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Stephen Wolfram: Fundamental Theory of Physics, Life, and the Universe | Lex Fridman Podcast #124

Stephen Wolfram is a computer scientist, mathematician, and theoretical physicist. Please check out our sponsors to get a discount and to support this podcast: - SimpliSafe: https://simplisafe.com/lex - Sun Basket, use code LEX: https://sunbasket.com/lex - MasterClass: https://masterclass.com/lex EPISODE LINKS: Wolfram Physics Project: https://www.wolframphysics.org/ Stephen's Twitter: https://twitter.com/stephen_wolfram Stephen's Blog: https://writings.stephenwolfram.com Books: - A New Kind of Science: https://amzn.to/3kotO6S - A Project to Find the Fundamental Theory of Physics: https://amzn.to/3mA3OaS PODCAST INFO: Podcast website: https://lexfridman.com/podcast Apple Podcasts: https://apple.co/2lwqZIr Spotify: https://spoti.fi/2nEwCF8 RSS: https://lexfridman.com/feed/podcast/ Full episodes playlist: https://www.youtube.com/playlist?list=PLrAXtmErZgOdP_8GztsuKi9nrraNbKKp4 Clips playlist: https://www.youtube.com/playlist?list=PLrAXtmErZgOeciFP3CBCIEElOJeitOr41 OUTLINE: 0:00 - Introduction 7:14 - Key moments in history of physics 12:43 - Philosophy of science 14:37 - Science and computational reducibility 22:08 - Predicting the pandemic 38:58 - Sunburn moment with Wolfram Alpha 39:46 - Computational irreducibility 46:45 - Theory of everything 52:41 - General relativity 1:01:16 - Quantum mechanics 1:06:46 - Unifying the laws of physics 1:12:01 - Wolfram Physics Project 1:29:53 - Emergence of time 1:34:11 - Causal invariance 1:53:03 - Deriving physics from simple rules on hypergraphs 2:07:24 - Einstein equations 2:13:04 - Simulating the physics of the universe 2:17:28 - Hardware specs of the simulation 2:24:37 - Quantum mechanics in Wolfram physics model 2:42:46 - Double-slit experiment 2:45:13 - Quantum computers 2:53:21 - Getting started with Wolfram physics project 3:14:46 - The rules that created our universe 3:24:22 - Alien intelligences 3:32:29 - Meta-mathematics 3:37:58 - Why is math hard? 3:52:55 - Sabine Hossenfelder and how beauty leads physics astray 4:01:07 - Eric Weinstein and Geometric Unity 4:06:17 - Travel faster than speed of light 4:16:59 - Why does the universe exist at all CONNECT: - Subscribe to this YouTube channel - Twitter: https://twitter.com/lexfridman - LinkedIn: https://www.linkedin.com/in/lexfridman - Facebook: https://www.facebook.com/LexFridmanPage - Instagram: https://www.instagram.com/lexfridman - Medium: https://medium.com/@lexfridman - Support on Patreon: https://www.patreon.com/lexfridman

Lex FridmanhostStephen Wolframguest
Sep 15, 20204h 23mWatch on YouTube ↗

EVERY SPOKEN WORD

  1. 0:007:14

    Introduction

    1. LF

      The following is a conversation with Stephen Wolfram, his second time on the podcast. He's a computer scientist, mathematician, theoretical physicist, and the founder and CEO of Wolfram Research, a company behind Mathematica, Wolfram|Alpha, Wolfram Language, and the new Wolfram Physics project. He's the author of several books, including A New Kind of Science, and the new book, A Project to Find the Fundamental Theory of Physics. The second round of our conversation is primarily focused on this latter endeavor of searching for the physics of our universe in simple rules that do their work on hypergraphs and eventually generate the infrastructure from which space, time, and all of modern physics can emerge. Quick summary of the sponsors: SimpliSafe, Sunbasket, and MasterClass. Please check out these sponsors in the description to get a discount and to support this podcast. As a side note, let me say that, to me, the idea that seemingly infinite complexity can arise from very simple rules and initial conditions is one of the most beautiful and important mathematical and philosophical mysteries in science. I find that both cellular automata and the hypergraph data structure that Stephen and team are currently working on to be the kind of simple, clear mathematical playground within which fundamental ideas about intelligence, consciousness, and the fundamental laws of physics could be further developed in totally new ways. In fact, I think I'll try to make a video or two about the most beautiful aspects of these models in the coming weeks, especially, I think, trying to describe how fellow curious minds like myself can jump in and explore them either just for fun or potentially for publication of new innovative research in math, computer science and physics. But honestly, I think the emerging complexity in these hypergraphs can capture the imagination of everyone, even if you're someone who never really connected with mathematics. That's my hope at least, to have these conversations that inspire everyone to look up to the skies and into our own minds in awe of our amazing universe. Let me also mention that this is the first time I ever recorded a podcast outdoors as a kind of experiment to see if this is an option in times of COVID. I'm sorry if the audio is not great. I did my best and promise to keep improving and learning as always. If you enjoy this thing, subscribe on YouTube, review it with five stars on Apple Podcast, follow on Spotify, support on Patreon, or connect with me on Twitter @lexfridman. As usual, I'll do a few minutes of ads now and no ads in the middle. I try to make these interesting, but I do give you timestamps so you're welcome to skip, but still please do check out the sponsors by clicking the links in the description. It's the best way to support this podcast. Also, let me say, even though I'm talking way too much, that I did a survey and it seems like over 90% of people either enjoy these ad reads somehow magically or don't mind them at least. That honestly just warms my heart that people are that supportive. This show is sponsored by SimpliSafe, a home security company. Go to simplisafe.com to get a free HD camera. It's simple, no contracts, 15 bucks a month, easy setup. Even I figured it out. I have it set up in my apartment. Of course, I also welcome intruders. One of my favorite movies is Leon or The Professional with Jean Reno, Gary Oldman, and the brilliant young Natalie Portman. If you haven't seen the movie, he's a hitman with a minimalist life that resembles my own. In fact, when I was younger, the idea of being a hitman or targeting evil in a skilled way, which is how I thought about it, really appealed to me. The skill of it, the planning, the craftsmanship. In another life perhaps, if I didn't love engineering and science so much, I could see myself being something like a Navy SEAL and, in general, I love the idea of serving my country, of serving society by contributing my skill in some small way. Anyway, go to simplisafe.com/lex to get a free HD camera and to support this podcast. They're a new sponsor and this is a trial run, so you know what to do. This show is also sponsored by Sunbasket, a meal delivery service. Visit sunbasket.com/lex and use code Lex to get $30 off your order and to support this podcast. This is the last read of the trial they're doing so this is the time to get them if you're considering it, and if you do, it'll help ensure that they decide to support this podcast long term. Their meals are healthy and delicious, a nice break from the minimalist meals of meat and vegetables that I usually eat. Maybe on a personal note, one of my favorite things to do is watch people cook, especially people who love cooking, and hang out with people over amazing meals. I still tend to be strict in my diet no matter what, even in fancy restaurants, but it brings me joy to see friends and family indulge in something like a cake that has way too many calories or ice cream or whatever. My mom, in fact, for much of my life made this cake called an anthill on my birthday that brings me a lot of joy and way too many calories (laughs) . I was thinking of doing a video with my mom as she makes it. I thought it'd be a fun thing to, to do together. Anyway, go to sunbasket.com/lex and use code Lex. Do it now so they sign a long term contract with this podcast. This show is also sponsored by MasterClass. Sign up at masterclass.com/lex. 180 bucks a year, you get an all-access pass to watch lessons from Chris Hadfield, Neil deGrasse Tyson, Tony Hawk, Carlos Santana, Garry Kasparov, Daniel Negrano, and many more brilliant world experts.Masterclass has been a really special sponsor. They believe in this podcast in a way that gives me strength and motivation to take intellectual risks. I'm thinking of doing a few solo podcast episodes on difficult topics, especially in history, like the rise and fall of the Third Reich, or Stalin, Putin, and many other difficult topics that I'm fascinated by. I have a worldview that seeks inspiring positive insights even, and perhaps especially, from periods of tragedy and evil that perhaps some folks may find value in if I can only learn to convey the ideas in my mind as clearly as I think them. I think deeply and rigorously and precisely, but to be honest, have trouble speaking in a way that reflects that rigor of thought. So, it really does mean a lot, the love and support I get as I try to get better at this thing, at this talking thing. Anyway, go to masterclass.com/lex to get a discount and to support this podcast. And now, finally, here's my conversation with Stephen Wolfram.

