Are Humans Smart Enough to Understand the Universe? Stephen Wolfram - #506

Please join my mailing list here 👉 https://briankeating.com/yt to win a meteorite 💥 Why aren't whales building rockets? They have bigger brains than we do after all. In this episode with Stephen Wolfram, we talk about why more brainpower doesn't always mean more understanding, and how neural architecture faces physical constraints. Stephen Wolfram says even super intelligent AIs may hit hard computational limits. In our conversation today, we explore why intelligence has a ceiling, and how ideas like Wolfram's Ruliad, computational irreducibility and brain size scaling reveal the boundaries of thought itself. Wolfram created Mathematica, Wolfram Alpha, it's probably in your pocket right now, in your cell phone, and he's now building a radical new theory of everything grounded in computational reality. If he's right, smarter doesn't always mean deeper. It might just mean we get stuck. Key Takeaways: 00:00 – 01:34 Are we discovering or simulating the universe? 01:34 – 06:50 Ruliad defines reality 06:50 – 10:02 Brains compress data into decisions, experience. 10:02 – 17:00 Math models nature, not necessarily its foundation. 17:00 – 25:07 AI may trap us like algebra did. 25:07 – 29:42 LLMs mimic minds, but lack depth. 29:42 – 35:57 Shared minds define reality; Boltzmann brains questioned. 35:57 – 42:28 Free will arises from irreducibility. 42:28 – 47:04 AIs may inherit computational free will. 47:04 – 52:45 Exploring Ruliad = expanding intellectual paradigms. 52:45 – 59:06 Massless particles = timeless, universal concepts? 59:06 – 01:07:32 Immortality blocked by biological irreducibility. 01:07:32 – End Biggest question: extend life or decode reality? ------------------------------------------- Additional resources: The Second Law: Resolving the Mystery of the Second Law of Thermodynamics: https://www.amazon.com/Second-Law-Resolving-Mystery-Thermodynamics/dp/1579550835 https://www.wolframalpha.com/ ------------------------------------------- Join this channel to get access to perks like monthly Office Hours: https://www.youtube.com/channel/UCmXH_moPhfkqCk6S3b9RWuw/join 📚 Get a copy of my books: Think Like a Nobel Prize Winner, with life changing interviews with 9 Nobel Prizewinners: https://a.co/d/03ezQFu My tell-all cosmic memoir Losing the Nobel Prize: http://amzn.to/2sa5UpA The first-ever audiobook from Galileo: Dialogue Concerning the Two Chief World Systems: Ptolemaic and Copernican https://a.co/d/iZPi9Un 📺 Watch my most popular videos:📺 Neil Turok https://www.youtube.com/watch?v=Dt5cFLN65fI Frank Wilczek https://youtu.be/3z8RqKMQHe0?sub_confirmation=1 Eric Weinstein vs. Stephen Wolfram https://www.youtube.com/watch?v=OI0AZ4Y4Ip4?sub_confirmation=1 Sir Roger Penrose: https://youtu.be/AMuqyAvX7Wo Sabine Hossenfelder: https://youtu.be/g00ilS6tBvs Avi Loeb: https://youtu.be/N9lUceHsLRw Follow me to ask questions of my guests: 🏄‍♂️ Twitter: https://twitter.com/DrBrianKeating 🔔 Subscribe https://www.youtube.com/DrBrianKeating?sub_confirmation=1 📝 Join my mailing list; just click here http://briankeating.com/list ✍️ Detailed Blog posts here: https://briankeating.com/blog 🎙️ Listen on audio-only platforms: https://briankeating.com/podcast #universe #podcast #briankeating #intotheimpossible #science #astronomy #cosmology #cosmicmicrowavebackground #intotheimpossible #briankeating Learn more about your ad choices. Visit megaphone.fm/adchoices

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 00

  This episode is brought to you by Indeed. You're ready to level up your business, but the pressure to find the right person to make that happen is intense. Indeed sponsored jobs can help carry the load. It boosts your job post to help it reach quality talent fast. Cut through the chaos with Indeed sponsored jobs. Get a $75 sponsored job credit at indeed.com/podcast. Terms and conditions apply. Hiring now? Then this is a job for Indeed sponsored jobs.

• 0:30Speaker 01

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• 0:59Speaker 02

  Why aren't whales building rockets? They have bigger brains than we do after all. In this episode, we talk about why more brain power doesn't always mean more understanding and how neural architecture faces physical constraints.

• 1:12Speaker 03

  Yes, we are locked in a kind of prison, which is the prison of what human minds deal with. The things we care about are the things that human minds can kind of deal with. But there's a lot else out there in the computational universe, in the ruliead, that is behavior that human minds can't really wrap themselves around.

• 1:29Speaker 02

  Stephen Wolfram says even super intelligent AIs may hit hard computational limits. In our conversation today, we explore why intelligence has a ceiling and how ideas like Wolfram's Ruliad, computational irreducibility, and brain-sized scaling reveal the boundaries of thought itself. Wolfram created Mathematica, Wolfram Alpha, it's probably in your pocket right now, in your cell phone, and he's now building a radical new theory of everything grounded in computational reality. If he's right, smarter doesn't always mean deeper. It might just mean we get stuck.

• 2:02Brian Keating?

  Stephen Wolfram, you've created Mathematica, you've built Wolfram Alpha, you've basically taught computers how to think. Your theory of everything. Everything, what you call the ruliad, is considered by many to be the frontrunner among computational approaches to fundamental physics. But here's what I really want to know, Stephen. If the universe is just the entangled evolution of all possible rules and observers like us are simply slicing our way through the ruliad from our own computational vantage point, then what makes our experience, our qualia, what makes them feel so real, so privileged? What does it mean to have a brain? You're describing how the universe might even be thinking in a certain sense, but not in the woo-woo sense. Are we discovering the universe?

• 2:46Brian Keating?

  Or are we really just bumping up against the limitations of our own computational prison?

• 2:52Speaker 03

  Well, let's see. I mean, the way I see it these days, the sort of the ruliad is a representation of everything that is computationally possible. We, each one of us, is sampling a tiny thread of what is possible in the ruliad, of what happens in the ruliad. Just as we're sampling a tiny thread of what happens in physical space. You know, we're sitting on this one planet in a, you know, in a corner of a galaxy that's one of 100 billion galaxies. You know, it's a, we are, we are sampling a small part of the, of even the, the physical spatial universe, let alone this kind of much larger computational universe that is the ruliad.

• 3:33Speaker 03

  So, you know, if you're asking what, what makes that feel real to us? What else would it feel? That is, if we feel anything, we will feel that it is real, so to speak. If, if we're, we are, we're not, you know, and if we're asking what? So, so there's a sort of interesting question of, you know, how do we know that anything is real? What does it even mean for things to be real? Uh, what's the difference between living in a simulation of the real and living in the real, so to speak? So, these are complicated questions. There's a whole bunch to say about them. But maybe we can kind of dig into questions about,

• 4:14Speaker 03

  well, for example, let's say, the only thing that, that any of us are really aware of is what we are perceiving. In other words, I have a certain feeling about what's going on. I know what's happening in my own mind. To know anything about what you might think is happening, that's merely an inference. You seem a bit similar to me. So I kind of project what I feel is going on as something that I would imagine you also feel is going on. And that's how we kind of have a shared sort of objective reality. Each one of us has just the particulars of what's going on sort of inside our own mind. I mean, I've kind of often thought if you think about a computer

• 4:59Speaker 03

  and what does a computer think is going on in the world? Internally to the computer, it is something very similar to the kind of thing that we think is going on in the world. It's just that we don't identify with computers. So we don't sort of, we don't project ourselves into, it seems very alien and unnatural to us to imagine that there's a thing being perceived by the computer that is kind of like the thing that's being perceived by us. You just, you just jumped right into kind of a, a pretty complicated area. I mean, there's, there's a lot to untangle there. To, to give another thing, people, people will say, well, what, you know, could the universe be a simulation? What does what mean by that?

