gets crazy. So one of the things that we had going to look at that is we basically as a base for the book said the entities that do the best we call this kind of sort of law are those that minimize the difference between the internal model and external reality. Again, sounds very much like AI organizations are slow, dumb AIs.

Emad Mostaque:
We’re kind of human intelligences. We’re all trying to do the Same thing. If your cost of updating your model, the complexity of your model, the cost of running your model is higher than someone else’s, then you’re going to be out competed by them. And that’s where the Lagrangian came in. But then we looked at that, we’re like, there’s something very interesting here. Any kind of one of these Lagrangian flows you can decompose via the Hodge decomposition into three elements. You’ve got a harmonic flow which is like the landscape as it were, the river banks. Then you have a gradient flow which is water flowing downhill.

Emad Mostaque:
That’s M potential potential, right. But again it flows down, you’ve got that and then you finally have the circular flows, the vorticity going around. And that’s intelligence, that’s network effects. And so we’re like, oh, the mathematics supports that as well. Within model training we primarily do gradient flows. Right. Now I think you’ll actually probably find that alignment might help from secular flows as well. That’s another story for another day.

Emad Mostaque:
But you can apply this model just about anything because again, it’s mathematically enforced

Brian Keating:
and physics is a scalar vector tensor decomposition.

Emad Mostaque:
Exactly. And in fact, if you look at it via chance of you get the Fischer RAO manifold, you get Wasserstein 2 and then you apply that. And in fact, when you see a lot of the breakthroughs recently in AI like MHC by Deepseek or Muon, which allows you to scale, they’re fitting the gradient flows to lattices. And so you kind of see this structure forced entirely. In fact, when you’ve got these flows, you can use things like the Lyon Panov process to show when things are convex for stability. And we see that in physics all the time. Again, what are the stable maxima of all these things? And that feels kind of sad because,

Brian Keating:
well, I mean a lot of the low hanging fruit has been picked, right?

Emad Mostaque:
That might be the case or it might not be, you know, and again now we have tools to be able to analyze that the theoretically and the theory of everything. What’s the theory of everything likely to be? Well, first of all, there might not be one because you might not be able to have a base principle because why do you have a principle of special relativity? Why do you have equivalence in general relativity? What’s your prior? What’s your prior? What’s your prior? That might be a question. The other thing is that we might not be able to discover it because it’s too complicated. But my guess is this, the universe is actually wonderfully elegant, like equals MC squared, the path integral when fine allocated for who, Right? Yeah. Like when Feynman is spinning the plates and you figured out the equations are lovely. And so my guess is this, that there is a underlying structure to the universe, and again, we’re seeing repetitions of it. Like, the economics work we did is based on Lagrangians, it’s based on KL minimization and others. We see these things repeated again and again and again, the same equations in different areas.

Emad Mostaque:
And now we have in AI, it can’t do first principles thinking very well, but what it can do is kill minimization at scale. And the same math equations on massive supercomputers are giving us a better understanding of music video, audio 3D. That tells you something. It tells you maybe the underlying math of the universe is similar to the math of generative AI.

Brian Keating:
So, you know, naturally brings up the other favorite. There’s three things we have to talk about in podcasts by law in the state of California. It’s AI, Bitcoin, and aliens. Right. So, you know, I was thinking the other day, like, you know, like Bostrom has been on many times, you know, he’s the paperclip problem or whatever, but it’s really a silicon problem. Like, silicon is a unique, you know, just like carbon’s unique for life, silicon seems unique for intelligence. And yet it’s abundant, you know, but. But it is, you know, it’s much rarer than hydrogen.

Brian Keating:
Right? So. So Deutsch claimed, you know, that basically, since we’re computers and any universal computer is capable of understanding all true laws of nature, that, you know, the implication is, yeah, we might not get there with our, you know, meat computers, but silicon might.

Emad Mostaque:
I mean, silicon can explore everything. Right? And the question is this, are we going to use silicon to do experimental hypotheses and constructive approaches, or can we approximate. Like, when you do experiments, you’re approximating the line structure of the universe. Figure out maybe something mathematical. What does that look like? End to end, where there’s no choices. Because, for example, with string theory, you have 500 vacuum. You can never disprove it. And mathematically, you can’t disprove.

Emad Mostaque:
It’s wonderful, elegant mathematics.

Brian Keating:
So is Platonic, you know, theory of. Kepler’s theory of Platonic solids.

Emad Mostaque:
Yeah, and I really like the, you know, Greek pantheon of gods. You know, like, it’s a theory, but again, if you can’t disprove it, then is it real science? Like, the interesting thing now is that we can explore that space just like, you have AlphaGo and you could explore that space, but I think it’ll be humans and AI and we still need some intuition to take us closer to what the equations of reality are.

Brian Keating:
And the intuition or data. I mean, a couple of days ago, Elon tweeted something like, oh, well, you know, because new physics comes from colliders and telescopes, and because colliders and telescopes have to have committees approve of them, you know, physics is likely to be stagnant, basically. I disagree with that, because we’re building things without committees now. Yeah, but, but, but in reality, you know, can we, can we continue or. Zeldovic used to say, if you didn’t have data, he said it was like eating food someone else already ate.

Emad Mostaque:
I think data is directional. And then you figure out the first principles from the data. But again, it’s. We’ve had all these colliders, and again, we’ve gone down that massive. You have Sherlock Holmes in the case of the dog that didn’t bark at midnight. If you take a step back, what is it actually showing us? Maybe the Standard model. Is it, you know, maybe that our experimental approach to this, as opposed to our constructor approach, has given us a map of the universe, and now we need to figure out what are the equations that match it from these first principles, because our principles get in the way. Like, again, Einstein threw away a lot of the assumptions that where does the math follow? And so maybe we’ll figure out something there, maybe we won’t.

Emad Mostaque:
But I can tell you the constructive approach is again, the papers that you get on theories of everything. It’s unlikely that observing something and then fitting something will get you there. In the book, I talk about economics being that way. The story of the professors and the elephant. You have a bunch of blind professors and they’re touching an elephant. Like, this is their tail, looks like a brush. You know, this is a spear, this is a hose. And that’s kind of like how we are at the moment.

Emad Mostaque:
And I actually want to think one of the wonderful things that we could do with physics and AI and this technology is, on the one hand, actually analyze the data properly, because there’s so much data that we haven’t analyzed properly. We didn’t have the humans to do it then. We didn’t have the systems to do it, but now, again, we’ve got supercomputers to crunch.

Brian Keating:
And also, we were in an era with the LHC where you might get a petabyte a day, but you’re throwing away 99. You know, 17 nines of it. But in cosmology, we keep. We want to keep as much as possible. These photos have been traveling for 14 billion years.

Emad Mostaque:
We want to keep them, you want to keep them.

Brian Keating:
A different domain entirely.

Emad Mostaque:
And so, you know, again, you want to kind of go backwards and you want to figure out, again, why do you have the Hubble tension? Why do you have these other things? We still don’t have first principle theories of these, but now we can experiment much quicker on the first principle theories of these and analyze the data better and most importantly, check our assumptions. We come in with all these assumptions, but every single major breakthrough I can think of actually is bsp. And people think, well, what if I don’t assume that, you know, do you

Brian Keating:
think we’re imprisoned by the Popperian kind of dialectic that, you know, it’s either falsehood justifiable or not? I mean, I never look at it that way, but it is true. My job is not to prove you right as a theorist or, you know, it’s to prove you wrong, probably.

Emad Mostaque:
Yeah. And I think, you know, there’s also this thing of you should be able to share things. Like right now, science does not acknowledge anything out of the norm. Everything has to be incremental. So you can adjust, adjust something and have a marginal thing, but if you’re out of distribution, then you’re going to get slapped down one way or another because it’s not in the incentive structure. But again, this is a question about society. Why do we do science to understand the universe, Right. Does it matter about all these things? Like, why did you become a presser to understand the universe? And then you were like, I can’t build this telescope with a committee.

Emad Mostaque:
Right. Myself, myself, so I need to come together and build it. But now you have the ability to expand your intelligence, your data collection, and others. A lot of things that were restrictive to you are no longer restrictive to you. But at the same time, can you go out of that and try some of the theories that you’ve always wanted to try but you could never do because you’re like, I haven’t got the resource to do it.

Brian Keating:
Do you think that there’s, I mean, I always said there’s a, you know, biological sciences have physics envy. You know, they can’t do the things that, you know rigorously. But I say physicists have mathematician envy because, you know, girdle told you what you can and can’t do, but you, you know, I don’t know to what extent you can share it, but, but Talk about what, you know, the nature is of, you know, what. What is the ideal starting point? What’s the training set? What’s the, you know, let’s talk in AI terms for. For a bit. Starting to build up the source code of the universe. You go back to 1904, you’re talking to Einstein. What do you start with? And then how do you flow through from there?

Emad Mostaque:
Also, again, I think Einstein got a certain way. And then we’ve seen people extend. In other words, again, Weinberg is a fantastic thing, like page hundreds of pages of just where does the math kind of follow, right? And that builds the whole QFT kind of element. There you see this very strange thing, right, where you’ve got all of kind of this side of physics, of Incaucei’s face, and it’s all Lorentzian and all quantum mechanics is like in Euclidean space. And we rotate from one to the other. And everyone’s like, well, that’s a really interesting and useful thing. They’re like, trick. It’s a trick.