  2. 7:1412:43

    Key moments in history of physics

    1. LF

      You said that there are moments in history of physics, and maybe mathematical physics or even mathematics, where breakthroughs happen and then a flurry of progress follows. So, if you look back through the history of physics, are, what moments stand out to you as important such breakthroughs where a flurry of progress follows?

    2. SW

      So, the big famous one was 1920s, the invention of quantum mechanics, where, you know, in about five or 10 years, lots of stuff got figured out that's now quantum mechanics.

    3. LF

      Can you mention the people involved?

    4. SW

      Yeah.

    5. LF

      Like, key people?

    6. SW

      It was kind of the Schrodinger, Heisenberg, you know, Einstein had been a key figure. Originally Planck, then Dirac was a little bit later. That was something that happened at that time. That's sort of before my time, right?

    7. LF

      (laughs)

    8. SW

      In my time was in the 1970s, uh, there was this sort of realization that quantum field theory was actually going to be useful in physics, and, uh, QCD, quantum chromodynamics theory of quarks and gluons and so on, was really getting started. And, uh, there was again, sort of big flurry of things happened then. I happened to be a teenager at that time, and happened to be, uh, really involved in physics. And so I got to be part of that, which was really cool.

    9. LF

      Who- who were the key figures, aside from your young selves at that time?

    10. SW

      You know, who won the Nobel Prize for QCD, okay? People, David Gross, Frank Wilczek, you know, um, David Politzer. The people who were the sort of the slightly older generation, Dick Feynman, Murray Gell-Mann, people like that, uh, uh, who were Steve Weinberg, Gerard 'Hoft, he's younger. He's, he's in the younger group, actually. But, um, these are, these are all, you know, characters who were involved. I mean, it was, uh, you know, it's funny because those are all people who were kind of in my time, and I know them, and they don't seem like sort of, uh, these historical...

    11. LF

      (laughs) Einstein figures.

    12. SW

      ... you know, iconic figures. They seem more like, uh, everyday characters, so to speak. Um, and, uh, so it's always, you know, wh- when you look at history from long afterwards, it always seems like everything happened instantly, um, and that's usually not the case. There was usually a long build-up. But usually there's, you know, there's some methodological thing happens, and then there's a whole bunch of low-hanging fruit to be picked, and that usually lasts five or 10 years. You know, we see it today with machine learning, and, you know, uh, deep learning neural nets and so on. You know, methodological advance, things actually started working in, you know, 2011, 2012, and so on. And, uh, you know, there's been this sort of rapid, uh, picking of low-hanging fruit, which is probably, you know, mm, some significant fraction of the way, way done, so to speak.

    13. LF

      Do you think there's a key moment? Like, if I had to really introspect, like what was the key moment for the deep learning, quote unquote, revolution? I mean-

    14. SW

      Th- it's probably the AlexNet business

    15. NA

      Yeah.

    16. LF

      ... with ImageNet.

    17. SW

      Yeah.

    18. LF

      So, is there something like that with physics where... So, deep learning neural networks have been around for a long time.

    19. SW

      Absolutely. It's the 1940s, yeah.

    20. LF

      There's a bunch of little... There's a bunch of little pieces that came together, and then all of a sudden everybody's eyes lit up. Like, wow.

    21. SW

      Right.

    22. LF

      There's something here. Like, even just looking at your own work, just your thinking about the universe, that there is simple rules can create complexity. You know, at which point was there a thing where your eyes light up? It's like, wait a minute, there's something here. Is it the very first idea, or is it some moment along the line of implementations and experiments and so on?

    23. SW

      Yeah. There's, there's a couple of different stages to this. I mean, one is the think about the world computationally. You know, can we use programs instead of equations to make models of the world? That's something that I got interested in in the, at the beginning of the 1980s. You know, I did a bunch of computer experiments. Uh, you know, when I first did them, I didn't really, I s- I could see some significance to them, but took me a few years to really say, "Wow, there's a, a big important phenomenon here that lets sort of complex things arise from very simple programs." Um, that kind of happened back in 1984 or so. Then, you know, bunch of other years go by, then I start actually doing, uh, a lot of much more systematic computer experiments and things and find out that the, you know, this phenomenon that I could only have said occurs in one particular case is actually something incredibly general. And then that led me to this thing called principle of computational equivalence, and that was a, a long story. And then, you know, as part of that process, I was like, "Okay, you can make... Simple programs can make models of complicated things. What about the whole universe?" That's our sort of ultimate example of a complicated thing.

    24. LF

      Yeah.

    25. SW

      And so I got to thinking, you know, could we use these ideas to, to study fundamental physics?... a you know, I happen to know a lot about, you know, traditional fundamental physics. My, um, uh, my first, you know... I, I had a bunch of ideas about how to do this in the early 1990s. I made a bunch of technical progress, I figured out a bunch of things I thought were pretty interesting, you know, I wrote about them back in 2002. Um-

    26. LF

      With A New Kind of Science and The Cellular Automata World and-

    27. SW

      Right.

    28. LF

      ... there's echoes in The sem- Cellular Automata World with your new, uh, Wolfram Physics Project world. We'll get to all that. Allow me to-

    29. SW

      Yeah.

    30. LF

      ... sort of romanticize a little more on the philosophy of science. (laughs) Uh,

  3. 12:4314:37

    Philosophy of science

    1. LF

      so Thomas Kuhn, a philosopher of science, describes that, you know, the progress in science is made with, uh, these paradigm shifts. And so to linger on the sort of original line of discussion, do you agree with this view that there is revolutions in science that just kind of flip the table?

    2. SW

      Yeah. What happens is, it's a different way of thinking about things, it's a different methodology for studying things, and that opens stuff up.

    3. LF

      There's this idea of, uh... (sighs) He's a famous biographer but I think it's called The Innovators. The biographer of Steve Jobs, of Albert Einstein-

    4. SW

      Oh, yeah.