• 5:42Speaker 03

  I think what people often think they mean is there's some simulator out there who's playing a video game and we're all part of that video game. Right. That has a certain implication that there are many video games that could be played. And the kind of godlike figure who's playing the video game picked this particular cartridge or whatever it is to put in. And that's the one that we're all operating within. That's kind of the, the idea that there is a simulator who is making arbitrary choices. And that we are then the working out of those arbitrary choices. That would be kind of one version of what it means that that's sort of the beginning. What it means to say that we are operating sort of in a simulation is there is a choice about what simulation it is.

• 6:27Speaker 03

  Now, in, in my view of how sort of things actually work, the idea of the ruliad, this kind of entangled limit of all possible computations, there's no choice about that. There's only one of it. If you just aggregate all possible computations, you inevitably end up with a ruliad. So the simulator has no choice. And the question of what we actually perceive is then a story of where we are, who we are, how we observe, how we sample this ruliadable possibilities. And so it's it's like saying, well, you know, can we explain why the night sky looks the way it does? Well, that's because we're in this on this particular planet,

• 7:10Speaker 03

  this particular place in this particular galaxy, et cetera. It looks the way it does. But there's no theory that says why we ended up on this planet, in this particular galaxy, and so on. That's just where we are is there. And so we have this perception of what of what the universe is like, what the night sky looks like, and so on. And so similarly, when when you say, well, what, you know, how did we get the particular sampling of physics that we got? Well, it's because we are where we are in the ruliad. It's not because there is something about the ruliad that is determining that. It is the it is the kind of the the thing that is the case about where we are. It's not something for which you can derive where we have to be.

• 7:55Speaker 03

  You can't derive that we have to be on this particular planet.

• 7:58Brian Keating?

  Right. And and even even in a simulator and the hypo matrix, ultimate matrix hypothesis, the thing that sometimes confounds people is that we imagine, as the title of your wonderful essay, which I'll link to below, what if we had bigger brains, imagining minds beyond ours? And it naturally thinks, you know, it starts off with the just the raw facts of the human brain that, you know, in this three pound supercomputer, we've got, you know, a hundred billion or so neurons, which all my, you know, woo woo friends like Deepak Chopra love to say, oh, that's the same as the number of stars and the same the number of galaxies. It's just nonsense, of course, and it's coincidental, just like you said, the constellations or the, you know, the planets that we have are as well.

• 8:42Brian Keating?

  But it seems to me that, you know, computer companies are, let me say, it seems to me like AI companies like OpenAI, they can't get enough of bigger and better processors from Nvidia, for example. And so it might lead one to believe that certainly for human based computation. Bigger is better. And yet, and yet, you know, Einstein reputedly, reportedly, his brain was slightly smaller than normal and cats have smaller brains and sperm whales have six times larger brains. So why is bigger not better? How does that fit into this notion? I mean, I would think the Ruliad would privilege things that have more and more connections in their connectome, but but it doesn't seem to scale as I naively would have thought.

• 9:23Speaker 03

  Well, that's you. You're jumping into several very different, deep kind of areas. So I mean, maybe we should, we should finish on one issue about sort of the perception of reality. I mean, the, the thing that matters to us is what we ultimately perceive. There is, we are getting that there is a, a, a sort of, we, we think about the world in terms of the outside and things actually happening in the outside that are then being transferred through our senses, through our eyes, through our touch senses, all those kinds of things to the internal perceptions that we have. In other words, we're, we're taking, um, and then the question is, well,

• 10:04Speaker 03

  you know, what if it isn't actually, you know, your eyes that are sending those signals down your optic nerve? What, what if it's something that is sort of digitally generated and it has nothing to do with sort of the outside world as the outside world is? Well, so in kind of this sort of computational view of what's going on of the Ruliad and so on, in some sense, there is no distinction between the merely computational and the actually, uh, the, the, the real thing, so to speak. Everything in the universe is just a feature of these computational constructs. And so it's, it's the question then is, well, what is happening when we perceive

• 10:45Speaker 03

  things in the universe? I mean, this is where you're, you're forcing me through at very high speed through a bunch of really philosophically complicated kinds of ideas. But, but just to try and say something about, you know, what, what happens when we perceive things? What's, what's happening is, I think, and you know, you were sort of talking about how brains work. I think the key thing that brains are doing is going from all of those inputs that we have, you know, we have millions of photoreceptors in our eyes, we have millions of touch sensors on our skin and so on. We're taking sort of those millions of kinds of inputs. Where those are coming into our brain, somehow we are having a sort of model of the world based on that input that we're getting.

• 11:28Speaker 03

  And then the big thing that our brains do is they decide what to do next. Probably roughly 10 times a second. So they're doing a huge amount of compression. They've got huge amounts of data coming in. And yet, all they do with it is to say, what are we going to do next? I kind of got to realize recently that it's sort of a little disappointing in a sense. We, we think of, you know, this idea of consciousness and our thread of consciousness and so on. It's a great achievement of, of, you know, kind of humans and, and perhaps human-like things. But I, I kind of think what started that all off was an incredibly mundane thing. Sometime, you know, a billion or two years ago, in the history of biological evolution on, on earth,

• 12:08Speaker 03

  which was when there started to be mobile animal-like things, the animal had to decide where to go next. And the animal could go to only one place. The animal can't go both left and right. The animal has to make a decision. It's going to go to the right, it's going to go to the left, whatever. And that means that the animal has to take in all that input and then come out of that with a definite decision about what to do next. And I kind of think that incredibly mundane sort of need for a mobile thing that is a sort of a biological organism is what probably drives the thing that, that is terribly significant to us, which is this idea that we, we abstract this thread of conscious experience from all of this input that we get from our senses.

• 12:52Speaker 03

  So, and that, that seems to be, and so there's sort of a question of what, what are we doing when we do that? Well, we're, we're, you know, the, the, the big thing is that we're taking all this detail about what happens in the world. And we're just deciding we're, we're, we're concentrating that all down onto this sort of thread of perception that we have, this, this thread of experience we have.

• 13:12Brian Keating?

  Was that what, you know, they refer to as Galileo's error? So, you know, for you listening, or maybe those of you with bad eyes, here's my friend Galileo, who, you know, really said that our job as scientist is to measure what's measurable and make measurable, as he said, what is not yet so. In other words, that was the, that was the project, the Galileo project, not your neighbor, you know, in Cambridge over there, different kind of Galileo project, as opposed to the, the Wolfram Physics project. In Galileo's view, mathematics was the core operating system, if you like, of, of all of nature, and understanding it could reveal universal truths. We needed the sensors, but that was the job of man, to build sensors, to transduce information. But as you point out, and as

• 13:57Brian Keating?

  my friend and former guest, Jan Le Cun has pointed out, you know, the human eye is processing terabytes of data, you know, in some sense, and yet, the brain must be doing some immense filtering process, which is a simplification. And so, in terms of those computation or compression, is compression really the core job of the human brain in, in your perspective?

• 14:18Speaker 03

  Well, that's, that's an important part of it. I mean, that's what leads us to go from kind of the complexity of the world to kind of what we perceive about the world, and then how we decide what to do next. But I think I want to come back to Galileo.

• 14:33Brian Keating?

  Yeah.

• 14:34Speaker 03

  I, I, I mean, your implication there is that Galileo thought that what, that what was really there there, I'm not completely sure that that's how I would interpret what Galileo said, but let's take this as a, as a conceptual Galileo, even if it wasn't the actual Galileo Galilei. The, let's, let's consider it to be your, your avatar of Galileo. What, what, what that avatar might have said is, is the implication that the, the true there there in the universe and physics and so on, is something mathematical, and that we are sort of poking at that mathematical thing, that the real sort of way the universe

• 15:17Speaker 03

  works, one might say, is according to something mathematical. Now, that's a, that's a, that's a funny concept. Because mathematics, we have to decide what we mean by mathematics. What mathematics probably meant to Galileo was a set of ideas that had emerged from kind of human thinking about things. You know, mathematics sort of, and it's, you know, and it's probably emerged historically in ancient Babylon in sort of two different threads. One was kind of accounting, doing arithmetic, counting things. And the other was land surveying and geometry. And those two threads kind of developed over time, algebra developed and so on.