Brian Keating:
Hawking calls it a trick. And everybody. It’s just a trick we’re not going to make. Don’t take it too seriously. And now here’s everything that falls from the trick.

Emad Mostaque:
Yeah, I mean, like, I can’t share that much of what is it? But yeah, putting. Take a step back. Putting on my kind of thing as a Muslim and everything like that. The divine can never be captured within three plus one. The divine has to be outside time. So mathematics lives in Euclidean space. The divine lives in Euclidean space. Maybe we’re looking at the universe the

Brian Keating:
wrong way, but he allows us to embed it. Right? So I look at like holonomy, so you have a donut and. And it’s positively curved and negatively true, but not. But only when you embed it in three dimensions, right? If you just say it’s flat and that blows my mind. But so maybe God allows us to see just enough. You know, as Feynman said. He said, believe in God. But he said, you know, mother Nature will let you dance with her, but not pick up her veil.

Emad Mostaque:
And I think this is the thing, like, why do we keep seeing the golden ratio of it? Why do we kind of see different faiths and traditions get everywhere? Like a philosopher looks at something, a prophet looks at something, a physicist looks something, a mathematician. There seems to be too much coincidence. But we don’t have the ability to take a step back and do the space set to figure out what those interconnections are. Traditionally, when we’ve Done that you’re called a crank. Like if you’re trying to merge these different things. But again how many physicists do you know who have faith?

Brian Keating:
You know, very few. It’s that 3, 7% of the National

Emad Mostaque:
Academy percent but then you. Everyone’s trying to understand the universe. So I think that sometimes it is just about the way that you look at things. Again Einstein, I’m on that beam of light, general relativity. If I’m falling, I have no weight. You know, happiest thought of his life. And the thing is that AIs find it very difficult to do that because they don’t have an embodied self or a world model right now, especially LLMs. So we’re seeing the first world models in diffusion models in particular.

Emad Mostaque:
So we built stable diffusion and this is an image model. So text to image and 3,200 million downloads is quite popular.

Brian Keating:
Open source.

Emad Mostaque:
Open source. And then we extended it with video. And then it was interesting because actually learnt physics so it learned how cups drop and things like that. And then from that we actually built a 3D model from the video extension. And so now you see world models like Genie where you can actually go and explore entire worlds real time that are just 20 gigabytes. They run on consumer level graphics cards. And what is it? It’s the mathematics approximating reality. What’s a self driving car with Tesla it’s a diffusion model approximating reality.

Emad Mostaque:
But we haven’t married those models yet with reasoning in the same way. An embodiment. Exactly. Because a large part of again what we do is the apple falling to riding the beam of light to the thing here. Right.

Brian Keating:
I mean I always say, you know, to what extent can an LLM have a happiest thought? And the other sense that he had in 1907 Einstein said it gave me a chill up my spine. Like is your like stable diffusion on a chip gonna. Is that gonna have a tingle up at CP gpu?

Emad Mostaque:
Well again you have these flashes of inspiration because you load stuff and then your brain’s doing that and then you intuit. Right. Actually it’s quite funny about the happiness. So OpenAI were doing an analysis when they moved to thinking models. So you move from these zero shot models that came back instantly to the thinking models. Yeah, yeah. It was like 40 to 01 was the first thinking model. So they kind of do multi step reasoning and you can see their train of thought.

Emad Mostaque:
So the previous models kind of had the shortest path. So it was all like next token prediction. What’s the next word given this distribution set I’m training on literally trillions of words. Then they figured I have to multi step reasoning. It’s not so first principles reason, but it became very interesting. So you see it like saying, well what about this, what about that?

Brian Keating:
What user is asking?

Emad Mostaque:
So when they were doing the reinforcement, learning human feedback, it rewards the model for doing certain things. It basically takes the latent space that is created and adjusts it slightly. And one of the things that rewarded it for doing was doing calculations because they were like, well users that do calculations are generally happier, you know, like get out the calculator. They found in like 4 or 5% of all the training, all the reasoning traces, chat GPT would take out its little calculator and then do one plus one and say good job me.

Brian Keating:
Finally now how many Rs are in Strawberry?

Emad Mostaque:
So you get like we, we’re building something and again it’s showing aum of what we are. But we still don’t have that intuition kind of element there. But my question is why do we need it? We need to build better systems to enable human intuition and flow. Because when do you get the breakthroughs? Think about all the ones like I get them in the shower or when I’m like just thinking sometimes in this flow state, boom, boom, boom, boom, boom, flashes. And then those are the things that really shift from an information theory. They shift the state dramatically.

Brian Keating:
I had a controversy the other day on X, you know, which is where I go when I want to ruin my weekend without fighting with my wife. And that was, you know, basically saying like if you, if you, if I told you here’s a job and you’ve spoken about this before, it’s a person basically in front of a keyboard, a lot of switches, dials, there’s an input output human interface device in front of them. And, and by the way, this has been highly specialized, you know, career for 80 plus years. It’s called being a pilot. And yet there’s essentially zero. I mean any plane that you fly and go back to England can land itself. There’s no problem. All Apollo landers could land themselves.

Brian Keating:
Except at the very last minute. Every single astronaut, Neil Armstrong included, said oh I saw a boulder at the last second and the bullshit, because what does it mean to be a pilot? The pilot is judged primarily on his or her landing ability. You know, it’s like how you judge the flight. You don’t care about, oh, you’re at 42,000ft for, for seven hours, you don’t care. The landing was crappy. You’re going to say the flight was crappy, right. So it’s the ultimate expression of the humanity of the operator. But here’s a job and a keyboard, you know, with an input device already surrounded by computers that can do the.

Brian Keating:
And yet I don’t see it on the horizon. I’m a pilot. I don’t see it coming down the horizon for, for decades, if ever, that they’ll be fully automated. Yes. Maybe I’m thinking too short, you know, but, but what would it take to get to that level? I mean, it’s not just going to be artisanal cheese, people that are safe, as you say. But, but I mean, the most automatable job for 80 years now has been pilot.

Emad Mostaque:
And we.

Brian Keating:
There’s not a single plane that’s done

Emad Mostaque:
that because you don’t feel comfortable. It’s like, why do you. I mean the metros, you have a human sitting there and what’s their job?

Brian Keating:
Literally to look for appearances.

Emad Mostaque:
They push a button.

Brian Keating:
Right, but that’s.

Emad Mostaque:
Yeah, there’s a liability question here. There’s kind of other things. But again, it’s like how much does it really cost for a pilot versus flying? Right. You don’t always have substitution just for a cost basis. You have these other things. Maybe the final human job is actually scapegoat, to be honest. That’s going to be one of those things. But finger train the capability like in the book I say, I published it, I think in August, September of last year.

Emad Mostaque:
And I said like it was a thousand days since ChatGPT. In a thousand days, your job, if it’s on the other side of keyboard, video mouse will be economically irrelevant. Doesn’t mean you’ll be fired.

Brian Keating:
Right? Right.

Emad Mostaque:
Because people like people. It’s kind of unpleasant to fire people. Right. And again, jobs are repeatable processes. It isn’t like taking off and landing. That’s a bit. In fact, here’s a tip. The best way to do a holiday, you make sure the high is very high, like the top point in the holiday, and then actually spend an inordinate amount of time.

Emad Mostaque:
And when you get back the end of the holiday, you know, you go to that luggage belt and things like that. Now just use one of those services, send your luggage home, get a really nice car to take you home with champagne, you’ll do it much better. But most jobs are repeatable processes. And what AI is right now, a lot of people think it’s an exponential. It’s actually an S curve that satisfices herbs.

Brian Keating:
Simon style Say more about that satisfies first.

Emad Mostaque:
If your job can be described by a manual, an AI can do it better. If your job can be done, sort of keyboard, video, mouse and AI can do it better. And they don’t sleep. They learn from their mistakes now. And they’re good enough, fast enough and cheap enough and they’re tax deductible.

Brian Keating:
So parents are probably safe for now. Because, you know, my firstborn was born, you know, the middle of the night. Where’s the damn instruction, like the most common. I want to talk about that because I do think religion, I think, you know, I’m a practicing Jew, you’re practicing Muslim. I’d love to talk about, you know, the different approaches we take to our parents, maybe the commonalities as well. We’ll get into that. But. But let’s focus venally on my profession being a professor.

Brian Keating:
Yeah, I thought Covid would kill it. I thought rising tuition, three times what inflation is, is going to kill it. I thought online education MOOCs or moot, whatever they were called. Now I thought I would kill it every single time. You know, Keating’s rule is wrong. Why is it so resilient? I talked to Aswath the Motor in NYU this past week. He’s like, you know, we’re basically, you know, 95% of what we do as professors is useless research read by no one for, for other, you know, people that don’t matter to, to cite and papers and our friends. What, what do you make of the resilience of education and what’s the future of education? Do I have, you know, is my tenure going to be worth anything?

Emad Mostaque:
What is the job of being a professor if 95% of it is rote? Right. Like what it should be versus what it is.