    5. LF

      He also wrote a book, I think it's called The Innovators, where it, he discusses, uh, how a lot of, uh, the innovations in the history of computing has been done by groups. There's complicated group dynamic going on. But there's also a romanticized notion that the individual is at the core of the revolution. Like, where does your sense fall? Is, is, um, ultimately, like, one person responsible for these revolutions that, that creates the spark? Or one or two, whatever, but... Or is it just the big mush and mess and chaos of, of people interacting, of personalities interacting ...?

    6. SW

      I think it ends up being like many things. There's leadership and there ends up being... It's a lot easier for one person to have a crisp new idea than it is for a big committee to have a crisp new idea.

    7. LF

      Yeah.

    8. SW

      And, um, I think, you know... But I think it, it can happen that, you know, you have a great idea but the world isn't ready for y- for it. And, um, you know, you can, you can... I mean, this has happened to me plenty, right? It's, you know, you have an idea, it's actually a pretty good idea but things aren't ready. Either, either you're not really ready for it or the ambient world isn't ready for it, and it's hard to get the thing to, to get traction.

  4. 14:3722:08

    Science and computational reducibility

    1. SW

    2. LF

      It's kind of interesting. I, I mean when I look at A New Kind of Science, you're now living inside the history so you can't tell the story of these decades. But it seems like The New Kind of Science has not had the revolutionary impact I would think it, uh, might. Like, it feels like at some point, of course it might be, but it feels at some point people will return to that book and say, "There was something special here. This was-"

    3. SW

      Well, look, wha- what happened-

    4. LF

      "... incredible." So... Or do you think that's already happened?

    5. SW

      Oh, yeah, it's happened except that people aren't, you know... The, the sort of the heroism of it may not be there. But the, what's happened is, for 300 years people basically said if you want to make a model of things in the world, mathematical equations are the best place to go. Last 15 years, doesn't happen. You know, new models that get made of things most often are made with programs, not with equations.

    6. LF

      Mm-hmm.

    7. SW

      Now, you know, was that sort of going to happen anyway? Was that a consequence of, you know, my particular work and my particular book? It's hard to know for sure. I mean, I am always amazed at the amount of feedback that I get from people where they say, "Oh, by the way, you know, I started doing this whole line of research because I read your book blah blah blah blah blah." It's like, well, can you tell that from the academic literature? You know, were, was there a chain of, you know, academic references? Probably not.

    8. LF

      One of the interesting side effects of publishing in the way you did this tome is it serves as an education tool and an inspiration to hundreds of thousands, millions of people. But because it's not a single, uh, is, it's not a chain of papers with spiffy titles, it doesn't create a splash of citations. Like-

    9. SW

      No, it's had, it's had plenty of citations. But it's, it's, you know, I think that the, it... People think of it as probably more, you know, conceptual inspiration than, uh, than kind of a, you know, this is a line from here to here to here in our particular field.

    10. LF

      Right.

    11. SW

      I think that the, you know, the thing which I am disappointed by, and which will eventually happen, is this kind of study of the, this sort of pure computationalism, this kind of study of the abstract behavior of the computational universe. That should be a big thing that lots of people do. ... get to-

    12. LF

      You mean in mathematics purely, almost like for some-

    13. SW

      It's like pure mathematics, but it isn't mathematics.

    14. LF

      But it isn't. It, it isn't.

    15. SW

      It's different.

    16. LF

      It's a new kind of mathematics is, is it... (laughs) And the title of the book-

    17. SW

      A new kind of science. Yeah, right. (laughs)

    18. LF

      (laughs) It's a good title.

    19. SW

      That's why the book is called that, right?

    20. LF

      (laughs)

    21. SW

      That, that's not coincidental. (laughs)

    22. LF

      Yeah. It's interesting that I haven't seen really rigorous investigation by thousands of people of this idea. I mean, you look at your competition around Rule 30. I mean, that's fascinating if y- if you can say something...

    23. SW

      Right.

    24. LF

      Is there some aspect of this thing that could be predicted?

    25. SW

      Right.

    26. LF

      That's the fundamental question of science. That's the core-

    27. SW

      Well, that has been a question of science. I think that's a, that is a, some people's view of what science is about, and it's not clear that's the right view. In fact, as we, as we live through this pandemic full of predictions and so on, it's an interesting moment to be pondering what, what science's actual role in those kinds of things is.

    28. LF

      Oh, you think it's possible that in science, clean, beautiful, simple prediction may not even be possible in real systems? That's the open question ... question I don't know.

    29. SW

      Right. I don't think it's open, I think that question is answered and the answer is no. (laughs) I mean-

    30. LF

      (laughs) Well, no, no, no answer could be just humans are not smart enough yet.... like we don't have the tools yet.

  5. 22:0838:58

    Predicting the pandemic

    1. SW

    2. LF

      Can we talk about this pandemic then-

    3. SW

      Sure.

    4. LF

      ... (laughs) for a second?

    5. SW

      A little bit. Yeah.

    6. LF

      Is, so how do we... so there's obviously huge amount of economic pain that people are feeling, there's a huge incentive and medical pain, uh, health, just all kind- psychological, there's a huge incentive to figure this out, to walk along the trajectory of reducible, of reducibility. Uh, there's a, there's a, a lot of disparate data. You know, people understand generally how viruses spread, but it's very complicated because there's a lot of uncertainty, uh, there's, uh, there could be a lot of variability, like, so many, obviously a nearly infinite number of variables that, uh, that represent human interaction, and so you have to figure out inter- from the perspective of reducibility, figure out which variables, uh, are really important in this kind of, uh, from an epidemiological perspective. So, why aren't we... you kind of said that we're clearly failing. (laughs)

    7. SW

      Well, I, I think it's a complicated thing. So, so, I mean, you know, when this pandemic started up, you know, I happened to be in, in the middle of being about to release this whole physics project thing-

    8. LF

      Yes.

    9. SW

      ... but I thought, you know-

    10. LF

      The timing is just, uh, cosmically absurd.

    11. SW

      A little bit, a little bit bizarre.

    12. LF

      Yeah.

    13. SW

      But, but, um, but, you know, but I thought, you know, I, I should do the public service thing of, you know, trying to understand what I could about the pandemic and, you know, we'd been curating data about it and all that kind of thing, but, but, you know, so I started looking at the data and started looking at modeling, and I decided it's just really hard. You need to know a lot of stuff that we don't know about human interactions. It's actually clear now that there's a lot of stuff we didn't know about viruses, um, and about the way immunity works and so on. And, um, it's, you know, I think what will come out in the end is there's a certain amount of, of what happens that way you just kind of have to trace each step and see what happens. There's a certain amount of stuff where there's gonna be a big narrative about th- this happened because, you know, of T-cell immunity. This ca- happened because there's this whole giant sort of field of, of, of asymptomatic viral stuff out there. You know, there will be a narrative, and that narrative, whenever there's a narrative, that's kind of a sign of reducibility. But when you just say, "Let's, from first principles, figure out what's going on," then you can potentially be stuck in this kind of, uh, mess of irreducibility where you just have to simulate each step, and you can't do that unless you know details about, you know, human interaction networks and so on and so on and so on. The thing that has, has been very-... sort of frustrating to see is the mismatch between people's expectations about what science can deliver and what science can actually deliver, so to speak. Um, because people have this idea that, you know, it's science, so there must be a definite answer, and we must be able to know that answer. And, you know, this is, it is both, uh, uh, you know, the- the- when you've- after you've played around with sort of little programs in the computational universe, you don't have that intuition anymore. You know, it's- it's- I always- I'm always fond of saying, you know, the- the- the- the computational animals are always smarter than you are. That is, you know, you look at one of these things and it's like, "It can't possibly do such and such a thing." Then you run it and it's like, "Wait a minute, it's doing that thing. How does that work? Okay, now I can go back and understand it."