• 16:00Speaker 03

  And in Galileo's time, it was those are, that is what mathematics is about. Things like arithmetic and geometry. And those things seemed very pure. And I think Galileo might have imagined that there's all this mess associated with, with how the world actually seems. But at some ultimate level, the world must be just described in terms of the mathematics that humans had invented to that time. Now, that's a, in a sense, that's a, it's a very, it's a, it's a very un-humble kind of claim, because it says, we humans in the course of those couple of thousand years of developing mathematics, had nailed it. We got kind of the abstract concepts

• 16:44Speaker 03

  that are going to be, that are the core of how our universe works. I don't think that's actually right. I mean, what happened after Galileo, sort of when, when came to Newton, who really made use of this kind of mathematical idea. He, he sort of introduced the notion that there were mathematical principles of natural philosophy, that you could describe nature in mathematical terms. Now, Newton was pretty lucky in a sense. So was Galileo. But the particular things, that maybe it isn't luck. The particular things they studied were things where that approach works. Yes. You know, Newton studied mechanics, studied, you know, how things move and, and what forces are needed to change their, their states of motion, things like that.

• 17:25Speaker 03

  Had Newton tried to study fluid mechanics instead of solid mechanics, he would have been completely stuck. When, if you look at the motion of fluids, they have things like fluid turbulence, there's some randomness that you get from fast flowing fluids. Those kinds of methods that Newton had that came from sort of the development of mathematics and algebra and what Newton did himself with calculus, they just don't tell you very useful things. That the fact that and it's a good example of some other things, the fact that Newton was able to use mathematics, Galileo was able to use math-

• 18:00Speaker 00

  This episode is brought to you by Indeed. You're ready to level up your business, but the pressure to find the right person to make that happen is intense. Indeed sponsored jobs can help carry the load. It boosts your job post to help it reach quality talent fast. Cut through the chaos with Indeed sponsored jobs. Get a $75 sponsored job credit at indeed.com/podcast. Terms and conditions apply. Hiring now? Then this is a job for Indeed sponsored jobs.

• 18:29Speaker 03

  Mathematics to talk about things is because the things they chose to talk about were things about which mathematics has something to say. In other words, if, and so I think that's a, it's a very common characteristic in science that you have certain methods and then the science sort of wraps itself around the things about which those methods have something to say.

• 18:49Brian Keating?

  Do you mind if I just interject there because it's something I wanted to ask you for quite some time, which is the interlocking of our technology with the problems of the time. So exactly what you just said about Galileo, Newton, but to apply to today's marriage of L L Ms plus GPUs, which were never designed to, you know, replace, you know, human functions of chatting and so forth, but they're very good at it. They're very good at linear algebra. It's not very sophisticated mathematics at some level. Your book on chat G P T explains it very thoroughly. We talked about that last year. But are we locking ourselves into a new type of prison, you know, Sam Altman's prison? I don't know. Some prison where we're, these things are so good at doing this one type

• 19:32Brian Keating?

  of very abstract and very important type of reasoning that we might not be able to solve problems like, for example, come up with new laws of nature, ab initio, you know, unify the laws of quantum mechanics with the laws of gravity, et cetera. I know, I know that you can do that, but, but in terms of the conception of a theory of everything, are we perhaps because of our success, we are victims and we are entering a new prism of GPUs plus L L Ms?

• 20:00Speaker 03

  Okay. So there's several different directions there. So one thing I thought you were going to say is, you know, in the time of Galileo and Newton, they had algebra and things like this, and they fashioned their theory to be one where that kind of approach would work. I thought you were going to say, and here we are today with computers, and you have a computational way of thinking about the universe, and isn't that sort of as limited as the way that Galileo and Newton had of thinking about things based on the kind of intellectual technology of their time? Okay, so answer that question. And then, then I want to talk about the L L M's. Yeah. But that was, uh, so, you know, that's an interesting question. I've certainly thought

• 20:41Speaker 03

  about it. I think the thing that for me is, is kind of the, the suggestion that we are not fooling ourselves in that way is this, the fact that with the things we're doing in computation, we have in some sense reached the end of what is abstractly possible in the following sense. One, one might have said, well, you've got algebra, you've got this, you've got that, you've got these different methods. And imagine you're making machines to do algebra, machines to do geometry and so on. The machines you need to do these different things are different machines. What got discovered about a hundred years ago was this idea of universal computation. The idea that you could have one machine that could be programmed to do all these different kinds of things. That's the idea

• 21:26Speaker 03

  that made software possible. That's the idea that made everything we do in practice with computers possible. But it's also an idea that tells you there's a bottom to what's going on. It's not the case that you keep on saying, oh, I need, I, I need something sort of more fundamental. It's like you reach the thing that is the universal thing that can do everything that anything can do. So I think that the, the idea that, that there's in a sense, you know, I talk about things in terms of computation because that is a metaphor of our times. I could equally well talk about things in terms of just rules that are followed by a system, which is something a little bit less familiar than sort of what we experience with computers and the way that computers run and so on. But I, I think.

• 22:11Speaker 03

  That, you know, what we're seeing is, it seems to be the case that, you know, what, what, what we know is that at some abstract sense, we have kind of reached the end of what, we've reached kind of the lowest level of what can be talked about in, in terms of rules, in terms of computation and so on. So I feel much more confident that, you know, we, we can be talking about things at a truly fundamental level, rather than we are just talking about things in the form that we can talk about them in the, you know, third decade of the, of the 21st century and so on. And that at some time in the future, when we'll have a completely different picture of what's possible.

• 22:50Speaker 03

  With respect to L L Ms, I think the thing to realize is that our brains operate in certain ways. Those ways in which our brains operate determine the things that we care about in the natural world. That is, the way I imagine with the ruliad, for example, there's a lot of stuff going on in the ruliad. But yet, our particular sensory systems, our particular ways that our brains work, we concentrate on only certain things. So in a, in a sort of extreme case, we could say, well, you know, I'm sitting in this room. It's got a bunch of air in it. That's a bunch of gas molecules. There's zillions of molecules bouncing around, but the only thing I notice is, you know, if I, if I wave my hand, I can kind of feel that there's air flowing around it.

• 23:35Speaker 03

  That's the only thing I notice. I'm not, not paying attention to every individual molecule and so on. That is, that's the thing that for, with my kind of sensory system and my way of thinking about things, I only get to sort of talk about these very large scale fluid motions and things like that. So at some level, the things we care about talking about in physics, in science, are things that are relevant to our sensory experience. If we were different from the way we are, you know, even, you know, you talk about, I don't know, a dog or something like this that has a, a very good sense of smell, different from ours. The things, you know, dog physics would no doubt be different from human physics. There's a bunch of things that dogs will be very concerned about, that we barely notice.

• 24:20Speaker 03

  And more extremely with, with other kinds of critters and so on. But I think that, so the first thing to say is, I think the, the science that we care about is science that somehow relates to our way of sensing things going on in the world. Now to this question of whether there are certain kinds of things we can figure out. What is science ultimately doing? Science is going from the natural world over here. What is science trying to achieve? It's trying to go from the natural world and it's trying to essentially have a translation, have a bridge between what actually happens in the natural world and the kind of narratives that we can kind of tell ourselves in our finite minds. So there's all this stuff going on in nature, but science is about kind of how we can think

• 25:06Speaker 03

  about what's going on, how we can take all the stuff that's going on in nature and stuff some sort of filtered version of that into our finite minds and develop some narrative that allows us to make it kind of predictable and understandable what's happening in nature. So we're not, we're not getting all of nature. We're just getting this tiny little, little piece of nature. And I, I think then the question is, and that's, so then you can say, well, well, how do the L L Ms relate to this? The L L Ms are kind of built in our image. L L Ms, the, the fundamental operation of neural nets, which is what L L Ms are based on, is kind of a cartoon version of what happens in brain. We didn't know until very recently that that cartoon version was good enough to be able

• 25:51Speaker 03

  to do these impressive human-like things. Turns out that it is. And what we can expect the L L Ms to do are many of the kinds of things that we do. Now, there are lots of things that we know can be done that we don't do. Like pretty much nobody can run code in their minds. If you say, I've got this program, what does it do? It does a complicated thing. There's no way that a human can sort of run that code in their mind. By the way, an L L M can't do that either.