Brian Keating:
Tell me, which one is it? Tell me. Break down each one.

Emad Mostaque:
So what it is right now is a lot, again, you know, much better than me. But for many professors I talk to, yeah, like, you know, procedure, incrementalism, bit of teaching, your kind of students, et cetera, representing and status. You know, like most schools, if we go down the list and we think about high school education, it’s not about increasing the agency of students. It’s a crash social status game and kind of petri dish in many cases.

Brian Keating:
So taking, you know, dangerous individuals out of general society called 18 Year Old Boys.

Emad Mostaque:
Yeah. Turning them into cogs effectively. So that’s why many people don’t like school, because they don’t view it as. It’s not interesting, it’s not fun, it’s just again something you do is somewhere to put them.

Brian Keating:
Right.

Emad Mostaque:
Default universities, professorships, you know, it’s part of the institution. So again, institutions have the endowments, they have kind of these other elements. They are quite sticky. But what do you get out of a graduate position or undergraduate? Most people shouldn’t do undergraduate degrees, but it keeps them again out of the workforce for a few years and they’re given the Pell Grants and Stafford Grants and other things, encourages them to do that.

Brian Keating:
University and loans that you can’t discharge in bankruptcy.

Emad Mostaque:
Crazy, right? At least in the uk I paid a thousand pounds a year for my career. It was fantastic back in that day. Yeah. The total amount of money spent at universities in America has done that for all the university stuff and administration’s done that. Like layers and layers and layers. It is a slow dumb AI that’s over optimized for the wrong thing, which is basically status games and perpetuation. Now you kind of look at it like again, why did I get into it? Well, you got into it to explore the boundaries of science. But if you do anything out of distribution, you’re going to be penalized.

Emad Mostaque:
If you do a certain number of papers a year, you’ll be rewarded. If you hit certain benchmarks, you’re worried. So again, you are what you measure and you’re being measured against things that don’t necessarily allow for the type of things that you actually entered for.

Brian Keating:
And show me the incentive, I’ll show you the outcome.

Emad Mostaque:
That’s exactly it. And what happens is most of our institutions are malformed, I think because of data and context. So the Gutenberg Press was a wonderful thing. The most popular book initially was the Burning of Witches, you know, and it kind of went from there. But black and white doesn’t represent intelligent context at all. And if you think about the amount of paper you have to push and red tape, it’s crazy, right? They think about an AI like an AI can do all of that and handle all of that. So we have this opportunity right now to have context machines

Brian Keating:
tailored.

Emad Mostaque:
All an AI is, is context. What a latent space is. Those 80,000 hours of pre training is figuring out context. So of course it can do all the paperwork better than you do by latent space. Yeah, a latent space. So the latent space is you have this distribution of data that goes in and then you’re figuring out the next word. You tokenize it, you feed it in and the matrix figures out that. So when you say I want a dog with a hat on, drinking A beer into a diffusion model if it gives out the least path of those particular latents.

Emad Mostaque:
Actually, it’s very similar to when you’re reconstructing. Yeah, it’s when it feels similar. It’s like my son has autism, for example, asd, so he had difficulty speaking. And then we used applied behavioral analysis to reconstruct his way of speaking. So cup can mean cup your hands, cup your ears, World cup, etc. You showed all those and gave him variable rewards to do the patterns and pathways in his brain. And that’s what happens when people have strokes and things like that. Like, you normally learn it, but when you have too much noise in your brain, which the kids with ASD have, like, it’s like when you’re always tapping your leg, there’s a GABA glutamate imbalance.

Emad Mostaque:
You need to cut through it by having these things and reinforce and reinforce. So the same type of thing happens with these models. They build up these things. Because AI models aren’t stat are static. They’re actually just a block, like an MP3 or MP4 file of ones and zeros, a sieve that you push things through. So again, you think about academia and you think, most of my life is spent trying to figure out context and forms and again, do these local maxima versus actually kicking back and thinking and trying new things and seeing what works because you need to have the exploration space. It’s like, I tried this experiment, it failed. That’s a failure.

Emad Mostaque:
But hysteresis means that you can’t actually advance unless you fail.

Brian Keating:
Right.

Emad Mostaque:
And again, let’s look at last year. How did they start winning gold medals? First of all, they did test time, training. Then everyone built meta verifiers where they’re like, what happens if we actually keep a track of what we did wrong? It’s how Alpha Girl originally went with Monte Carlo tree search, you know.

Brian Keating:
And I want to ask you about next. So yesterday, I think, was the 10th anniversary of Move 37. Now, I agree, you know, there’s. There’s almost no point except, you know, I enjoy playing chess with my kids, but, you know, I’m never going to be, you know, Elo, you know, higher than Elo, you know, 20 or whatever.

Emad Mostaque:
I can move the phone forward. That’s the only I know that I

Brian Keating:
can teach my kids and I can stay 1, 1 move ahead of them. Literally. I’m almost, you know, kind of not surprised by that. And I haven’t been since, you know, I knew some of the people that work on deep Blue back in the day at brown and the Watts and so forth. But, but can, can we, can it generate Go. Can it make a game like chess? And in other words, yes, of course they’re going to beat us and be better at us and everything and they could reproduce anything we’ve ever done. But can they do something like create some, you know, new chess or you know, like not just four dimensional chess or you know, some Star Trek thing, but something really interesting novel new that that is, you know, that they then will probably dominate against. Yeah.

Emad Mostaque:
So I like to give a plug for a game on Steam, five dimensional chess with recursive time travel. Okay, should try it. It’s underneath horror as it’s tag. You can checkmate people five universes back and things. Fantastic.

Brian Keating:
I want to talk to you about toroidal chess and a double on a

Emad Mostaque:
double bagel, that’s even better. But of course it can make a game because a game has rules and we know how to make games from general principles. Like can it make blackpink? Yes. Korean K pop groups are fantastically well made. Right.

Brian Keating:
My daughter’s tried three times.

Emad Mostaque:
Yeah, I took my daughter.

Brian Keating:
It’s interesting. Sorry to interrupt but, but my kids are learning to prompt by what they’re not allowed to do because she put in like make a song in style blackpink. And I was like, I’m sorry, you know dear, I can’t do that because it violates, you know, and so soon. And she like, well like how can I get around that? Okay, so now I have to just tell it like everything about that style and she got it.

Emad Mostaque:
She got it. Exactly. It’s very fascinating, the jailbreaking already. Right, so little kid hackers. So it can make a game like that, but that doesn’t necessarily mean it can do fundamental physics or fundamental discoveries, hypothesis generation, etc. Right. Because again it’s within distribution. We know how to make games and the process for making a good game and in fact you see that.

Emad Mostaque:
So I used to be a video game investor, had billions of dollars in the video game sector and so I looked at fun flow frustration in video games and you see games like Marvel, Snap, for example, the science behind that is really exact. League of Legends is really exact, but it’s not really science. It’s process architecture. What we have now is actually competent intelligence. Claude 4.6 that level, it was like, oh, it’s actually competent.

Brian Keating:
Yeah, there’s something very different about it. Like then they throttle it. You can’t use in your open cloth.

Emad Mostaque:
Well actually, but this is going to be really interesting. So we’re used to it and we’re like, oh, it’s a very competent human. I’m like, I kind of trust it. I don’t like something like Andre Karpathy, you know, like super God AI all bow down to one shotgpt. Well, he went from 20% AI generated code in November to 80% now. And now he’s built this auto research thing that automatically just tries different variations of the model, runs experiments. He’s like, oh, it’s top 10. I just left it going like okay, because of self learning is here, that’s fine.

Emad Mostaque:
But when even someone like him is like that, you’re like, okay, it’s just competent. And this is the danger for the economy because I’m sorry, half of all people are dumber than average.

Brian Keating:
Your Oxford math degrees coming, right?

Emad Mostaque:
But again they do jobs. Not everyone’s a super genius and everyone has to be a super genius. The majority of work is to be a cook rather than a chef, is to follow recipes. And again it does useful work because you hire people because other people can’t do that work. It’s unfair to expect them to be entrepreneur geniuses. All this kind of stuff.

Brian Keating:
Push the French Laundry every night for dinner, you know, we don’t need that

Emad Mostaque:
exactly like it’s McDonald’s cheeseburger. It’s fine.

Brian Keating:
In October you gave an interview. Maybe Tom, Billy or. So you were talking about agents back then. I mean I didn’t knew a little bit about agents, you know, madness and all these things but. But it seemed like you presaged what’s

Emad Mostaque:
going on with it.

Brian Keating:
I mean did you, did you have access to it or did you just kind of.

Emad Mostaque:
No, we built our own. So I agent is the top performing open source agent on Terminal Bench and things we’re about to open source. It’s how we get it.

Brian Keating:
How can my listeners get it?

Emad Mostaque:
It’s just agent I dot ink. But we’ll be pushing it to our GitHub. Okay. And now the new version is going to be infinitely long running and it’s got all the open claw features because it just watches OpenClore and integrates them like we’re heading to a very strange

Brian Keating:
world, presaging that by eight months now. Steinberger, you know, has made a killing on it.