    14. LF

      But that's the brave thing about science, is that in the chaos of the irreducible universe, we nevertheless persist to find those pockets, that's kind of the whole point. That's- like, you say that the limits of science, but that, you know, yes, it's highly limited, but th- there's a hope there. And, like, uh, there- there's so many questions I wanna ask here. So one, you said narrative, which is really interesting. So obviously from a- at every level of society, you look at Twitter, everybody's constructing narratives about the pandemic, about not just the pandemic, but all the cultural tension that we're going through. So there's narratives, but they're not necessarily connected to the underlying reality of these systems. So our human narratives, I don't even know if they're... I don't like those pockets of reducibility 'cause we're, um, it's like constructing things that are not actually representative of reality-

    15. SW

      Well, but-

    16. LF

      ... and thereby not giving us, like, good solutions to how to pre- predict the system.

    17. SW

      Look, it- it gets complicated because, you know, people want to say, "Explain the pandemic to me. Explain what's gonna happen."

    18. LF

      In the future, like predict-

    19. SW

      Yes, but- but also, can you explain it? Is there a story to tell?

    20. LF

      What already happened in the past?

    21. SW

      Yeah, or- or-

    22. LF

      Just- just in general.

    23. SW

      ... what's going to happen. But I mean, and- and, you know, it's similar to sort of ex- explaining things in AI or in any computational system. It's like, like, you know, explain what happened. Well, it could just be this happened because of this detail and this detail and this detail and a million details, and there isn't a big story to tell. There's no kind of big arc of the story that says, "Oh, it's because, you know, there's a viral field that has these properties and people start showing symptoms, you know, when- when the seasons change, people will show symptoms," and people don't even understand, you know, seasonal variation of flu, for example. It's a- it's a, um, uh, it's something where- where, you know, there- there could be a big story or it could be just a zillion little details that- that mount up.

    24. LF

      See, but... Okay. Let's- let's, uh, pretend that this pandemic, like the coronavirus resembles something like the 1D Rule 30 cellular automata, okay? So, I mean, that's how e- epidemiologists model virus spread.

    25. SW

      Indeed, yes.

    26. LF

      Is there some graphs-

    27. SW

      They sometimes use cellular automata, yes.

    28. LF

      Yeah. So... Yeah. And, okay, so you could say it's simplistic, but... Okay, let's say it- it is- it's representative of actually what happens. Uh, you know, the- the dynamic of you have a graph, it probably is closer to the hypergraph, uh, model.

    29. SW

      It is, yes. It's- it's actually...

    30. LF

      (laughs)

  6. 38:5839:46

    Sunburn moment with Wolfram Alpha

    1. SW

    2. LF

      Right.

    3. SW

      Hold on one second. I'm going to use my handy Wolfram|Alpha sunburn computation thing, so long as I can get a network here. There we go.

    4. NA

      Answer's

    5. LF

      sunburn.

    6. SW

      Oh, actually, you know what? It says sunburn unlikely.

    7. LF

      (laughs)

    8. SW

      This is a QA moment.

    9. LF

      (laughs) Ah. This is a good moment. Okay. (laughs)

    10. SW

      Okay. (laughs) Well, let's, let me just check what it thinks there.

    11. LF

      (laughs)

    12. SW

      I would see why it thinks that. It doesn't seem like my intuition. This is one of these cases where we can... The question is do we d- do we trust the science or do we, um, use common sense?

    13. LF

      The UV thing is cool. The...

    14. SW

      Yeah, yeah. Well, we'll see. This is a QA moment, as I say. It's, uh, it's like-

    15. LF

      (laughs)

    16. SW

      ... (laughs) do we trust the product? Yes, we trust the product. So, if I'm-

    17. LF

      And then there'll be a data point either way.

    18. SW

      Yeah, but if, if I'm desperately sunburned, I will send bin it in a angry feedback.

  7. 39:4646:45

    Computational irreducibility

    1. SW

    2. LF

      Because we mentioned the concept so much and a lot of people know it, but can you say what computational irreducibility is?

    3. SW

      Yeah, right. So it's, I mean, the, the question is, if you think about things that happen as being computations, you think about the, uh, some process in physics, something that you compute in mathematics, whatever else, it's a computation in the sense it has definite rules, you follow those rules, you, uh, follow them many steps, and you get some result. So then the, the issue is, if you look at all these different kinds of computations that can happen, whether they're computations that are happening in the natural world, whether they're happening in our brains, whether they're happening in our mathematics, whatever else, the big question is, how do these computations compare? Is, are there dumb computations and smart computations, or are they somehow all equivalent? And the thing that I kind of, uh, was sort of surprised to realize from a bunch of experiments that I did in the early '90s and now we have tons more evidence for it, this thing I call the principle of computational equivalence. Which basically says when one of these computations, one of these processes that follows rules, doesn't seem like it's doing something obviously simple, then it has reached the sort of equivalent level of sophisticate... of computational sophistication of everything. So, what does that mean? That means that, you know, you might say, "Gosh, I'm, I'm studying this little, tiny, you know, tiny program on my computer, I'm studying this little thing in, in nature, but I have my brain and my brain is surely much smarter than that thing. I'm gonna be able to systematically outrun the computation that it does, because I have a more sophisticated computation that I can do." But what the principle of computational equivalence says is that doesn't work. Our, our brains are doing computations that are exactly equivalent to the kinds of computations that are being done in all these other sorts of systems. And so what consequence does that have? Well, it means that we can't systematically outrun these systems. These systems are computationally irreducible in the sense that there's no sort of shortcut that we can make that jumps to the answer. Now, the-

    4. LF

      In a general case.

    5. SW

      Right. Right. The, but, but the... So, what has happened, you know, what science has become used to doing is using the little sort of pockets of computational reducibility, which by the way are an inevitable consequence of computational irreducibility that there have to be these pockets scattered around of computational reducibility to be able to find those particular cases where you can jump ahead. I mean, one, one thing, sort of a little bit of a parable-type thing that I think is, is fun to tell. You know, if you look at ancient Babylon, they were trying to predict three kinds of things. They tried to predict, you know, where the planets would be, what the weather would be like, and who would win or lose a certain battle.

    6. LF

      (laughs) Yeah.

    7. SW

      And they had no idea-

    8. LF

      Yeah.

    9. SW

      ... which of these things would be more predictable than the other.

    10. LF

      That's funny. (laughs)

    11. SW

      Uh, and, and, you know, it turns out, you know, where the planets are is a, is a piece of computational reducibility that, you know, 300 years ago or so we pretty much cracked. I mean, it's been technically difficult to get all the details right, but it's basically we, we got that. You know, who's gonna win or lose the battle? No, we didn't crack that one. That one-

    12. LF

      Not yet.