• 26:21Brian Keating?

  Right, right. You make the case for the working memory. You make the distinction between working memory and processing speed and even, as you say, even L L Ms can't do that. They stumble on things like how many Rs are in the word strawberry, right?

• 26:34Speaker 03

  Well, but, but you know, they're doing the same kind of thing that we're doing, which is broad but shallow computation. The thing that is sort of a, a coincidence of history perhaps, is that, you know, after Newton and Galileo and all those folk. We developed this kind of very formalized way of thinking about the world that eventually led us to computation and computers. And eventually led to this idea that we could actually do sort of a whole tower of formal operation and do that. And and build that up so that we could do these kind of irreducible computations. That that we can do with a machine that we can't really do with our brains. And so there's sort of these two different branches of how you can approach things. You can approach things.

• 27:16Speaker 03

  By sort of just what you can think through with your own mind. And you can approach things by actually doing computations, doing kind of big towers of computation. And we can readily see that there are things that we can get to with big towers of computation. I've spent. A large part of my life doing those kinds of things. There are things we can we can get to with those big towers of computation. That human minds just don't get to on their own. We can and that kind of tells us, yes, we are locked in a kind of prison. Which is the the the prison of what human minds deal with. Those are the things that we we have this sort of story. Of the fact that the things we care about are the things that human minds can kind of deal with.

• 28:01Speaker 03

  But there's a lot else out there in the computational universe in the ruliad. That is sort of that is behavior that human minds can't really wrap themselves around. I mean, the. The kind of story of my my kind of day job life is building our computational language, working language. And what is the point of that language? The point of that language is to make a bridge. Between the way humans think about things and what is computationally possible. So in other words, there's much that is computationally possible. That we humans just look at it and say, that looks alien. I don't know what's going on. We're, you know. In order to kind of address those kinds of things, the science of the Galileos and Newtons doesn't really do that.

• 28:46Speaker 03

  That kind of science and the mathematics that it's associated with doesn't get there. That's, you know, I uh uh twenty twenty years ago, I wrote this book. That had a title, which at the time people were like, how can you say that? The title was A New Kind of Science. And the reason I called it that is because that's what it was about. In other words, there'd been a kind of science that people have been doing for 300 years, which was based on this kind of idea of using mathematics. And this was, this is a kind of science that is different. It's based on sort of building these kind of formal towers of computation that go, go very far beyond what sort of unaided human minds can deal with.

• 29:30Brian Keating?

  In the opposite end of the spectrum, we talked about, you know, supermassive. We could talk about planetary sized brains. But what about the opposite side? People talk about Boltzmann brains. And in the context of the ruliad, where all possible computations exist, do Boltzmann brains represent inevitable observers that will come into qualification as, as, as we would consider an observer, so to speak? Or do they fail to qualify as observers because they lack sustained computational reducibility?

• 30:00Speaker 03

  Well, there aren't very many, you know, when, when you want your brain to spontaneously form from a bunch of random molecules bouncing around, that's a pretty rare thing to happen. It is a very interesting scientific question, which I don't feel that I've answered yet. The extent to which observers like us are inevitable in the ruliad. It is, you know, at the level of talking about Boltzmann brains and sort of all things are possible. Yes, occasionally you'll just randomly get a thing that's a bit like us. But that's not, I think, enough to explain what we actually observe. And actually, it's interesting that the thinking about sort of the emergence of brain-like things leads you much more into biology than I had expected.

• 30:45Speaker 03

  In other words, I'd always imagined, I, I think it becomes important that, for example, things like self-replication occur. Because one of the things to realize is if there was only one mind, things will be very different. The fact that we operate the way we do is partly a consequence of the fact that there are lots of minds that we're communicating with, lots of similar minds that we're communicating with. As an example, the fact that we sort of believe in objective

• 31:12Speaker 00

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• 31:41Speaker 03

  Reality. The fact that we, is a consequence of the fact that we all kind of agree about, in some sense, about what's happening because there are lots of us who are sort of similar enough that we kind of come to the same conclusion. If there was only one of us, it would be very hard to, it's not even clear what we would mean by objective reality. It's if there's only one of us, that one of us is experiencing things, but they don't get to sort of say, well, this is the way everybody will experience this. This is the way it is. It's just all they know is the way it is to them.

• 32:14Brian Keating?

  So sorry to interrupt you, but you just made me think of Pascal, you know, and the Kogito ergo sum. It's sort of

• 32:21Speaker 03

  Descartes.

• 32:22Brian Keating?

  Oh, Descartes, sorry, sorry. You just made me think of, I'm gonna edit that out. You just made me think of Descartes, Kogito ergo sum, in that, you know, the refutation perhaps of a single master simulator, or maybe a god, you know, could be found in what you just said, which is, which is that these, it's sort of the interactions. Am I overstating the case?

• 32:45Speaker 03

  The the issue, so there are a bunch of different issues. I mean, one is, is there all we know for sure, and I agree with Derek on this, all we know for sure is what we internally experience. But we can make many inferences, guesses about what's going on from the fact that we assume that the other people we see are like us. It is interesting. We've been thrust into this situation of having alien intelligences among us with the AIs. And the question of whether we perceive in the AI something similar enough to us that we imagine that it has some of the same kinds of experiences we have is an interesting one. I mean, if if all you're doing is you're in a chat interface or something

• 33:29Speaker 03

  and you're talking to the thing, and you might be talking to a human in a chat interface too, it's, you know, it very quickly comes to the point where you probably will have a theory of what's going on in that thing you're talking to that says, this is, this is like me. It must have the same kinds of inner experiences that I have, even though I can never know that for sure. Right, the theory of mine. I never know that for sure. All I know for sure is what's happening inside me, so to speak. Now, you know, there's a, there's a, there's a lot to say about kind of, well, here's an example of something kind of, the the fact that we kind of agree on objective experience is a consequence

• 34:11Speaker 03

  in many ways of the fact that we are sort of a, our minds, we're sort of a flock of minds that are in some sense very close together relative to the vast mass of what happens in the ruliad. So in the ruliad, many, many different kinds of things can happen. But it's because we're all sort of going through, we're all sort of existing in the ruliad very nearby that we kind of agree about what's going on. We agree that, I don't know, I'm I'm looking and seeing whether the moon is out today, but we, we would agree about what the state of the moon is because, okay, we're a few thousand miles apart, but it's, it's sort of close enough that there's a moon in the sky. We're not on opposite sides of the galaxy where the sky is completely different.

• 34:56Speaker 03

  So in other words, we agree on objective reality because we are, in a sense, close together in the ruliad. And that's, that's kind of, that's a, that's something where. It's important that there are there's sort of many different entities that can have that communication to be able to form that sort of objective conclusion. Now, I think you're asking about sort of the the God versus versus the humans and so on. I I kind of feel like a lot of kind of the, to me, things like the existence of the universe, which is something that you might say, well, you know, the fact that the universe exists, you might associate with there has to be some prime mover, some god that's making the universe exist.