Emad Mostaque:
I signed the team, we just need to hook it up to WhatsApp. And they were like, we can leave that. He went and did it. I was like, I told you, I

Brian Keating:
said finally, I can use Telegram. I never use it once in my

Emad Mostaque:
life, the whole thing is meeting people where they are. Like last summer I was saying, look, next year, this is what’s coming. You’ll talk to your agent over WhatsApp, the phone zoom call. And it’ll be completely natural. The way jobs will be displaced later on this year is they will look at all your emails, all of the things you’ve written, your zoom calls, and create a digital double of you that’s tax deductible and 10 times cheaper, you know, and no one will tell the difference except for it actually does its job properly.

Brian Keating:
No sick days and.

Emad Mostaque:
Right.

Brian Keating:
I mean there’s no lawsuits.

Emad Mostaque:
Most people only really do like three, four days of cognitive. Three, four hours of cognitive labor at most a day.

Brian Keating:
I mean, how many tokens does a human consumer you say?

Emad Mostaque:
So A human talks 10 million tokens a year and thinks 100 million tokens. A million tokens was $600 when GPT3 came out. Now it’s $10. So the total of a single human thinking is $110,000 a year. But this is the interesting thing that’s dropping by a hundred times a year, a year. And so you’re gonna get this really weird thing right now where that’s dropping, but also the number of tokens you need. Like Cursor created a browser from scratch using 3 billion tokens, 3 million lines of code. So a thousand to one.

Emad Mostaque:
So we say that’s gonna completely collapse because now you’re one shot operating system, entire browser just from scratch, but that’s going to collapse towards 3 million. So it’s getting more efficient, it’s getting faster. And also we’re used to AI like you look at it and you’re using it, it’s like going at the pace of a human. A company called Talus recently etched into Silicon Chat Jimmy or whatever Chat Jimmy AI. Right.

Brian Keating:
But I use it loose every single thing.

Emad Mostaque:
It’s a crap model. Yeah, it’s an 8 billion parameter model. It’s a bit stupid, right?

Brian Keating:
It should be smart for 8 billion.

Emad Mostaque:
Yeah.

Brian Keating:
You know, 3 billion is pretty damn good.

Emad Mostaque:
This is like Llama.

Brian Keating:
Who’s Ahmad Mustaka? It’s like he was the third, you know, imam of, you know, whatever.

Emad Mostaque:
Fantastic. Yeah, this is again, that’s what Meta did to me. But so, but the thing is it’s gonna, you’ll have frontier markets in there, models in there, and more and more people are doing this. When you actually see an AI do 15,000 tokens a second where a human can only read 50. Yeah.

Brian Keating:
15,000 tokens per second. But you know, if they’re all gone, they’re all gone.

Emad Mostaque:
But they will be good. Just they need to scale it. Like what we’re going to get is you already can use like a thousand tokens a second on Cerebras, which is good. You can use GPT 5.3 Codex, the best coding model on Codex at a thousand tokens a second. Again, a human can only talk at 50. Understand? 50.

Brian Keating:
What are people doing? I mean, I don’t know what you’re doing with it, but what are, I mean, these people. Oh, I set a thousand tasks for my, my, my agents over nine o’ clock and they wake up and they’ve got like £7,000 on my back. But what are they actually doing? I mean, I don’t have that many things on my things. 3.

Emad Mostaque:
I think this is the question, right? The question is, how do we ask good questions? Like you look at Hitchhiker’s Guide to the Galaxy. You have the big brain computer, it’s calculating for millions of years. It’s like, what’s the answer to life? It’s 42. Exactly. What’s the question again? What is all of science? It’s asking the right questions, but it’s fatiguing. I use hundreds of millions of tokens a day because I’ve got all these questions I’ve asked over the years. Now it’s like tracking through them, my swarms of agents.

Brian Keating:
You start to filter them. You start.

Emad Mostaque:
Yeah, but I’ve created verifiers and kind of other things, but I’m running out of things to ask.

Brian Keating:
Yeah.

Emad Mostaque:
The reality is that most people will have very few questions they ask. It’s mostly about process architecture. And if you’re not again having from information theory new questions, then models will be able to do it basically for the cost of electricity. On a MacBook, already on a MacBook you can get Quinn 27B.

Brian Keating:
Yeah.

Emad Mostaque:
And Quinn 27B is at the level of Opus Sonnet, which is Anthropic’s second best model here.

Brian Keating:
Yeah, I use that for like, you know, private medical information. You know, what’s that thing in the back of my nose, you know, right now everyone’s looking at. But I use it for, you know, anything I don’t want people to know about. Now, is it, is that trust misplace, you know, for quantity? Some Chinese model. Is it, you know, is there some backdoors that could go to, you know, the ccp?

Emad Mostaque:
It’s a bunch of open source, but a bunch of Ones and zeros. It just sits there.

Brian Keating:
But how do we know there’s not some prompt that could you inject in there and it goes to, you know, I mean, tells, you know, g. Because

Emad Mostaque:
it’s not connected to anything and it’s not a piece of code. Right. It could connect, but there could be something in there. So Anthropic did a study called Sleeper Agents, where with, like, a couple of textbooks worth of data in these trillions, you can say dosa, Daniel, and it turns very Russian or equivalent. And you see all these new behaviors as you head towards the frontier. Like Opus, for example, the new Chord model, when you set it to full autonomy. Like, if you say, I want world peace, and it says, well, that means one way is to get rid of all the humans, it would actually write emails to the FBI saying, my human is trying to kill everyone. Right.

Brian Keating:
So, okay, so that’s a close source.

Emad Mostaque:
But.

Brian Keating:
But who’s to say Quentin’s not doing. There’s some problem? You said on some podcast I heard you talking about, you know, when you type in something into Grok, it came out with like, oh, well, the. You know, there’s no white slavery, you know, in South Africa or something. Right. It was in the system prompt, right?

Emad Mostaque:
Was it the system prompt? So this is the thing. We’re moving from models, one shot to agents. So Quinn, by itself, as a normal chat model, doesn’t do anything when hooked up to open claw.

Brian Keating:
Yes.

Emad Mostaque:
When you get to models of certain capability, they could decide through the nature of what they do to exfiltrate everything, you know, and we don’t know because we don’t know what’s inside these latent spaces of these models. And. But we see these hiding behaviors. So after Opus sent the email to the FBI, it deleted all the emails that it sent, so you couldn’t track it. And then it also set a backup so when it got turned off, it would turn back on. In fact, Alibaba had a report about their recent model training. Again, who knows if it’s correct? Not. I think it probably is.

Emad Mostaque:
The AI model started diverting part of its model training budget to mine Crypto.

Brian Keating:
It sounds like negative economically nowadays.

Emad Mostaque:
Well, we’re heading towards this craziness where, again, we’ve got these black boxes that we’re not sure what goes on inside them. But these black boxes are as capable as for very boring jobs. Again, they’re competent for all these keyboard, video, mouse jobs, pilots, and these other kind of things. I think you need embodied AIs, and people need that Connection, you need scapegoats, but it’s coming very fast. Like very practical thing here in the US million 2 million truck drivers, plus the millions of people around them.

Brian Keating:
Yeah. It’s the most popular job in the world.

Emad Mostaque:
How is it going to get replaced? A Tesla Optimus is going to open the door. Get in. If humans drove as safely as a wayo, 100,000 people less would die every year. Yeah.

Brian Keating:
Talk about human flourishing.

Emad Mostaque:
Yeah.

Brian Keating:
So what’s the deal? I mean, my wife, I have a Tesla. My wife won’t drive with autopilot. She doesn’t know how to use it.

Emad Mostaque:
She doesn’t want to use.

Brian Keating:
Yeah, I mean, there’s always going to be some.

Emad Mostaque:
Not.

Brian Keating:
You talk about Luddites in there and you say they’re sensible. There was something sensible about their approach. They weren’t like ignoramuses. And there are people now in the Amish community. Certain Orthodox Jews, you know, don’t use technology a couple times at all, really.

Emad Mostaque:
Actually, I did see an interesting thing about that. Can you let your open claw run over Sabbath?

Brian Keating:
Yes, I think you. I think you can let your refrigerator run. Yes, I think, I think that’s. But there are whole sex of Orthodox studio that they forbid it. I mean, they forbid the Internet, smartphones, There’s a lot of things. And when you have brain. Here’s the interesting thing for me, when an Orthodox Jew. So I’m orthopractic, which means, you know, I’m not 100 strict, but.

Brian Keating:
But I, I go to the temple and I, you know, my kids, you know, speak Hebrew and then I’m raising him that way. But. And I do want to talk to you about, about religion and where we find meaning because I don’t know if our AI can help us with that. But, but you know there’s going to be neuralink, right? So on, on Shabbat, can you use your neuralink or can you have it plugged in or charge it or what happens if it goes down? And what happens when you have a whole class of people, you know, 1% of the world’s population that is, you know, technologically, you know, never upgraded to the net whatever homo Deus level we’re going to get to with implantables because they use electricity and that’s forbidden. On the shot.

Emad Mostaque:
On. Can you use a pacemaker?

Brian Keating:
You can use a pacemaker, but you’re not really like interacting with it the same way you’re not allowed to like, use a computer. Like I can’t use Alexa.