    13. SW

      ... that one, right. The, the, the-

    14. LF

      Game theorists are trying.

    15. SW

      Yes.

    16. LF

      And then the weather...... how are we-

    17. SW

      It's kind of halfway on that.

    18. LF

      Halfway? (laughs)

    19. SW

      Yeah. I think we're, we're doing okay at that one. I, uh, you know-

    20. LF

      So do you think-

    21. SW

      Long term climate, different story.

    22. LF

      (laughs)

    23. SW

      But the weather, you know, we're-

    24. LF

      But-

    25. SW

      ... we're much closer on that.

    26. LF

      But do you think eventually we'll figure out the weather? So, do you think eventually most thing... we'll figure out the local pockets in everything, essentially, the local pockets of reducibility?

    27. SW

      No. I think that the... it's, uh, it's an interesting question, but I think that the... you know, there is an infinite collection of these local pockets. We'll never run out of local pockets. And by the way, those local pockets are where we build engineering, for example. That's how we... You know, when we... if we want to have a predictable life, so to speak, then, you know, we have to build in these sort of pockets of reducibility. Otherwise, you know, if we were, if we were sort of existing in this kind of irreducible world, we'd never be able to, you know, have definite things to know what's gonna happen. You know, I, I have to say, I think one of the features, you know, when we look at sort of today from the future, so to speak, I suspect one of the things where people will say, "I can't believe they didn't see that," is stuff to do with the following kind of thing. So, so, you know, if we describe, oh, I don't know, something like, um, heat, for instance. We say, "Oh, you know, the air in, in here, it's, you know, it's this temperature, this pressure." That's as much as we can say. Otherwise, just a bunch of random molecules bouncing around. People will say, "I just can't believe they didn't realize that there was all this detail in how all these molecules were bouncing around, and they could make use of that." And actually, I realized, there's a thing I realized last week actually (laughs) was, um, was a thing that people say, you know, one of the scenarios for the very long term history of our universe is the so-called heat death of the universe, where basically everything just becomes thermodynamically boring. Everything's just this big kind of gas and thermal equilibrium. People say, "That's a really bad outcome." But actually, it's not a really bad outcome. It's an outcome where there's all this computation going on, and all those individual gas molecules are all bouncing around in very complicated ways, doing this very elaborate computation. It just happens to be a computation that right now, we haven't found ways to understand. We haven't found ways... you know, our brains haven't, you know, and our mathematics and our science and so on, haven't found ways to tell an interesting story about that.

    28. LF

      (laughs) That's, uh-

    29. SW

      It just looks boring to us.

    30. LF

      There's a... you're saying there's a hopeful view of the heat death, quote unquote, of the universe, where there's actual beautiful complexity going on-

  8. 46:4552:41

    Theory of everything

    1. LF

      So let's talk a little bit of physics. Maybe let's ask the, uh, the biggest question. What is a theory of everything? In general, what does that mean?

    2. SW

      Yeah. So I mean, the question is, can we kind of reduce what has been physics as a... something where we have to sort of pick away and say, "Do we roughly know how the world works?" To something where we have a complete formal theory where we say, "If we were to run this program for long enough, we would reproduce everything." You know, down to the fact that we're having this conversation at this moment, et cetera, et cetera, et cetera. We-

    3. LF

      Any physical phenomena, any phenomena in this world?

    4. SW

      Any phenomenon in the universe.

    5. LF

      Yeah.

    6. SW

      But the... you know, because of computational irreducibility, it's not... you know, that's not something where you say, "Okay, you've got the fundamental theory of everything, then, you know, tell me whether, you know, uh, lions are gonna eat tigers or something." You know, that's a... no, you have to run this thing for, you know, 10 to the 500 steps or something to know something like that. Okay. So at some moment, potentially, you say, "This is a rule, and run this rule enough times, and you will get the whole universe." Right? That's, that's what it means to kind of have a fundamental theory of physics, as far as I'm concerned, is you've got this rule, it's potentially quite simple. We don't know for sure it's simple, but we have various reasons to believe it might be simple. And then you say, "Okay, I'm showing you this rule. You just run it only 10 to the 500 times-"

    7. LF

      Mm-hmm.

    8. SW

      "... and you'll get everything." In other words, you've, you've kind of reduced the problem of physics to a problem of mathematics, so to speak. It's like... it's as if, you know, you'd like... you generate the digits of pi. There's a definite procedure. You just generate them. And it'd be the same thing. If you have a fundamental theory of physics of the kind that, that I'm imagining, you, you know, you get a... this rule and you just run it out and you get everything that happens in the universe.

    9. LF

      So, a theory of everything is a mathematical framework within which you can explain everything that happens in the universe kind of in a unified way. It's not there's a bunch of disparate modules of-

    10. SW

      Right.

    11. LF

      Does it feel like if you create a rule, and we'll talk about the Wolfram Physics model, which is fascinating, but if- if you, if you- f- have a simple set of rules with a, with a data structure, like a hypergraph, does that feel like a satisfying Theory of Everything? Because then you really run up against the, uh, irreducibility, computational irreducibility.

    12. SW

      Right. So that's a really interesting question. So I- I- I, you know, what I thought was gonna happen is I thought we, you know, I thought we had a pretty good, I had a pretty good idea for what the structure of this sort of theory that's sort of underneath space and time and so on might be like. And I thought, "Gosh, you know, in my lifetime, so to speak, we might be able to figure out what happens in the first 10 to the minus 100 seconds of the universe."

    13. LF

      Mm-hmm.

    14. SW

      And that would be cool, but it's pretty far away from anything that we can see today and it will be hard to test whether that's right and so on and so on and so on. To my huge surprise, although it should've been obvious, and it's embarrassing that it wasn't obvious to me, but- but, um, to my huge surprise, we managed to get unbelievably much further than that. And basically what happened is that it turns out that even though there's this kind of bed of computational irreducibility that sort of, uh, these, all these simple rules run into, there is a, there are certain pieces of computational reducibility that quite generically occur for large classes of these rules. And, and this is the really exciting thing as far as I'm concerned, the- the- the big pieces of computational reducibility are basically the pillars of 20th century physics. That's the amazing thing, that general relativity and quantum field theory are sort of the pillars of 20th century physics turn out to be precisely the stuff you can say. There's a lot you can't say, there's a lot that's kind of at this irreducible level where you kinda don't know what's going to happen, you have to run it, you know, you can't run it within our universe, et cetera, et cetera, et cetera, et cetera, et cetera. Um, but the thing is, there are things you can say and the things you can say turn out to be very beautifully th- exactly the structure that was found in 20th century physics, namely general relativity and quantum mechanics.

    15. LF

      And g- general relativity and quantum mechanics are these pockets of reducibility that we think of as the, that, you know, 20th century physics is essentially pockets of reducibility. And then it's, it is incredibly surprising that any kind of model that's generative from simple rules would have, would have such pockets.

    16. SW

      Yeah, well, I think what, what's surprising, uh, is we didn't know where those things came from. It's like general relativity, it's a very nice mathematically elegant theory. Why is it true? You know, quantum mechanics, why is it true? What we realized is that from this, that they are, these theories are generic to a huge class of systems that have these particular very unstructured underlying rules. And that's the, that's the thing that is sort of, uh, remarkable, and that's the thing to me that's just, it's really beautiful. I mean, it's-

    17. LF

      It is. True.