• 35:40Speaker 03

  In my way of thinking about things, you don't need that. The ruliad is something that is a formally inevitable thing. It's just like saying one plus one equals two. You don't have to have an actual one rock, another rock, and put them together and make two rocks. One plus one equals two is an abstract thing to talk about. The ruliad is also an abstract thing to talk about. So the existence of the ruliad is not something that you have to debate. What is non-trivial is that there are observers like us within the ruliad. And that is something which potentially is amenable to sort of scientific investigation. In other words, how inevitable are observers like us? How common are observers like us? If you ask for observers like us but a bit different from us,

• 36:25Speaker 03

  how far away, what what is the nearest thing that is kind of somewhat like us but not us? That's kind of a extraterrestrial intelligence or or across the ruliad intelligence, alien intelligence kind of question. But I I think so, you know, I think the in some sense, the the sort of the existence of the universe is is an inevitability. What is not so obvious is that we are here to perceive it and that the universe as we perceive it is something that anything is perceiving, so to speak. It could be that the universe is just doing its thing and nobody is is there to kind of to sort of sense it in the way that we do

• 37:07Speaker 03

  and to conclude that there are laws of physics of the kind that we conclude there are.

• 37:11Brian Keating?

  Interesting. So if the ruliad contains all possible computations, including every brain state of a conscious observer, is free will sort of the subjective, you know, effect of these reducible branches, or is it an illusion? As many of my guests, Stephen, I get very frustrated. I've never met a person who acts like they don't have free will, and yet so many of my guests, from Sapolsky to Dawkins to Dennett and some, and to Sam Harris in particular, they claim free will is a complete illusion. Sibina Hosenfeld is another one. Where does free will come in to the ruliad, in our brain states, or is it a luc- a lucery?

• 37:52Speaker 03

  So it is a very interesting thing that we assume about ourselves that we have free will. Even the doing of science requires an assumption of free will. The idea that we can do experiments, the idea that we can pick the experiment we do and come out with a conclusion, requires an assumption of free will. We don't have free will, no experiment, we can't do an arbitrary experiment. We are determined in what experiments we do and will, we're forced to do just those experiments. So that, we kind of assume, and we, in our thinking about science, that we have some kind of free will. So how does that work? Well, I, I, I think I've sort of had an understanding of this for a long time now, and it's all related to this concept of computational irreducibility that I've been talking about

• 38:31Speaker 03

  for 40 years now. So, the, the, the starting point there is, you might imagine that if you write down particular rules, let's say a particular program, that you would always be able to foresee what that program will do. And in some sense, you can, because you can just run the program step by step and see what it does. But the thing that has been the kind of, the conceit of science, since your friends Galileo and Newton, has been, okay, if we know the rules, we solve the problem. We can just jump ahead and see everything about what will happen. That's what one had assumed was the case. That's what mathematical science tends to encourage one to do.

• 39:11Speaker 03

  That's kind of what, when people talk about predictability as sort of a key aspect of science. That's what people are focusing on, but it isn't always the case. What can happen is that you have an irreducible computation where you know every step that you can follow. But to work out what will happen after, let's say, a billion steps. You basically have to just run those billion steps and see what happens. There's no way to jump ahead. It's all related to these questions about, I talk about this notion of computational equivalence. The notion that if, if it is the case that these things, even these very simple rules that one might write down. Are no less computationally capable than our minds or our, or our computers or our mathematics.

• 39:57Speaker 03

  Then there's no way that we'll be able to win out over those simple programs. Those simple programs will be, we'll, we'll be stuck just keeping up with those programs as they run. So how does this relate to free will? Well, the, the point is even if you have deterministic underlying rules. You can't know what's going to happen, except by running those rules and seeing what happens. So if you were looking at some, some creature, you know, the moth that's, you know. Trying to bash itself at the window, trying to get to the light. That doesn't look like it has free will. It looks like it's just following some very simple program. It's just keeps on doing the same thing. But the thing that I think is where you start thinking about free will.

• 40:37Speaker 03

  Is you can't work out what the thing will do any more efficiently than just by watching it do it and, and seeing what happens. In other words, it's not the case that you can, you can say, no, you don't have free will. I can tell you don't have free will because I know what you're going to do. That what, what's happening is you can't know what the thing is going to do. The thing is just going to do what it does and you are merely a passenger watching what it does. And so that's the sense in which, you know, you can say, well, looked at from the outside. You can, you could say, well, I know what it's going to do because I know its rules.

• 41:11Brian Keating?

  Right, like the weather, like the weather. We know the rules of of weather, but we can't predict. Uh, you know, because it's a complex system, correct? I mean, we can't predict, you know, mere moments ahead if you took the entirety of the system, even though we know basic principles of climate. Is that a fair comparison?

• 41:27Speaker 03

  That's that's a complicated, that's a complicated case. That has a whole bunch of other tentacles associated with it.

• 41:33Brian Keating?

  But sure.

• 41:33Speaker 03

  But the basic idea is that for something to be not have free will, it is because it is, it is, it's, we know what it's going to do. It is not, it is not acting freely in the sense that it is doing things that are just intrinsic to it. It's something where we can, from the outside, we can say, we know what it's going to do. So I think, you know, I think this really is is the story of kind of our perception of free will. The universe is doing what it does. We are part of that universe. You can't jump ahead and say, we know what we're going to do. We're just doing what we do. And so that's, that's why we are, we are, we have both the

• 42:18Speaker 03

  the perception and in a sense, the reality of free will. There is no way to know what what we're going to do, other than by just running us and seeing what we do. And I think that's, that's the, um, and you know, this becomes a very practical issue for, you know, for AIs, for example. Do AIs have free will? In other words, is it the case that, and, and okay, so that's important if you want to sort of make sure the AIs do the right things. You have to say, well, I'm going to put these, I'm going to constrain the AI. I'm going to set the AI up so that it can only do the right things. The problem is if the AI has free will, then you can know, you can never say for sure based on sort of what you put into the AI, what it's going to do.

• 43:01Speaker 03

  It will have, it will be doing things which are unexpected and surprising. And the fact is that if you have an AI that is capable of doing arbitrary computation, if you're not constraining it to be sort of this, this impoverished version of computation, then it becomes inevitable that the AI in this same sense has free will. It is, it is doing irreducible computation where you can't know what it's going to do, except by running it and seeing what happens. So that's a, it's kind of a, I think it's a, it's an important kind of almost societal issue for the future. Is do we have AIs that can do these computationally sophisticated things that are probably pretty useful to us, but they will sometimes do things that are unexpected and surprising and not what we want?

• 43:46Speaker 03

  Or do we say, no, we want our AIs to be constrained to only work in ways that we can readily understand and predict, in which case the AIs won't be able to do as much for us? So that's a sort of very practical manifestation of computational reducibility. I mean, it's sort of remarkable to me. You know, I invented this idea forty years ago, and I invented it as a way of understanding sort of what was possible to do in science and what wasn't. And it's ended up getting so many tentacles. I mean, like, the idea that's central to blockchain of, you know, proof of work in Bitcoin and so on, is a computational reducibility idea. I never would have imagined that this idea that was something associated with kind of a limitation of science and a theoretical understanding of limitation of science would

• 44:30Speaker 03

  in not too many decades get used to kind of be the proof of value that was burning huge amounts of energy and so on in all sorts of efforts of things like Bitcoin mining and such. It's sort of interesting to me that these very conceptual, sort of almost philosophical things that one comes up with in science can end up being sort of becoming very, very practical and real. And so this question of free will that you raised, which might seem like a philosophical question, it's a very much something that is very practical question when it comes to AIs. I mean, there are all kinds of issues with that boil down to questions about, you know,

• 45:13Speaker 03

  just how much free will do we want to give the AIs, so to speak?

• 45:17Brian Keating?