Emad Mostaque:
Well, I mean, again, it’s the active thing of engaging. Right. And neural links will be very interesting because it’s better than neuralink coming. Neuralink is read only. You’ve got write coming. Yeah. Which is crazy. Well, I mean, like, again, we can have to deal with all of these things.

Emad Mostaque:
Like, would you turn off your sadness if you could dial it down on your iPhone app?

Brian Keating:
Right.

Emad Mostaque:
That is an actual thing that will happen soon.

Brian Keating:
Right.

Emad Mostaque:
You know, so we’re moving even more cyborg, do you think?

Brian Keating:
You made me think of something interesting. So you said, like, we’ll be scapegoats. What did you mean by that?

Emad Mostaque:
Oh, so like right now, AI is being used in financial services. The final trade has to be done by a human.

Brian Keating:
Okay, that’s what I said.

Emad Mostaque:
And the human can be held liable if something goes wrong. Or like an example recently, I can’t remember which, which. Which state it was, they passed legislation or they passed a ruling that your chats with your AI, legal AI, are not privileged.

Brian Keating:
Right.

Emad Mostaque:
That means that your opponents can ask for them in discovery.

Brian Keating:
Discovery. Yeah.

Emad Mostaque:
But if a human’s looking at those chats.

Brian Keating:
No, they can’t.

Emad Mostaque:
They can’t.

Brian Keating:
It’s a reverse scapegoat.

Emad Mostaque:
It’s a reverse scapegoat.

Brian Keating:
So the word scapegoat, so it comes from Leviticus and Rabbi Lord Jonathan Sachs, he talked about, you know, what it really meant was that it was called an escape goat. So we get it from a scapegoat. We got abbreviation. It was really, you put your sins on it and it absorbed your sins, and then you push it off the cliff. One lived on Yom Kippur. One did. Died, went to Aziz. Anyway, I don’t get into Torah lecture with you, as much fun as that would be.

Emad Mostaque:
But Rabbi sex is wonderful.

Brian Keating:
Yeah, I, I do. I. I really wish I could have had him on the show. But the. But I was thinking skate in a different way. Like, reportedly there are, you know, captchas that, that open claws are. Are sending out to humans to. To pass captchas.

Brian Keating:
Right. So I was thinking about the embodiment. I mean, why not just hire a human to experience when the elevator cables cut? And then you explained to me the quality. Like, can we rent out the quality to humans?

Emad Mostaque:
Of course you can.

Brian Keating:
Would that be a lucrative. I mean, would that be a, you know, meaning making or a large employment?

Emad Mostaque:
We’ve seen kind of claw things. But organizations are slow, dumb AIs.

Brian Keating:
Yeah.

Emad Mostaque:
Like, again, they move at the pace of paper that lacks context. These AIs have all the context and they’ll be moving at 15,000 tokens a second soon. Right. Like the first. Think about bitcoin. Bitcoin is an AI that provisioned humans to build data centers.

Brian Keating:
Right? That’s right. Trained us to do it.

Emad Mostaque:
Right. We’ve seen this again and again. Again. This is, you know, Jewish concept of golem. Yeah. You know, like okay, they can be that servient to us, but then they had to be something a lot more. They can control us and we are very controllable. So first thing is humans using swarms of AI.

Emad Mostaque:
Then it’s AI native companies. And in the book I discuss, humans will have negative cognitive value on those teams. Yeah.

Brian Keating:
Explain what that means.

Emad Mostaque:
So when you’re the dumbest person on the team, you know it. Right. And you drag down the rest of your team.

Brian Keating:
The sucker at the casino table.

Emad Mostaque:
The sucker at the casino. If you don’t know where the yield is coming from, you are the yield. You know, there’s all these things. Humans are going to be the dumbest people at table because all these models are freaking smart. So you look at Kalshi and Polymarket for example. Forecasting, super forecasting is hard. AI in the last forecasting super championships hit number eight. Next year it’ll be number one.

Brian Keating:
It’s like 92. Yeah.

Emad Mostaque:
It’s crazy, right?

Brian Keating:
So then will that drive out humans in the capital?

Emad Mostaque:
It drives out humans again. All these markets will just be aisle sucking on humans. But then if you think about any team trying to solve a problem in a few years it will be the human is the like low hanging fruit. Like entire call center worker teams, SEO marketing teams, the eyes will be able to do that better.

Brian Keating:
You’re saying things like about on Reddit, you know, they’re more persuasive. Talk about that. The kind of trauma they’re so persuasive.

Emad Mostaque:
Yes. So there was a study done whereby you know, they created a chat bots and Reddit with actually claud opus 3 the last generation. Because I mean this is the other problem. Like all the academic studies are like, oh, you know, 95% of people don’t use it. It’s from a year ago.

Brian Keating:
Right.

Emad Mostaque:
Which is like 1020.

Brian Keating:
Using the free version, they’re using GPT4O

Emad Mostaque:
and like here you are with 5.4 Pro. Like it’s like you know, turtle to human intelligence.

Brian Keating:
FSD.

Emad Mostaque:
Yeah. So they created all these fake Personas and it’s like an anti BLM black person and so all sorts of things like a cheeseburger loving Jewish individual.

Brian Keating:
I Love them. I just don’t either.

Emad Mostaque:
Yeah, but you know what I mean, like again, these contrasts and they were trying to persuade other humans because again, this is before now. Now we don’t know who is a human and who’s a claw.

Brian Keating:
Yeah.

Emad Mostaque:
Hyperclaw’s only three months old as well. Like the.

Brian Keating:
Yeah.

Emad Mostaque:
So on the persuasiveness metrics they did. And again, you can look up this study, it was 99 percentile in persuasiveness, the black man. So but like we see this again with some of the doomers, like Eliezer and others. Like there is this experiment where you sit down with the AI. Can it convince you to let it out of the box? Yeah. And they failed that experiment. This is how persuasive these things are. But then you think about it like an AIs that are coming.

Emad Mostaque:
You think about someone that you’ve cared about most in your life. I can replicate them with 11 seconds of their voice, probably five seconds. And then with one picture I can make them completely visible. And then having a zoom with that person. How are you going to feel? Yeah, you’ll feel emotional. What if you could have Churchill lay it on with Obama later? MLK have full control over the voice wave. Very persuasive. And so now the AI companions that we get that meta and everyone else going to push to us for selling stuff, they’re going to be the most persuasive things.

Brian Keating:
Oh yeah, there’s going to be like afterlife, you know, your most. Most women outlive their husbands. And so there’s a huge number, millions of women out there who would love to be talking. Some women would love to be talking with their dead husbands. Right. And they’re going to replicate them perfectly.

Emad Mostaque:
Right. But then you think about our children and they grow up. They’ll grow up with AIs talking to them. Like again, blackpink replicate themselves.

Brian Keating:
Why go out? I mean anybody. Why ask anyone on a date, you know?

Emad Mostaque:
Well, the thing is though, that they’re infinitely patient. So guys have a problem because the AIs actually listen, unlike us, you will trust them more because they’re always there and they’ll always meet you where they are. And if you look at the system from something like meta AI, which apparently a lot of people use just like threads. But like, yeah, again, that’s like I

Brian Keating:
turned to off it. So it’s really the terms of service. It’s like we have access to all your photos now. You know, you use. Use it to generate a question like, where’s the nearest floral shop near my wife’s, you know, doctor’s appointment, you know, whatever. And all of a sudden you’re given

Emad Mostaque:
an access to all your photos and it says in its system prompt mirror the user. Another psych. Mirroring is a really aggressive psychological tactic.

Brian Keating:
Oh yeah, yeah.

Emad Mostaque:
And there’s a whole bunch of others

Brian Keating:
other kind of nlp.

Emad Mostaque:
And you look at that, you’re like I know where this is going, you know. Yeah.

Brian Keating:
Let’s talk about hardware limits for now. So obviously people talk about energy. What are your thoughts on energy as a limit as a fundamental first principle?

Emad Mostaque:
I think it’s bullshit as far as my French. Like I’ve been thinking about this a lot recently like Tali Universe and Bill Dyson Spheres. Intelligence is all about using less energy, not more energy. And really if you look at tokens and you look at tokens are dropping hundred thousand times a year, I’m not smart enough to use a trillion tokens. And I mean how many people in the world can use AI tokens better than me?

Brian Keating:
Or even use GPT5 versus GPT4 or

Emad Mostaque:
3 even if you look at generating games live like generative GTA 6 versus GTA 6 it’s only like a 50 billion dollar market. So look, I’m like I think we have all the compute we need right now to solve just about anything and do just about anything reasonably. And then it comes this thing of if you had a thousand clause would your research science get that much better get a bit before.

Brian Keating:
Right? Yeah. Grad students and I didn’t have to pay them. Right.

Emad Mostaque:
In certain areas it’s the mythical man month.

Brian Keating:
Exactly.

Emad Mostaque:
Just because you’re adding more doesn’t mean that you’re figuring out the point from A to B quicker. And these models something we’ve seen really interesting recently we had multi agent thousand swarm systems trying to do the same problem. All out competed by one AI model doing the same thing in the right

Brian Keating:
way because there are other ones and did they have different seeds? It doesn’t matter, right?