    18. SW

      And the thing that's even more beautiful is that it turns out that, you know, people have been struggling for a long time, you know, how does general relativity, theory of gravity relate to quantum mechanics? They seem to have all kinds of incompatibilities. It turns out what we realized is at some level they are the same theory. And that's just, it's- it's just great as far as I'm concerned.

  9. 52:411:01:16

    General relativity

    1. SW

    2. LF

      (laughs) So-

    3. SW

      Yeah.

    4. LF

      ... maybe, like taking a little step back from your perspective, not from the low, not from the beautiful hypergraph Wolfram Physics model perspective, but from the perspective of 20th century physics, what is general relativity? Wha- what is quantum mechanics? How do you think about these two theories from the context of the Theory of Everything? Like just even definitions.

    5. SW

      Yeah, yeah, yeah, right. So, so I mean, you know, a little bit of history of physics, right?

    6. LF

      Yeah.

    7. SW

      So, so I mean, the- the, you know... Okay, very, very quick history of physics.

    8. LF

      Yes (laughs) .

    9. SW

      Right? So, so I mean, you know, physics, you know, in ancient Greek times, people basically said, "We can just figure out how the world works. As, you know, we're philosophers, we're gonna figure out how the world works." You know, some philosophers thought there were atoms, some philosophers thought there were, you know, continuous flows of things. People had different ideas about how the world works. And they tried to just say, "We're gonna construct this idea of how- how the world works." They didn't really have sort of notions of doing experiments and so on quite the same way as developed later. So that was sort of an early tradition for thinking about sort of models of the world. Then by the time of 1600s, time of Galileo and then Newton, um, sort of the big, the big idea there was, you know, you know, title of Newton's book, you know, Principia Mathematica, Mathematical Principles of Natural Philosophy. We can use mathematics to understand natural philosophy, to understand things about the way the world works. And so that then led to this kind of idea that, you know, we can write down a mathematical equation and have that represent how the world works. So Newton's, one of his most famous ones is his universal law of gravity, inverse square law of gravity that allowed him to compute all sorts of features of- of the planets and so on. Although some of them he got wrong and it was, took another a hundred years for people to actually be able to do the math, uh, to the level it was needed. But, but, um, but so that, that had been this sort of tradition was we write down these mathematical equations, we don't really know where these equations come from. We write them down, then we figure out, we work out their consequences and we say, "Yes, that agrees with what we actually observe in astronomy or something like this." So that tradition continued and, um, then the first of these two sort of great 20th century, uh, innovations was, uh, well, the history is actually a little bit more complicated, but let's- let's say-

    10. LF

      (laughs) Yeah.

    11. SW

      ... that the- the, um, the- the- the- the, there were two, quantum mechanics and general relativity. Quantum mechanics had kind of, 1900 was kind of the very early, uh, stuff done by Planck that led to the idea of photons, particles of light. Um, but let's, let's take general relativity first. One, one feature of this story is that special relativity, thing Einstein invented in 1905-... was something which, surprisingly, was a kind of logically invented theory. It was not a theory where... it was something where given these ideas that were sort of axiomatically thought to be true about the world, it followed that such and such a thing would be the case. And it was a little bit different from the, the kind of methodological structure of some, of some existing theories in more, in the more recent times, where it had just been, we write down an equation and we find out that it works. So what happened there-

    12. LF

      So there's some reasoning about the light.

    13. SW

      The basic idea was the, you know, the speed of light is, appears to be constant. Uh, you know, even if you're traveling very fast, you shine a flashlight, the light will come out, e- even if you're going at half the speed of light, the light doesn't come out of your flashlight at one and a half times the speed of light. Um, it's still just the speed of light. And to make that work, you have to change your view of how space and time work, um, to be able to account for the fact that when you're going faster, it appears that, you know, uh, length is foreshortened and time is dilated and things like this.

    14. LF

      And that's special relativity.

    15. SW

      That's special relativity. So then Einstein went on with sort of, uh, vaguely similar kinds of thinking. In 1915, invented general relativity, which is a theory of gravity. And the basic point of general relativity is, is it's a theory that says when there is mass in space, space is curved.

    16. LF

      Mm-hmm.

    17. SW

      And what does that mean? You know, you, y- y- usually you think of, uh, what's the shortest distance between two points? Like in a, uh, ordinarily in, on a plane in space, it's a straight line. You know, photons, light goes in straight lines. Well, then the question is, is, uh, if, if you have a curved surface, a straight line is no longer straight. On the surface of the earth, the shortest distance between two points is a great circle. It's a circle. Um, it's, uh, so, you know, Einstein's observation was maybe the physical, uh, structure of space is such that space is curved. So the shortest distance between two points, the, the path, the "straight line" in quotes, won't be straight anymore. And in particular, if a, if a photon is, is, you know, traveling near, near the sun or something, or if a particle is going, something is traveling near the sun, maybe the shortest path will be one that is, is, uh, is, is something which looks curved to us because... it seems curved to us because space has been deformed by the presence of mass associated with that, that, uh, massive object. So, so the, kind of the idea, uh, there is, um, think of th- the structure of space as being a dynamical changing kind of thing. But then what Einstein did was he wrote down these differential equations that basically represented the curvature of space and its response to the presence of mass and energy.

    18. LF

      And that u- ultimately, it's connected to the force of gravity, which is one of the forces that s- seems to, based on its strength, operate on a different scale than some of the other forces. So it operates at a scale-

    19. SW

      Yeah.

    20. LF

      ... that's very large.

    21. SW

      What happens there is, is just this, this curvature of space which causes, you know, the paths of objects to be deflected, that's what gravity does. It causes the paths of objects to be deflected. And this is a, an explanation for gravity, so to speak. And the surprise is that from 1915 until today, everything that we measured about gravity precisely agrees with general relativity. And that's, um... uh, and that, you know, it wasn't clear black holes were sort of a predi- well, actually, the expansion of the universe was an early potential prediction. Although Einstein tried to sort of patch up his equations to make it not cause the universe to expand, 'cause it was kind of so obvious the universe wasn't expanding. And, um, uh, you know, it turns out it was expanding and he should have just trusted the equations. And that's a lesson for, for those of us, um, interested in making fundamental theories of physics is, you should trust your theory and not try and patch it because of something that you think might be the case that, um, uh, that, that might turn out not to be the case.

    22. LF

      E- even if the theory says something crazy is happening?

    23. SW

      Yeah, right.

    24. LF

      Like the universe is expanding.

    25. SW

      Like, like the universe is expanding, right? Which is... but, but, um, but, you know, then it took until the 1940s, probably even really until the 1960s until people understood that black holes were a consequence of, of general relativity and so on. But that's, um... you know, the big surprise has been that so far, this theory of gravity has perfectly agreed with, you know, these collisions of black holes seen by their gravitational waves. You know, it all just works. So that's been kind of one pillar of the story of physics. It's mathematically complicated to work out the consequences of general relativity, but it's not... there's n- there's no... I mean, and, and, and, and some things are kind of squiggly and complicated. Like people believe, you know, energy is conserved. Okay, well, energy conservation doesn't really work in general relativity in the same way as it ordinarily does, and it's all a big mathematical story of how you actually nail down something that is definitive that you can talk about and not specific to the, you know, reference frames you're operating in, and so on, and so on, and so on. But fundamentally, general relativity is a straight shot in the sense that you have this theory, you work out its consequences. Um-

    26. LF

      And, and that, that theory is useful in terms of basic science and trying to understand the way black holes work, the way the creation of galaxies work, sort of all these kind of cosmological thing. Understanding what happened, like you said, at the Big Bang-

    27. SW

      Yeah.