  Right. And will we turn them off, or will we cause them pain, or will they cause us pain, and so on? These are ethical questions that many people wouldn't have dreamed of. I just, again, find it interesting that, you know, Sam Harris does believe in free that AI can have free will, but he doesn't believe humans can have free will. Uh, to the extent that we, you know, we, we model, as we, as you said earlier, we're sort of, you know, uh, looking at these as extensions of what we are familiar with, which, which kind of, for me, makes me want to ask the question of, you know, are these AIs training us? We've heard, you know, you'll hear stories in, in the news and provocative headlines and stuff of AIs,

• 45:59Brian Keating?

  you know, convincing people, you know, to leave their wives or whatever, and not, you know, things that I don't find very important, but, but these questions of, you know, we are prompting them and we seem to think that we're in complete control, but is it not possible, Stephen, that they could be prompting us in a certain sense? I mean, will, is there a threshold? We think about neural networks. What is that? What is it based on? Hardware, software, both?

• 46:23Speaker 03

  Well, I mean, look, we humans can be kind of lazy. You know, it's kind of like, there was a time when you would read maps to try and figure out where you would go in your car.

• 46:33Brian Keating?

  I read that.

• 46:33Speaker 03

  Most of us, and I started doing that very early on, much to the amusement of my children at the time, just was, I'm just going to follow what the GPS says. I'm not going to think about it. And, you know, we can imagine that more and more, there's sort of an auto suggest for life, so to speak.

• 46:48Brian Keating?

  Yeah.

• 46:48Speaker 03

  And, uh, you know, people just, well, I'll do what the auto suggest says. That's the sense in which the AIs take over. It's not that the AIs are rounding us all up with, with, uh, you know, uh, autonomous weapons or something. It's more just that the humans get kind of lazy and they just follow what the AIs tell them to do. Now, it's, it's sort of an interesting question. What, uh, what then do the AIs lead the humans to do? What's happened with sort of the current round of AI is that we've trained those AIs from, you know, a trillion words of what we humans have written, so to speak. And what the AIs have got out of that is kind of the average of what humans have said.

• 47:31Speaker 03

  And so there's a great tendency to say, well, we're kind of going to, everything's going to be average. Everything's going to be, you know, the AI is going to say, the AI is going to say a definite thing. The AI is going to say things that are kind of in some sense, the average of what we humans say. Now, we can certainly imagine setting things up so that the AI is, is trying, not what's done right now, but one can imagine something where the AI is trying to be kind of an awkward AI that is trying to say the things that are like the, the unexpected, controversial kind of corners of what we humans have said. Not, not the way that things are set up right now, but it's something one could sort of imagine. But the fact is that, that sort

• 48:11Speaker 03

  of the, the, the tendency is sort of to be, to be circling around sort of the average that the AI has learned from all the things we've produced. Now, it's worth saying that the way you, one way you break out of that is you start doing computations. What comes from just sort of averaging all the things we humans have written is something that is just sort of statically there. When we compute things, it is easy for us to compute things that have never been computed before, to go out into the ruliad, basically, and find things that we can, we can just sort of pick at random what direction we go, and we'll go to places that have never been visited before.

• 48:49Brian Keating?

  Is there, is there an optimum way to colonize the ruliad, Stephen?

• 48:53Speaker 03

  Well, what we've been doing in a sense, as we develop sort of an intellectual history, I see as being a progressive colonization of the ruliad. I mean, that is, you can think about any mind.

• 49:04Speaker 00

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• 49:33Speaker 03

  With any sort of paradigm for thinking about things is lives at a point in the ruliad, a place in the ruliad. As we sort of expand our domain of thinking, as we get more paradigms for thinking about things, we're colonizing the ruliad, much like we get different points of view about the universe by sending spacecraft out further and further to kind of explore what different points of view on the universe. Where in rulial space, the development of paradigms is kind of the successive expansion of the ruliad. Now, you know, what directions do we go? Well, that's what we societally tend to choose. We say, we're going to colonize in this direction. We're going to develop our paradigms in this direction. These are the kinds of things that we're going to understand. These are the kinds of things that are going to turn into words in

• 50:18Speaker 03

  our languages, where those words in our languages are things where we can exchange those words between us, and we all sort of have collective agreement about what those words mean. So, in a sense, there is a sort of a big expansion that we can make in the ruliad to many things that seem completely alien to us. With our finite minds, we tend to go only in particular paths out into the ruliad, where we are, we're exploring things that we can kind of still think about in our minds. And that's, you know, there are, there are many contingencies, there are many possibilities of how sort of human intellectual history could have developed. We've picked particular ones. Now, there's sort of a, it's a fair question, are there better ones versus

• 51:00Speaker 03

  worse ones to pick? I don't know the answer to that fully. I've studied that a bit in the case of mathematics. When we develop mathematics, there are maybe three or four million theorems that human mathematicians have, have written down in the history of human mathematics. But there are an infinite number of possible theorems of mathematics. And there's a question of how do we explore those infinite number of possible theorems of mathematics, which by the way, are, we can think of as being elements of the ruliad. So how do we, you know, what are the paths we could follow? Are there paths that are somehow more, more productive than other paths?

• 51:34Brian Keating?

  Right.

• 51:35Speaker 03

  Well, in the end, I think it depends a lot on what endpoint you're looking for. So in other words, there are things where we can say, this is the direction we could go, but the place we end up with. Is something that is very unfamiliar to us humans, perhaps in the case of more physics-related things, perhaps is something that does not map well onto the biological senses that we happen to have.

• 51:55Brian Keating?

  So you speak about rulial particles, which to me, you know, is inescapable to not think about. The other way that you can colonize the rulial quickly is to have, you know, massless particles, right? So you can either shorten the distances or you can speed up the rocket ships or the particle. And first, can you please explain rulial particles and what those are in the context of the communication that we are engaging with and so forth? But also, are there more efficient ways, particulate forms of rulial particles that have massless properties that travel at some ultimate speed limit? Does C apply to thinking?

• 52:34Speaker 03

  That's a good and interesting question and complicated. So first thing to say is I think our perception of the universe critically depends on the fact that we're not massless. In other words, if we were photons, massless particles, time would not elapse for us. And our perception of the photons that you collect, cruelly collect in your detector, those photons, the last thing they knew was when they were emitted at, you know, at recombination time, you know, 100,000 years after the beginning of the universe. And the next thing they know is splat, they ran into, you know, Brian's detector of those photons. That, you know,

• 53:13Speaker 03

  there was no, they had no experience between those two things. They led to their minds very short lives from the beginning of the universe to smashing into your detector. But so it is, our perception of the universe critically depends on the fact that we are not massless particles. We have an experience of time that, you know, our experience of the universe is an experience of the progression of time. I mean, the progression of time we can think of as being kind of the doing, the universe doing computation, we're part of the doing of that computation. And it's it's for us to experience that we can't operate like massless particles.

• 53:56Speaker 03

  Now, in terms of kind of this idea of real particles, that that's the the the kind of the the point there is you're at different places in physical space. How do you communicate across physical space? Well, you need a you need the even the possibility of communication requires the idea of motion. It has to be the case that a thing can go from one place in the universe to another and still be the same thing. This is something people worried about in antiquity, how that works. By the time of, for example, Galileo, Galileo sort of just said, well, you know, motion is what it is, and and then tried to analyze how motion works. The fact that motion is possible is not obvious.

• 54:38Speaker 03

  It even in traditional physics, if you're close enough to a spacetime singularity, any material object, you know, your spacecraft or whatever else, will be distorted beyond recognition when you're close to that spacetime singularity. But most of the time, we can think of pure motion as being a thing. Now, the question is, well, what is ultimately the carrier of pure motion? What is the thing that we can sort of move around the universe without changing? And the answer to that is basically particles, like electrons and and photons and things like that. Those are the, in a sense, the elementary carriers of pure motion, the things that move around the universe without changing. An electron in in our models, electrons are made of atoms of space, and the atoms of

• 55:21Speaker 03

  space of which an electron is made will change as the electron moves. It's like if you have an eddy in in a in water or something, the the molecules that make up that eddy will change as the eddy moves, but yet the eddy preserves its identity. So that's the sense in which sort of particles are things that preserve their identity under motion. And so then the question is, well, we have in real space, we have all these minds in different places in real space. And the question is, what is it that can be transported from one mind to another? So at a very practical level, you know, in in my mind, there are sort of neuron firings going on, and I'm I'm thinking of some concept, I'm thinking of a cat or something like. This and that corresponds to some pattern of neuron firings in my mind.