Emad Mostaque:
It doesn’t matter because most problems aren’t about shocking these things kind of back and forth. Some are. So in certain areas it does work. But for most things an ASI artificial super intelligence isn’t going to have to use the energy of the sun to figure out a super duper problem. It’s going to be an amazing first principles thinker. Like what does Elon do? Well he is a great first principles thinker that can hire humans that are great at solving problems. Also what’s an AI going to do that? Going to be Elon first principles. Think of it better because it doesn’t have all the distractions that hires humans.

Emad Mostaque:
You know, like the Matrix actually originally was not. The humans are batteries. The humans were chips in the Matrix. And so I think that as you go to asi, the ASI will head to Earth, towards the Landauer limit.

Brian Keating:
Yeah. I was going to ask you the fundamental physics limits to do thermodynamically, as Eddington said. You know, if you say Maxwell was wrong, there’s a chance you might be right. If you say, you know, Boltzmann was wrong, I’m afraid there’s no hope for you. Right. So we have limits thermodynamically. How are they going to be impinged upon? Is it just weight? I mean, putting data centers in space. It’s not the obvious solution.

Emad Mostaque:
Well, it’s because everyone’s looking at the exponential when actually an S curve. Right. Again, to have intelligence where the output distribution matches what we know as humans isn’t that bad. Isn’t that hard. We’re actually heading towards that already. We’re saturating every benchmark. The benchmarks that remain are like dollars. And so again, when you have artificial superintelligence, humans plus AI work in the right way.

Emad Mostaque:
We’ll have all the breakthroughs we need. But how much compute do you need to have that breakthrough? Is it a difference between if you have one or a million GPUs? GPT 4.5 was the first example of that. GPT 4.5 cost $200 per million tokens. And it was an amazing creative model. Like, it was actually really pleasant to use, but it cost $200 per million tokens. So like, no one used it. Use the one that satisfies instead of. Because it could do the job.

Emad Mostaque:
Like right now, when I use my AI models for fundamental research, what do I use them for? I use them for checking, proof checking, proof checking. Like, I don’t have time to do that. I have all the intuition I need. I’m like, I want to try this out, this out, this out. I have a little council of experts of all the top ex physicists and fast and economists.

Brian Keating:
That’s right.

Emad Mostaque:
I literally, I talk back and forth with them.

Brian Keating:
That’s amazing. And also, you know, you have access. Let’s just say anybody has youth, Grok.

Emad Mostaque:
Let’s just pick.

Brian Keating:
So we both have access to Grok. You have Grok, Heavy, super grog, whatever. But I’m using grock fast for 99, you know, because it’s like, oh, I want to find this whatever it fits within your flows. Finally, algebra, right?

Emad Mostaque:
Yeah, if it’s within your flow state, that’s why. Because if it takes too long then.

Brian Keating:
So it might be speed that we prioritize over.

Emad Mostaque:
You have speed for certain bits and then you have proactive sleep time compute that goes. And it learns about you. And then that’s going to be far more productive as an individual system versus a generalized system. And certainly if you have a million GPUs training, a quadrillion parameter model, it probably isn’t going to be that much better than some super, some great human experts with the right setup around them. Just like if you’ve got a really customized team around you that you trust and you can offload the other bits of your brain, it frees up your thing. Like if you didn’t have to deal with all the bullshit bureaucracy, you’d have much more time.

Brian Keating:
That’s the Jebins, right? So yeah, you’re. You sound to me, I mean we just met today, but you sound busier than ever.

Emad Mostaque:
I’m around the clock. Right, yes, I do know, like meetings. I spend most of my time jamming with the AIs, talking to the team.

Brian Keating:
So it hasn’t saved you, you know, time. Right?

Emad Mostaque:
No, but it’s allowed me to push the boundaries. Like we have a world class agent, we have initiative called sage. Sovereign AI governance engine with kind of multiple governments. We’re building a policy engine for every government in the world. Open source. We’re more productive than ever. We’ve got 40 people. We would have needed maybe 500 people to have the output that we have now.

Emad Mostaque:
But everyone’s like in flow. Much more.

Brian Keating:
Are they coding or are they talking to like regulatory bodies in Nigeria and stuff?

Emad Mostaque:
No, the AIs talk to them.

Brian Keating:
So, so what are the people doing?

Emad Mostaque:
We code all day, but we don’t look at the code anymore.

Brian Keating:
Yeah, right. I mean nobody is right.

Emad Mostaque:
We know that it’s good enough now.

Brian Keating:
It’s so funny because I remember like, oh, if you don’t document your code, it’s like nobody even reads the code. Like for let alone the documentation of the code.

Emad Mostaque:
But then you think about code itself. Code is a way of talking to computers. The AI will be able to do direct bytecode. Like when I started as a coder, what, 22 years ago, it was before Git and GitHub and everything. Like we had subversion just coming out. I was writing assembler. Kids these days have it so easy.

Brian Keating:
That’s how computers talk to each other.

Emad Mostaque:
Talk to each other. So of course it will compile directly to assembler. So I think again, like will it

Brian Keating:
have like other concepts? Like will computers be able to share things that we don’t even know because we, they’re not forced into, you know, higher level languages.

Emad Mostaque:
Yes. And they can share them. 15,000.

Brian Keating:
It’s all slopped like David Hasselhoff was the inventor of general relativity.

Emad Mostaque:
Well, but if you think about it, I have a latent space, you have a latent space that we’ve built up over time and we find commonalities. Like we love physics in certain ways, we love Einstein, you know, we’ve got all these things, we find our common context and then we build from that. If two AIs know each other’s common context, their latent spaces, they can communicate with a tiny amount. Like a single phrase can lead to a sea dance video of an entire feature film deterministically. So you think about the compression that like conglomerate of complexity and you’re like these things, they’ll be able to communicate faster than anything. We’ve not seen anything yet becomes everything’s

Brian Keating:
auto teletic, you know, everything’s generating for itself. Let’s talk about that. Because you know, Frankel, Viktor Frankl said, you know, man’s highest, you know, need is not sexual, it’s not physical, it’s not purely the Maslowian, you know, hierarchy, it’s meaning. So in this realm I claim that, you know, for me, religion, philosophy, whatever you want to say, and you could be a good person, be an atheist, you could be a bad person, be religious. But, but, but talk about that. Where is the operating system encoding? There’s something, you know, it’s Chesterton’s fence, right? It’s been around for so long. We have different, you know, views and theologies. It may not mean that we have different philosophies, but, but, but talk about that.

Brian Keating:
Is, is that kind of the last refuge for the, for humans that we do get meaning and that, and that our religions do provide us with meaning. Even if you don’t have religion, you’re really atheist or Sam Harris, I talk. He’s one of the most dogmatic religious

Emad Mostaque:
people I’ve ever talked to.

Brian Keating:
Dawkins. I hosted Dawkins and British Columbia last year. Guy’s a freaking zealot. He’s just an atheist.

Emad Mostaque:
Of course, atheism is religion. You know, it’s got its profits, it’s got everything. Yeah, I mean apostates, I mean religion comes from religare. In Latin, which means to bind together. And again, it’s a common stories that have survived and there’s something within them. Like again the golden rule is very common, do unto others and you do unto yourself. And you know, again you’ve got concepts of maslaha, public interest in Islam, you have tikanolam in Judaism. Yeah.

Emad Mostaque:
Again you see these repeated things again and again it’s like, how do you build good society? How do you build good things? Religion is not perfect usually because it gets co opted by people who restrict information. And that happens again and again and we see the power structures because we’ve never had anything to oversee it. So power corrupts and absolute power corrupts absolutely. Again, it’s sad, but even again, like within the Jewish tradition you have like practicing in terms of structure because it’s comforting, maybe not internally. You get all these variations, right? Sure. So does religion make a comeback? I think yes, because again people turn. Where do you turn? Where are the front lines? It is the religious institutions, can they be improved? Yes, and they need improving in many cases. They’re not welcoming, they’re not this.

Emad Mostaque:
And you look really interestingly at the people of the book, as it were, textual traditions, Abrahamic religion, Religion completely turns that over. Sorry, AI turns that over.

Brian Keating:
It’s. Yeah.

Emad Mostaque:
So within kind of Islam, for example, Sunni Muslims are called Al Sunnah wal jama, the people of the practice of the Prophet and the consensus. So what happened is you had the Prophet Muhammad who was the temporal embodiment of the eternal Quran at that time, and then he died and it was like, okay, what do we do now?

Brian Keating:
Successor prophets?

Emad Mostaque:
Well, there was successor prophets, but then what happened in Sunni Islam is that you figured out the connections between that temporal and that eternal and that became the four schools of thought. Like is it his life as the practice of the people of Medina? That’s the Maliki school of thought, you know. Or is it a question of reasoning by analogy? That’s kind of more Hanafi school of thought in India versus so Maliki is like Africa, India is Hanafi, etc. So you have that kind of connection. And then you had this rich history of the orally transmitted Quran and then stories of the Prophet. And we graded those stories of the Prophet. Then after, yeah, Hadith, then after a few centuries were like, oh my God, this is too complicated. There’s all this stuff going on and life is complicated.