    28. LF

      ... like all those kinds of... well, no, not, not at the Big Bang actually, right? But, uh...

    29. SW

      Well, features of the expansion of the universe, yes.

    30. LF

      Features of the expansion-

  10. 1:01:161:06:46

    Quantum mechanics

    1. SW

      some sense.

    2. LF

      Okay. So that's general relativity. And what's-

    3. SW

      Okay.

    4. LF

      ... its friendly neighbor? Like you said-

    5. SW

      Quantum mechanics.

    6. LF

      ... there's two theories, quantum mechanics.

    7. SW

      Right. So quantum mechanics, the, the, the sort of, the way that that originated was one question was, is the world continuous or is it discrete? You know, in ancient Greek times, people have been debating this. People debated it in, you know, throughout history. "Is light con- made of waves? Is it continuous? Is it discrete? Is it made of particles, corpuscles," whatever. Um, you know, what had become clear in the 1800s is that atoms that, you know, materials are made of discrete atoms. You know, when you take some water, the water is not a continuous fluid, even though it seems like a continuous fluid to us at our scale. But if you say, "Let's look at it smaller and smaller and smaller and smaller scale," eventually you get down to these, you know, these molecules and then atoms. It's made of discrete things. So the question is sort of how important is this discreteness? Just what's discrete, what's not discrete? Is energy discrete? Is, you know, is, wha- what's discrete, what's not? And so-

    8. LF

      Does it have mass? Those kinds of questions.

    9. SW

      Yeah, yeah, right. Well, well th- th- there's question, I mean, for example, is mass discrete is an interesting question, which is now something we can address. But, but, um, you know, what, what happened in, um, uh, the, in, in the, uh, coming up to the 1920s, there was this kind of mathematical theory developed that could explain certain kinds of discreteness in, in particularly in, in features of atoms and so on. And, uh, you know, what developed was this mathematical theory that was a theory, the theory of quantum mechanics, theory of wave functions, Schrodinger's equation, things like this. That's a mathematical theory that allows you to calculate lots of features of the microscopic world, lots of things about how atoms work, et cetera, et cetera, et cetera. Now, the calculations all work just great. The, um, uh, the question of what does it really mean is a complicated question. Now, I mean, to, to just explain a little bit historically, the, you know, the early calculations of things like atoms worked great in 1920s, 1930s, and so on. There was always a problem. There were, uh, in quantum field theory, which is a theory of, uh, uh... In quantum mechanics, you're dealing with a certain number of atom, a certain number of electrons, and you fix the number of electrons. You say, "I'm dealing with a two electron thing." Um, in quantum field theory, you s- allow for particles being created and destroyed. So you can emit a photon that didn't exist before. You can absorb a photon, things like that. That's a more complicated, mathematically complicated theory, and it had all kinds of mathematical issues and all kinds of infinities that cropped up, and it was finally figured out more or less how to get rid of those. But there were only certain ways of doing the calculations, and those didn't work for atomic nuclei among other things. Um, and that led to, oh, a lot of developments up until the 1960s of alternative ideas for how, how one could understand what was happening in atomic nuclei, et cetera, et cetera, et cetera. End result, in the end, the kind of most, quote, "obvious" mathematical structure of quantum field theory seems to work, although it's mathematically difficult to deal with. But you can calculate all kinds of things. You can calculate to, you know, a dozen decimal places certain, certain things. You can measure them. It all works. It's all beautiful. Now you say-

    10. LF

      By the way, the underlying fabric is the model of that particular theory is fields. Like you keep saying fields is-

    11. SW

      Uh, tho- those are quantum fields. Those are different from classical fields. A, a field is something like you say, um, there's, like you say, the temperature field in this room. It's like there is a value of temperature at every point around the room. That's, um... Or, or you can say the wind field would be the, the vector direction of the wind at every point.

    12. LF

      It's continuous, a field.

    13. SW

      Yes. And it's a, that's a classical field. The quantum field is a much more mathematically elaborate kind of thing. Um, and I should explain that, that one of the pictures of quantum mechanics that's really important is, you know, in classical physics, one believes that sort of definite things happen in the world. You pick up a ball, you throw it, the ball goes in a definite trajectory that's the, where it has certain equations of motion, it goes in a parabola, whatever else. In quantum mechanics, the picture is definite things don't happen. Instead, sort of what happens is this whole sort of structure of, of all, you know, many different paths being followed, and, um, we can calculate certain aspects of what happens, certain probabilities of different outcomes and so on. And you say, "Well, what really happened? What's really going on? What's the sort of, uh, what's the underlying, you know, what's the underlying story? What, how do we, how do we turn this, this mathematical theory that we can calculate things with into something that we can really understand and have a narrative about?" And that's been really, really hard for quantum mechanics. Uh, my, my friend Dick Feynman always used to say, "Nobody understands quantum mechanics," even though he'd made his, you know, whole career out of calculating things about quantum mechanics. Um, and, uh, you know, so, so it's a little-

    14. LF

      But nevertheless, it's, uh, what the quantum field theory is very, uh, very accurate at predicting a lot of the physical phenomena. So it works.

    15. SW

      Yeah. And, but there are things about it, you know, it has certain... When we apply it, the standard model of particle physics, for example, we, uh, you know, which we apply to calculate all kinds of things, it works really well. And you say, "Well, it has certain parameters." It has a whole bunch of parameters actually. You say, "Why is the, you know, why does the muon particle exist? Why is it 206 times the mass of the electron?" We don't know. No

  11. 1:06:461:12:01

    Unifying the laws of physics

    1. SW

      idea.

    2. LF

      But, so the standard model of physics is, is, is one of the models that's very accurate for describing three, three of the fundamental forces of physics, and it's looking at the, the world of the very small.

    3. SW

      Right.

    4. LF

      And then there's back to the neighbor of, uh, gravity, of general relativity. So, and then in the context of a theory of everything, what's traditionally the task of the unification of these theories? And why is it hard?

    5. SW

      Well, I mean, the, the issue is you try to use the methods of quantum field theory to talk about gravity and it doesn't work.... just like there are photons of light, so there are gravitons which are sort of the particles of gravity. And when you try and compute sort of the properties of the, of the particles of gravity, the kind of mathematical tricks that get used, um, in working things out in quantum field theory don't work. And, um, that's, um ... so that's been a sort of fundamental issue. And when you think about black holes which are a place where, uh, sort of the, the structure of space is, um, uh, you know, has, has sort of rapid variation and you get kind of quantum effects mixed in with effects from general activity, things get very complicated and there are par- paradoxes and things like that. And people have, you know, there've been a bunch of mathematical developments in, in physics over the last, I don't know, 30 years or so which have kind of picked away at those kinds of issues, and got hints about how things might work. Um, and but it hasn't been, uh, uh ... you know, and the other thing to realize is, as far as physics is concerned, it's just like, here's general activity, here's quantum field theory, you know, be happy.