• 56:03Speaker 03

  In your mind, the way that you represent the concept of a cat will be a completely different set of neuron firings. So the question is, how do we, how do we sort of get, what is it that we can move from my mind to yours? That will communicate this concept of a cat that has to be, you know, packaged up and unpacked at the other end in different forms. And the thing that this is, we're kind of moving from one mind to another across real space. We're trying to move something from one mind to another. The thing we try to move that is sort of packaged up is what we imagine, what we think of as concepts. Concepts where, where a concept is something which is sort of the packaging of all those neuron firings

• 56:45Speaker 03

  into a robust thing that we will often describe with a word in human language and that then can be unpacked by another mind. So if you're asking, I mean, the, to me, it's sort of a remarkable analogy between things like particles, like electrons and so on, and the, the notion of concepts that are transportable from one mind to another. But now you're asking me to go further than that and to talk about what would it mean if there were sort of things, concepts that were like massless particles? And I suppose the, um, in a sense, what one would imagine, okay, so, so this is a, the, it, it's like what happens to that poor photon

• 57:26Speaker 03

  that is emitted and then a moment later for it, it smashes into your detector. It's, I think, the typical sort of particle that exists in the universe, which has mass. What is mass? Well, mass, I think, okay, so in the traditional modern theories of physics and the standard model and so on, what gives particles mass is their continual interaction with the condensate of the Higgs field. So the, the kind of thing which is always, I've always thought was a bit of a kludge is the idea that particles get mass because throughout the universe, there's this field that exists. And as a particle moves, it's constantly interacting with that field.

• 58:10Speaker 03

  It's constantly being kind of kicked.

• 58:12Brian Keating?

  That's like the ether view of it. That's the ether, almost.

• 58:15Speaker 03

  Well, it is, yes, but we have an ether again. It's the Higgs condensate. Okay, so in, in, in our models, it works differently from that. Because space in, in the, in sort of physics, as it has been worked on the last hundred years or so, there's the idea that space is just this background thing. And so to have something that particles have to sort of put effort into to getting through, you have to introduce something like the Higgs field where you're saying, and the particles keep on getting, interacting with this background field. The vacuum in usual physics is just like, well, the particles just go through the vacuum. Nothing much happens. Well, in our models, the vacuum is, space has to be made.

• 58:59Speaker 03

  Space is not something that just exists as a background. Space is constructed out of sort of the, the aggregate effect of all of these sort of processes that are going on in this network that, that we ultimately think of as being space. And so when we think about a particle sort of moving, what we're thinking about is that particle is being recreated out of different atoms of space at every successive moment of time. And so this idea that, that when we have a massive particle, we're thinking about that as being part of the sort of the recreation of the particle as it, as it goes through space. So an analogy, if you have a piece of glass, for example, and you shine a light through it, it is not the case

• 59:45Speaker 03

  that the photons just go straight through the piece of glass. Instead, what's happening is the photons are being absorbed by, by atoms in the glass. And then a moment later, another photon is being re-emitted that goes on and goes on going through the glass. That's why, that's why light goes, you know, one and a half times slower in glass than it does in a vacuum. It's because what's happening is the, the, the photons keep on getting absorbed, then there's a bit of a delay, then they get re-emitted again. And that's, that's kind of the process that's going on. And you can think of that as being sort of very qualitatively similar to what we imagine is happening for massive particles in the actual structure of space in our universe.

• 1:00:25Speaker 03

  But I'm not answering your question of what. So I think my best sort of immediate analogy there would be that would be to say that I think, and I don't know whether the analogy can be stretched this far, but I think that sort of the massless concepts are the ones where there is sort of inevitably no difference of interpretation between the emitting mind and the receiving mind. I'm not sure if that's right, but that's what I would. That would be. So it's kind of like when you have a massive particle, things happen to it on its way from the emitter to the receiver. Whereas when you have a massless particle, things aren't happening to it. That's why no time has passed for it. There's nothing

• 1:01:10Speaker 03

  happened to it on its way from the emitter to the receiver. But I'm not sure. It's a good question. And I, you know, it's always, one of the things that's always difficult, I'm sort of reminded of my long ago friend, Dick Feynman, who was always very big on the kind of intuitive explanations of things. And that's what people heard from him is the intuitive explanation of everything. But behind the scenes, he was a really good calculator.

• 1:02:05Speaker 03

  And so he would do all these calculations and work out, you know, this is how it had to work. And then he thought, oh, the calculations are easy. Nobody wants to see that stuff. I'm just going to tell them this intuitive explanation. But he knew the intuitive explanation was right because he did this calculation underneath.

• 1:02:21Brian Keating?

  That's right.

• 1:02:22Speaker 03

  Sometimes you can kind of jump from tree to tree, so to speak, with pure intuitive explanations. It's it's complicated. Sometimes the, you know, I I think when one gets good at it, you can do a lot of tree to tree jumping, so to speak. In some, in some sense, the, uh, uh, you know, there's, there's also a certain grounding. I mean, for me, uh, you know, for Dick Feynman, that grounding was always mathematical calculations done by hand or pieces of paper. For me, it's computer experiments. I mean, that's kind of the way that I ground my thinking about things is, you know, you do these experiments. And and one of the things about these experiments, which is related to the whole computational reducibility story and so on,

• 1:03:04Speaker 03

  is that very, very often those experiments reveal things that are not what one's intuition expected would happen. In other words, there's, there's a lot of surprises out there in the computational universe. You know, that's a thing that I I'm continually, you know, it's, it's a, it's a continual sort of humbling experience that sort of practically every week I'll have a thing that I'm studying and it's like, I'm sure it's going to do this. But I wouldn't have bothered to study it unless I had some idea of what it was going to do. But then when I actually run it, actually see the results of the experiments, it's no, actually it managed to do this other thing in a very clever way that I never imagined.

• 1:03:41Brian Keating?

  It's like the free will of the equations. I mean, that's, that's masterful. So Stephen, I have a couple of minutes left, but I I want to ask you something. I and forgive me if it's too pedantic, uh, but I kind of think of the Ruliad as sort of the ultimate Amazon web service, you know, cloud provider or something that's running these computational processes. And each instance, uh, you know, node is a, is a physical rule and so forth. But if if I were to analogize, make that analogy, that, you know, you could almost think of it as all these clients, you know, in this distributed That, you know, is abstract in some sense. What would you, given what you just said about surprise and the experiments?

• 1:04:21Brian Keating?

  If you could, you know, force the really add to do something or rent out one very dense portion of it to solve one physical problem, one problem in math or physics, what would be the problem that you'd most like to direct the computational firepower, the biggest computational firepower in the universe, perhaps the whole universe? What would you direct it to? What is the most important problem to you right now?

• 1:04:42Speaker 03

  Well, that's a, that's a hypothetical that's hard to sort of imagine executing on. I mean, I think that the, um, what's the most important problem? I mean, I, it, uh, it's again, there are things I'd like to know the answer to. It's, uh, uh, there are plenty of things, you know? We humans have a certain sort of human experience and existence. And it's, uh, you know, it'd be fun, you know, if we, if we talk about what do we want to solve? Like human immortality, that would be a fine thing to solve.

• 1:05:12Brian Keating?

  Yeah.

• 1:05:12Speaker 03

  Now, I've actually sort of looked at that a bit from a computational point of view, what's actually involved? If you, you know, what is the foundational thing that's happening in life and biology and so on? It's again, a big computational irreducibility story. And unfortunately, it makes things look pretty difficult. Cause it's like when you're, if you're thinking about sort of medical kinds of things, you say, okay, we've got the system. It was a sort of a piece of computational irreducibility that was adapted to the things that, you know, we humans do and so on. And now let's say you perturb it, you poke it in some way. Well, it does these unpredictable things. And then you say, well, what's the fundamental problem of medicine?