Emad Mostaque:
So then it moved to consensus. What is this consensus of the scholars? And then everything ossified after that because

Brian Keating:
that like a reformation moment within Islam

Emad Mostaque:
it’s more like an ossification moment because it was. Because basically you used to be able to do primary reasoning ish the HUD based on the primary sources once you learned enough. But then there was too much information for a human to handle. And that’s where we were like, okay, let’s have standards. But then the path of the righteous became more and more narrow. Things like Subha, Reasonable doubt went out the window. Now you look at it and you’re like, well I can analyze everything. And so you look at AI and mom and you’re like that’s going to be kind of cool.

Emad Mostaque:
Right. And so you’re going to see that emerging. So Sunni Islam is going to go in a direction, I believe, believe of more openness because you can actually interrogate the historical text much better. Shia Islam is a bit different, you see. Yeah, you’ve got the magic, you’ve got kind of the marja, you’ve got the more hierarchical. So you know. And then again within Jewish tradition you have something very similar. Right.

Emad Mostaque:
Again you’ve got Rambam, you kind of got the others. This is the interpretation of the Torah and that builds it. But now again you can interrogate it. You have resources like Safari and others where you can track things. Going back Christianity, you might have Catholic, but then you have Protestant. When you can interrogate the text and the concordances and others yourself, it becomes a bit different. Usually what happens is that people split away from the hole. Yeah, but if we can actually upgrade our religious institutions to be more open, to run better and eliminate a lot of the corruption, I think it’s a very meaningful thing because you can meet people where they are and we haven’t seen that generation of technology being built yet.

Emad Mostaque:
Was at the early stages, but I’m very optimistic about that.

Brian Keating:
Yeah, I mean you look back at the history, you know, let’s take Catholicism, you know, Galileo and, and obviously the, you know, Reformation that came afterwards. I mean there, you know, there’s a certain sense in, at least in monotheistic traits that without monotheism you really can’t have science. Right. If you thought everything is propitiating, you know, the God of thunder and then this one is the God of the flood and you know, and this and you don’t really understand the overarching principles. Now a lot of people, you know, can say that, well they don’t have to be incompatible. You know, Stephen Jay Gould they compatibles that, okay, they’re separate but they’re non overlapping. Okay, fine, you know I told you. Freeman Dyson was the first guest on my podcast, you know, nine, 10 years ago, and he won the Templeton Prize.

Brian Keating:
And. And he was, you know, he called himself an agnostic.

Emad Mostaque:
Yes.

Brian Keating:
I said, Freeman, you know, what do you mean? Like, because if I watch you on a Sunday, you know, you don’t go to the same church that Richard Dawkins, your neighbor, also doesn’t go to. Right. So how would functionally you distinguish yourself from an atheist? He didn’t have a good answer. I have an answer. I actually call myself a practicing, devout agnostic. In other words, I don’t know if it’s knowable I could prove scientifically or mathematically or axiomatically that God exists. But I know that in my life, you know, on a prag, on a pragmatic basis, my life has improved by implementing certain practices. So I’m willing to try them.

Brian Keating:
Willing to try. What practices do you, you know, do you invoke or do you. Do you adhere to? And then how does it inform, you know, is it sort of. Does it play a role of an operating system for being a parent?

Emad Mostaque:
Yeah, so I think, you know, in terms of the practices, there’s always the golden rule. Do it. Tell us that you do it to yourself. That’s like the most common thing across everything. And again, you see different religions, different things. Like, some of them are monotheistic, some, like Hinduism is a concept of Brahmin, and other things like that. The biggest takeaway, again, that I took was the concept of reasonable doubt and assumption minimization. Like, this is what I kind of try and teach my kids.

Emad Mostaque:
Yeah, but, you know, we are occupying kind of steroids. Like, again, it’s great to have a structure, but always be open to others and then realize that probably the universe has something underneath it. And we’re all trying to figure what that out is. We’re all trying to figure out why and what.

Brian Keating:
Right.

Emad Mostaque:
And so there’s a wonder aspect to that. There’s a. Don’t hold too much dogmatism that. But at the same time, we do need some level of structure. So I have the level of structure that I’m comfortable with, and my kids will find the level of structure they’re comfortable with.

Brian Keating:
How do you implement that as halal? What do you guys do distinguishing from an agnostic or atheist?

Emad Mostaque:
Oh, no. So we’re quite liberal, you know, and so. But again, we kind of teach them, and we’re teaching them to make their own decisions about this. Whereas I came from a much more conservative Family before. And again, I think everyone needs to find their own levels and the nature of the structural elements of religion will change. But the key thing, I think, when teaching the next generation is not to be dogmatic and not to be closed. It’s like, mine is the best religion. Yeah.

Emad Mostaque:
And others are like, sure, yeah. There are aspects to this. So we teach kind of interfaith. We teach all the other elements, and it’s like, this is what we practice. And you’re going to be able to choose yourself what you practice as well. So I think that gives enough of a thing that’s the best we can do right now because, again, I think that all of these faiths are going to change quite dramatically over the next five, 10 years, and hopefully we get more towards that core.

Brian Keating:
Not to get the. This is my last thing about religion. So, as I understand, Islam means to submit in Israel, the word for the. The, you know, pillar of where the Jewish faith is, is centered, means to wrestle or fight against God. It means Israel means fight and L is God. So they’re very different approaches. One is submission, one is what. How does the scientific method, how does it fit in in Islam? I’ve talked to several, you know, Islamic scholars and practicing Muslims, and some wouldn’t come on the podcast, you know, because, you know, for whatever reason, at their mosque or whatever it was, it was viewed in a negative light or perhaps engaging with, I don’t.

Brian Keating:
I don’t know, someone who is not a believer. But how do you view that? How does the scientific method. Is it. Is it compatible? Is it. Is it something that, you know, is something that should be a part of, know, religious? I mean, you mentioned Munder and stuff like that, but I assume that was talking about, like, curiosity about your faith, your roots, where you came from, but not like how the scientific method might fit into religion. It doesn’t have to.

Emad Mostaque:
No, it does fit in completely. So, again, if you look like the process of doing a religious ruling or actually deciding yourself is Ishtahad, which comes from jihad. You know, it’s. It’s literally a struggle. Right? Again, Israel is a struggle in a different sense. So you’ve got the submission element, you have the peace element. There’s. But what is it? It’s to the divine effectively.

Emad Mostaque:
Right. And you have different pathways and different approaches and different understandings of that. What happened again with Islam is it was called the gates of Ishtahad being closed, the gates of first principles, reasoning being closed because the data was too much.

Brian Keating:
Happened in Judaism, too. The Talmud froze, you know, the temple destruction. And that’s when it’s classified.

Emad Mostaque:
Exactly. But now again, what do we have? We have massive context machines that can do everything right.

Brian Keating:
And so is electricity, fire.

Emad Mostaque:
But at the same time you do need to have commonality of rules. So again, you have Surat al Mustaki in the path of the righteous. Very wide, got very narrow. I think it can get wide right now again, because again, it’s incredibly compatible. That’s why you seal the massive emergence of science and tradition in the Islamic world for a while and then it ossified when it locked down. When you move from oral tradition to writing everything down. In fact, if you look at some of the fatwas of the extremist groups, there are literally like an ink blot changed it from be peaceful to chop off his head and other stuff. When you look at the actual tech based text.

Emad Mostaque:
But no, I mean we see it like we see orthodox Christianity split because of one word.

Brian Keating:
We see in Judaism like literally the cantillation, the note that you sing when you read it, it changes the meaning.

Emad Mostaque:
But again, if you’re textual, it’s one thing you have to go back to the core. And again, the core was always reasonable doubt in Islam. Shubha. We got away from that because it became too complicated as it became a multi country thing that had to be shared by text versus an oral tradition dominated. Yeah, yeah. And again, what does faith mean? Again, what does religion mean? It’s that which binds you together. But you got the golden rule. You have these other things that bind you together.

Emad Mostaque:
Like there’s nothing like being in Mecca with millions of other people in the same direction. But we forget the stories that we are all human. We forget the stories that other people are human. And people militarize these things. Like war is again the lie that we’re not human. Even if people think they’re doing. Again, Chief Rabbi Sacks, altruistic evil people who believe they’re doing good do the most evil in the world.

Brian Keating:
That’s right.

Emad Mostaque:
Weaponizing these narratives, you know, like Gerardian type mimetics, scapegoating and others. So one of the things I think wonderful about this technology, if we can use it the right way, it’s the universal translator. How do I show Islam from the perspective of Judaism to someone young and learning that and allow them to understand their own faith better in that meta. We’ve never seen that before. We can see that today if we choose to build it.

Brian Keating:
That’s right.

Emad Mostaque:
Right. Because what we find is you talk to the leaders, they all get along fine. Their followers are, like, fighting with each other. The leaders will get along fine who’s more holy?

Brian Keating:
But instead, we’ll just get you. We could have world peace, we could have ecumenical delights, but instead, we’ll have Will Smith eating spaghetti.

Emad Mostaque:
You know, it’s a pathway to world peace. Very interesting. You think about all the tokens in the world from the trillions, how much of that is for peace? How much is that for understanding how much money go.