    6. LF

      Yeah. So do you think there's a quantization of gravity, quantum gravity th- ... what, what do you think of efforts that people have tried to ... yeah, what do you think in general of the efforts of the physics community to try to unify these laws?

    7. SW

      So I think what's ... it's interesting. I mean, I would've said something very different before what's happened with our physics project. Um, I mean, you know, the remarkable thing is, what we've been able to do is to make from this very simple, structurally simple underlying set of ideas, we've been able to build this, this, you know, very elaborate structure that's both very abstract and very sort of mathematically rich. And the big surprise as far as I'm concerned is that it touches many of the ideas that people have had. So in other words, things like-

    8. LF

      Mm-hmm. That's-

    9. SW

      ... string theory and so on, uh, twistor theory. It's like the ... you know, w- we might have thought, I had thought, we're out on a prong. We're building something that's computational-

    10. LF

      Right.

    11. SW

      ... it's completely different from what other people have done. But actually, it seems like what we've done is to provide essentially the machine code that, you know, these things are, are various features of domain-specific languages so to speak, that talk about various aspects of this machine code, and I think there's a ... this is something that to me is, is, is very exciting because it allows one both for us to provide sort of a new foundation for what's been thought about there, and for the, all the work that's been done in those areas to, you know, to give us, you know, more, more momentum to be able to figure out what's going on. Now, you know, people have sort of hoped, oh, we're just gonna be able to get, you know, string theory to just answer everything. That hasn't worked out, and I think we now kind of can see a little bit about just sort of how far away certain kinds of things are from being able to explain things. Some things ... one of the big surprises to me actually, I literally just got a message about one aspect of this, is, um, uh, the, uh, uh, you know, it's turning out to be easier. I mean, this project has been so much easier than I could ever imagine it would be. That is, I thought we would be, you know, just about able to understand the first 10-100 seconds of the universe, and, um, you know, it would be 100 years before we get much further than that. It's just turned out, it actually wasn't that hard. I mean, we're not finished but, you know, w-

    12. LF

      So you're, you're, you're seeing echoes of all the disparate theories of physics in this framework of ...

    13. SW

      Yes. Yes. I mean, it's a very interesting, you know, sort of history of science like phenomenon. I mean, uh, the best analogy that I can see is what happened with the early, early days of, of computability and computation theory. You know, Turing machines were invented in 1936. People sort of understand computation in terms of Turing machines, but actually there had been preexisting theories of computation, combinators, general recursive functions, lambda calculus, things like this, but people hadn't ... those hadn't been concrete enough-

    14. LF

      Mm-hmm.

    15. SW

      ... that people could really wrap their arms around them and understand what was going on. And I think what we're gonna see in this case is that a bunch of these mathematical theories, um, including some very ... and one of the things that's really interesting is, one of the most abstract things that's come out of, of sort of, uh, mathematics, th- higher category theory, things about infinity groupoids, things like this-

    16. LF

      Mm.

    17. SW

      ... which to me always just seemed like they were floating off into the stratosphere, uh, uh, ionosphere of mathematics, um, turn out to be things which our sort of theory anchors down to something fairly definite, and says are super relevant to the way that we can understand how physics works.

    18. LF

      Give me a sec. By the way, I just threw a hat

  12. 1:12:011:29:53

    Wolfram Physics Project

    1. LF

      on. You've said that, um, this metaphor analogy that, uh, Theory of Everything is a big mountain, and you have a sense that however far we are up the mountain, that the f- the Wolfram Physics model view of the universe is at least the right mountain.

    2. SW

      We're the right mountain.

    3. LF

      (laughs)

    4. SW

      Yes. Without question. So I'm, I'm-

    5. LF

      So, which aspect of it is the right mountain? So for examp- ... I mean, so th- there's so many aspects to just the way of the Wolfram Physics Project, the way it approaches the world, that's, um, that's clean, crisp, uh, and, uh, unique, and powerful. So, you know, there's a, there's discreet nature to it, there's a hypergraph, there's a computational nature, the, uh, there's a generative aspect; you start from nothing, you generate everything. Which ... do you think the actual model is actually a really good one? Or do you think this general principle of from simplicity generating complexity is the right? Like, what aspect-

    6. SW

      Well, I think-

    7. LF

      ... of the mountain is the correct-

    8. SW

      Yeah, right. I mean, I, I think that the, the kind of the meta idea about using simple computational systems to do things, that's, you know, that's the ultimate big paradigm that is, you know-... sort of super important. The details of the particular model are very nice and clean and allow one to actually understand what's going on. They are not unique. And in fact, we know that. We know that there's a, a, there's a large number of different ways to describe essentially the same thing. I mean, I can describe things in terms of hypergraphs, I can describe them in terms of higher category theory. I can describe them in a bunch of different ways. They are, in some sense, all the same thing, but our sort of story about what's going on and, and the kind of, uh, kind of cultural mathematical resonances are a bit different.

    9. LF

      Yeah.

    10. SW

      I mean, I think it's, it's, it's perhaps worth sort of saying a little bit about kind of the, the, you know, foundational ideas of, of, uh, of, uh, uh, you know, of these- of these models and things.

    11. LF

      Great. So, can you maybe, uh, can we like rewind? We've talked about it a little bit, but can you say like what the central idea is of the Wolfram Physics Project?

    12. SW

      Right. So, so the question is, we're interested in finding a sort of simple computational rule that describes our whole universe. That-

    13. LF

      Can we just pause on that? It's just so beauti- uh, that- that's such a beautiful, that's such a beautiful idea.

    14. SW

      Yeah.

    15. LF

      That we can generate our universe from a sim- from a, uh, from a data structure, a simple s- structure, a simple set of rules, and we can generate our entire universe.

    16. SW

      Yes. That's the idea.

    17. LF

      That's awe-inspiring. (laughs)

    18. SW

      Right. Uh, but, but so, so, you know, the question is how do you actualize that? What might this rule be like? And so one thing you quickly realize is, if you're gonna pack everything about a universe into this tiny rule, not much that we are familiar with in our universe will be obvious in that rule. So, you don't get to fit all these parameters of the universe, all these features of, you know, this is how space works, this is how time works, et cetera, et cetera, et cetera. You don't get to fit that all in. It all has to be sort of packed in to this, this thing, something much smaller, much more basic, much lower level machine code, so to speak-

    19. LF

      Mm-hmm.

    20. SW

      ... than that. And all the stuff that we're familiar with has to kind of emerge from the operation of-

    21. LF

      So, the rule in itself, because of the computational reducibility is not gonna tell you the story. It's not gonna give you the-

    22. SW

      Right.

    23. LF

      ... answer to a... It's not gonna let you predict what you're gonna have for lunch tomorrow-

    24. SW

      Right.

    25. LF

      ... and it's not going to let you predict basically anything about your life, about the universe.

    26. SW

      Right. But, and you're not going to be able to see in that rule, oh, there's the three for the number of dimensions of space and so on.

    27. LF

      Right.

    28. SW

      That's not gonna be there.

    29. LF

      So space-time is not going to be obviously-

    30. SW

      Right. So, and the question is then, what-

Episode duration: 4:23:38

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