• 1:05:53Speaker 03

  It's to, after the thing got poked and started doing the things you didn't expect it to do, can you poke it again and get it back on track? And the whole sort of computational irreducibility story tells you just how hard it is to do that. It's again, it's a little bit related to the whole free will question also. If you if you want to have a rich life, so to speak, that does many things, it's hard to say, let's have something that will kind of persist forever. Because there are things, I mean, we we can, we can easily make cell cultures that are kind of tumor cells or something that will persist forever. But we don't think that's a great way to live, so to speak. For us humans, the most obvious sort of big thing would be kind of how do we take,

• 1:06:38Speaker 03

  and it's not obvious how that is even sort of conceivable. You know, how do we take the kind of experience that we have? And if you like what's going on, which somebody like me tends to like, it's it's kind of you like your life you're living. You kind of want to make that go on as long as possible. And so that, I mean, that that's a, that's an example of a kind of a, uh, where you could. But I, you know, as I said, I think it is a fundamentally computationally difficult problem. I don't think it's one of these things where it's like, I mean, we're, if you look at sort of what we are constructed out of, we are sort of the sole example of a successful molecular scale computational system. Life is a kind of molecular scale computational system.

• 1:07:23Speaker 03

  And it's hard to kind of, uh, uh, the things that we do that are our current sort of approaches to medicine and things like that tend to be these very coarse things where you say, just send in that molecule everywhere and and you know, hope that it that it binds to the right things and so on. I mean, we have, you know, within ourselves, we have things like the immune system that's a bit more sophisticated at going in and sort of tweaking what's going on. But we're, we're still, we're pretty far away from that. But it's not even clear sort of at a, at a very almost philosophical level. If you sort of achieve immortality, but you achieve it. Again, it's kind of like when when people say, can we adapt AI to do some particular thing?

• 1:08:06Speaker 03

  You say, well, you adapt AI, you know, the the classic is to make as many paper cups as possible. And then it turns the whole, you know, surface of the planet into into a paper cup factory or whatever. And and, you know, the same thing, you want. The biological thing that kind of can continue forever. As I say, it's easy to get that, but it's not a good life type thing. That's right. Um. So I mean, that's a, that's, that will be an example. I mean, I think that the, you know, there are things, it's always complicated. When, when you ask for uh things that, but let's say you say, well, I'd really like to know the fundamental theory of the universe. Yeah. Okay, which I've worked on a lot. Yeah. But that's a complicated thing. What do you really mean by that?

• 1:08:48Speaker 03

  You know, with the rule of add, we have in a sense, what I'm pretty sure is the fundamental theory. But making the connection between that and what we humans are, are kind of what we humans can talk about, can, can perceive and so on. That's a different, different thing, which seems like it's, it's not quite find the fundamental theory. I mean, in terms of things that I'm sort of chasing right now, uh, you know, I'm, I'm very interested in sort of experimental implications of the sort of fundamental theory of physics that we have. Uh, I've been having fun using L L M's as my kind of collaborators in trying to study that, you know, there's a million papers about, that have been published about physics.

• 1:09:30Speaker 03

  And the question is, are there effects that have already been known, that have been known for thirty years, fifty years, whatever? Which, when correctly interpreted, one realizes, oh, that's actually a sign of this thing that our models predict. You know, the, the cautionary tale is Brown in Motion, which was, you know, people wondered throughout the nineteenth century, do molecules exist? And nobody knew. But the fact is, in eighteen twenty seven, Robert Brown, a botanist, had observed, you know, these little pollen grains getting kicked discreetly by water molecules. We didn't know that's what was going on, but they just observed, this is a weird effect. You know, it took until nineteen hundred, basically, for people to say, that thing that was discovered seventy years ago

• 1:10:13Speaker 03

  actually shows that molecules exist. So one of the challenges right now is, is there something that's sitting out there in the existing literature of physics? You don't even have to spend, you know, a hundred million dollars to do a new experiment. Right. Is there something that's already there where you just say, wait a minute, you know, if interpreted correctly, that's a sign. And it might be an experiment where people say, that was a really weird experiment. It produced a result we don't even believe because it's so weird, we don't have a theory to, to sort of back it up. But that's, you know, that, that's one very practical uh little application that, that I've been interested in for, for L L M's.

• 1:10:49Brian Keating?

  Very nice. Well, I do want to wrap up on that on that note, but I do want to say just one final question, which is, again, this is wonderful article you're writing is every bit the equal of your mathematics, which is, you know, the highest compliment, I think, I can give to a guest. It's beautiful. It's poetic. There's so many just incredibly stimulating aspects of this article that we'll link to in the show notes down below. But the final question is how you end it. You know, you talk about kind of a ruliad spanning mind that that can take care of all possible computations. But as with the mind of a human, as I get older, maybe I can do one thing in working memory, as you discuss, not even

• 1:11:32Brian Keating?

  three or four. But if it could have sort of this, you know, incorporation of all possible computations, but would it not lose coherency of what we experience, sort of where we started off? And the question is, can we know if AI systems are really minds like ours? Or are they really truly, as you maybe are hinting at, a type of alien that we have on Earth that we maybe created ourselves? But are they minds like ours? Are they something completely different?

• 1:12:03Speaker 03

  Well, it's easy to make an AI mind that's not like ours. You know, lots of things I've spent time doing of sort of exploring the computational universe, sort of running these arbitrary programs and so on. That makes that does computation. It does kind of, in some sense, mindlike stuff, but it's very alien to us. So it's it's easy to make minds that are very alien. It's easy to the challenge is to make, and that's sort of one of the achievements of modern AI, is to make computational minds that are aligned enough with us that we think what they're doing is worth doing, so to speak.

• 1:12:46Speaker 03

  And that's that's kind of you're asking what sort of what happens as we as we make those you know those AI minds kind of broader and broader do they um you know and the answer is it's easy to make a broad AI mind and it's easy to make an AI mind that doesn't have the kind of coherent existence that we have it's it's uh you know it is the case that the neural nets that we're making these days are built in our image and and do kind of human mind like things but as I say it's easy to get something which behaves more like nature behaves nature doesn't have this kind of this sort of filtering down to this kind of thread of consciousness of

• 1:13:31Speaker 03

  the kind that we have nature just does all these different things and that's that's an easy thing for us to be doing computationally and we'll look at that and we'll say well that kind of looks like nature it doesn't really look like a mind like a human mind like thing

• 1:13:49Brian Keating?

  Well Stephen this has expanded my mind you know my mom told me she named me Brian so that sometimes people would confuse me with brain and it does occur quite frequently uh but you are always wrinkling the brain and and new and interesting ways and uh I just can't wait to see what comes next whether it's a book or another article we'll link to your blog uh I really just just appreciate you spending so much of your time with me especially so late at night uh you were meant to be an astronomer I think you missed your calling you have this propensity to stay up all night uh Stephen I really appreciate you thank you so much and do let us know uh I we haven't met up in about eight years by my reckoning so um maybe we'll

• 1:14:27Speaker 03

  I feel like I met you because I see you so much on on you know on

• 1:14:30Brian Keating?

  No we met through Museum of Math and and so far

• 1:14:33Speaker 03

  No I know we've met in person

• 1:14:34Brian Keating?

  Yeah

• 1:14:35Speaker 03

  My test is always do I know roughly how tall this person is if the answer is yes then we met in person if the answer is I haven't the slightest idea then we probably never met in person but we definitely met and I look forward to to meeting again

• 1:14:48Brian Keating?

  Me too Stephen thank you so much

• 1:14:50Speaker 02

  If this episode blew your mind go watch my last interview from 2024 with Stephen where we unpacked the really ad from the ground up we uncovered the reality of time and he even helped me understand the fundamental basics of how he views the second law of thermodynamics won't see physics or thought the same way ever again click here and don't forget to subscribe

• 1:15:12Speaker 05

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