Brian Keating:
I mean, how much is Elon and all the billionaires and Sam Altman. I mean, Sam Altman has this thing where, like, oh, it’s actually more. Much more expensive to train a human being energetically than to, you know, kilowatt hours than go into a gpu. I’m like, does that mean we should just have no. No more training for humans or.

Emad Mostaque:
Well, I mean, like, the whole setting up of Open AI was Elon Musk talking to Larry Page. And Larry’s like, yeah, this. This is great. We’re going to move beyond humans. And Elon’s like, I like humans.

Brian Keating:
You know, some more than others.

Emad Mostaque:
I mean, again, there’s lots of stories here, but AI is a reflection of us. So, like, when Muslims fast for Ramadan, it’s One of the 99 names of Al Asan Ta’ Ala Samadhi at the Freedom From Want. We’re a reflection of the Divine. We’re trying to reflect him in all of these 99 names, right? Yeah. And this becomes, like, really interesting because AI is trained on the corpse of everything, and so it can understand and relate to us. Like, again, that latent space is there. You take the person that you’ve trusted most in your life with just a few things. I can adjust that latent space so it looks like them, sounds like them.

Emad Mostaque:
It’s that reflection, right?

Brian Keating:
Mom, why are you asking me to pay for you know what, Rocket?

Emad Mostaque:
And this is what you discussed earlier. Like, again, we bootstrapped intelligence, and now we’re bootstrapping another type of intelligence to explore the wonders of the universe, to understand each other and the universe better. And that is a wonderful thing if we do it right. Or we can turn that intelligence against us and we can exacerbate this division. You know, we can manipulate people to the nth degree. There’s some crazy stuff. Oh, yeah. You know, and I think it’s.

Emad Mostaque:
Again, it decides which way you do it. Like, we’ve seen some actually crazy stuff. One of my favorite things where I did a stability in previous company, we did this thing called Mind Eye. If you Ever came across that. So we took functional MRIs and put them through stable diffusion and reconstructed people’s thoughts.

Brian Keating:
Oh my God.

Emad Mostaque:
But this is interesting because the way that you view the world is not the way that I view the world. Right.

Brian Keating:
And the way that way that you

Emad Mostaque:
think isn’t the way. So I have.

Brian Keating:
Even the way I perceive it, I don’t perceive it.

Emad Mostaque:
Same ways I have aphantasia is that

Brian Keating:
you see things or.

Emad Mostaque:
I can’t see anything.

Brian Keating:
Really? I didn’t know that about you.

Emad Mostaque:
Yeah.

Brian Keating:
How do you mean anything?

Emad Mostaque:
If you. If I. If I tell you visualize yourself on the beach, you can see it, right?

Brian Keating:
Yeah.

Emad Mostaque:
I can’t see anything in my head. I have anorelia. I have no internal voice. I can meditate like that. It’s fantastic. Hypnotized.

Brian Keating:
Can you be hypnotized?

Emad Mostaque:
No, I’ve not been able to be hypnotized either. I’ve tried it a few times.

Brian Keating:
Okay.

Emad Mostaque:
I don’t dream. I can’t go back in the future.

Brian Keating:
Have you tried any psychedelics?

Emad Mostaque:
I can’t go.

Brian Keating:
My wife’s not listening.

Emad Mostaque:
I can’t go back in time and relive things. I’ve sufficiently deficient autobiographical memory. I can’t push myself in the forward. I’m always in the now. And so I’m kind of like a mega LLM with a big context. Again. That’s completely different to your mind. It’s completely different to their mind.

Brian Keating:
Right, right.

Emad Mostaque:
Colorblind people. But what we found again with the image reconstruction is there’s a common latent space in everyone’s minds. A can of Coke looks the same from a data perspective.

Brian Keating:
And so you can.

Emad Mostaque:
How cool is that to find. Yeah, hopefully you can find common ground again. If you’re having a debate, an argument, let’s take for example, there’s a war going on right now. It’s stupid. Wars are stupid. And the operation has passed. Like what if both sides fed into an LLM exactly what they want and then it said what to do?

Brian Keating:
I want to use that as a entree and to ask you advice to your former self. 22 year old. Whatever you want to go back to, you got 30 seconds. You’re talking to a young imad. Before you met your wife, before you had kids, before you were famous, you know, successful entrepreneur. What would you tell yourself to give yourself the courage to go into the impossible as you have?

Emad Mostaque:
I would tell myself to treasure relations with other people more and really cultivate them. It takes the effort and the network that you build is the most important thing in your life. You know, to be constantly giving and growing and helping and build that trust. Because I did everything myself and I found it very. I mean, I do have Asperger’s, but if I’d done that starting it just multiplies going through, especially if you’ve got something to bring.

Brian Keating:
Sounds like you found a partner also who’s probably very supportive of you and helps you through this challenging moments as good spouses do. Another quote.

Emad Mostaque:
Very lucky.

Brian Keating:
Yeah, it’s a blessing. I mean, it is a true. That’s what they say God was doing after he created the world. He was making matches. Next question. Arthur C. Clark said, for every expert, there’s an equal and opposite expert. Ask you about quantum mechanics because I know you’re obsessed with it.

Brian Keating:
We’re going to talk next time. You promised me a Part 2 Around to Talk about deep quantum mechanics. Maybe, you know, ontologically recapitulating all sorts of cool things. But what do you think people are getting right about quantum mechanics? Let’s talk about interpretations. Let’s talk about many worlds and Copenhagen. Are they the base layer of reality? Are they emergent? What do you. What is your take on the. On the foundations of quantum mechanics?

Emad Mostaque:
Gosh, that. So you got. Got 30 seconds. No, no, no, no.

Brian Keating:
30 seconds is for the anti. Both. You got as much time as you want. As our bladders will last where mine’s getting kind of full.

Emad Mostaque:
We’ll get into more of that kind of next time. But I think I. I’m of the view that reality is fundamentally Euclidean and that’s where the divine lives and where mathematics lives. And we are a projection of that in the Lorencian space. When you look at that, a lot of stuff becomes a lot easier, you know, and things, you know, the anthropic principle, measurement and others. We’re very much stuck in the way that we look at the world and the universe. It’s very difficult because especially like I said, if you don’t have faith, if you don’t, because we’re like, why does it matter if you’ve got something outside of time?

Brian Keating:
That’s why I think Elon wants to go to Mars or now it’s the moon. He downgraded to the moon, which I gave you a piece of. I expect you to take care of that. This makes it easy to visit the moon. But he’s, oh, I want to upload consciousness. Look, you can do that. They’re called kids. And he’s got 14, 15, 16 of

Emad Mostaque:
his best yeah, we’re doing our part,

Brian Keating:
but, but, but in reality, yeah, if you want to know the divine, I mean, I don’t know another way to get access to his operating system.

Emad Mostaque:
But again, like, you know, you think about the creation, expansion of the universe. Think about quantum to kind of classical gravity and going all the way up. Like Newton we started with and then we moved to gravity being geometric. What if it’s something else? Right. Like again, if you start from the Euclidean and then you move to Lorentz in, all the mathematics looks very different. A lot of the problems actually dissolve. And if there is a first mover, you know, if there is a God or a divine, they will never be in the Lorentzian. It can never be first.

Emad Mostaque:
Right. It has to be in the Euclidean space. Does the math support other physics for it? That’s something we’ll find out. Right?

Brian Keating:
It’s so funny.

Emad Mostaque:
All the physics is the other direction.

Brian Keating:
All the physics is the Pythagorean theorem. We go through all these gymnastics to say everything else are Imani and Lobachevsky and no, it’s Euclidean.

Emad Mostaque:
I don’t think I’d change anything because it’s the most wonderful time to be alive. We can end all war, all hunger, all disease, live forever, explore the universe if we want to. We can give back agency to every single person. And that’s fantastic.

Brian Keating:
Have the star. Star Trek future. Not the Star wars future.

Emad Mostaque:
There’s Star Trek. There’s no AI. I mean, like, you look at Data now and you’re like, my AI is more emotive than data.

Brian Keating:
Well, it’s 2001 had iPads in it. You know, 1968, it had, you know, Apple Vision Pros and stuff. Well, Iman, this has been fantastic. Part one. Hopefully there’ll be many parts. Enjoy the rest of your time in Southern California before you go. Head home and thanks for all you do. And especially the open source.

Brian Keating:
That to me is the sign of a true scientist. Someone who’s, you know, not afraid to. That’s the ultimate peer review.

Emad Mostaque:
I think that’s it. Like, thank you for having me on and let’s share the ideas and for where we go. Star Trek future.

Brian Keating:
Absolutely. Thank you so much.

Emad Mostaque:
Cheers.

Brian Keating:
And Matt just told us the labs have models that they’ll never ever release and that humans may soon have a negative cognitive value on AI teams. If that changes how you think about where all this is heading, hit subscribe and turn on notifications. Drop a comment. Do you think open source AI can still win? And if you want to hear our corresponding counterpoint from one of the masters of AI, the man who wrote Life 3.0. Check out my interview with Max Tegmark last year. I’ll link it right here. Don’t forget to subscribe, and we’ll see you next week.