Stephen Wolfram — Productivity Systems, Richard Feynman Stories, Computational Thinking, and More

1. 0:00 – 0:13

   Start

   1. TFTim Ferriss0:00

      [upbeat music]

2. 0:13 – 1:59

   How Stephen collects information for his vast personal archives.

   1. TFTim Ferriss0:15

      Stephen, it's nice to see you. Thank you for making the time today.

   2. SWStephen Wolfram0:18

      Pleased to be here.

   3. TFTim Ferriss0:19

      And I was impressed that just before we started recording, when I fumbled an attempt to recall when it was that we sat next to each other, you very quickly said, "2011, Wired Health Conference," and mentioned that you have an archive. So how do you search for something like that?

   4. SWStephen Wolfram0:43

      I keep an awful lot of stuff. So I've, uh, I've got all my email going back 30 years.

   5. TFTim Ferriss0:48

      Mm-hmm.

   6. SWStephen Wolfram0:49

      I have a habit of writing kind of trip reports for myself whenever I go to some event or something like that.

   7. TFTim Ferriss0:55

      Mm-hmm.

   8. SWStephen Wolfram0:55

      And I have also scans of, uh, paper documents. You, you weren't a paper document. You're, you're more recent-

   9. TFTim Ferriss1:02

      [laughs]

   10. SWStephen Wolfram1:02

       ... than a paper document, so to speak. But I have scans of, well, it's like a quarter million pages or so of paper documents that-

   11. TFTim Ferriss1:08

       Wow

   12. SWStephen Wolfram1:08

       ... uh, I generated in the, in the time in my life before I went fully digital, so to speak. And I also tend to record. I record all the keystrokes I type, and screen captures, and all kinds of things like that.

   13. TFTim Ferriss1:20

       How do you use the logging of the keystrokes?

   14. SWStephen Wolfram1:25

       I don't usually.

   15. TFTim Ferriss1:26

       You do not. [laughs]

   16. SWStephen Wolfram1:27

       No, usually I don't. Occasionally I'll want to know, uh, you know, occasionally, for example, some computer will crash in some horrible way, and it'll be like, "Oh, I just lost a bunch of stuff. Well, no I didn't-'

   17. TFTim Ferriss1:37

       Ah

   18. SWStephen Wolfram1:37

       ... 'cause I have it recorded."

   19. TFTim Ferriss1:38

       Right.

   20. SWStephen Wolfram1:38

       And that was, that was the thing that caused me, like, 25 years ago, to start recording those. This one crash, and then I decided it, it's cheap to just record everything like that. And occasionally I'll do things like, oh, I'm using a new keyboard. You know, do I type faster or slower on my new keyboard?

   21. TFTim Ferriss1:53

       Got it.

   22. SWStephen Wolfram1:54

       You know, those kinds of things.

   23. TFTim Ferriss1:55

       And you can track that type of thing.

   24. SWStephen Wolfram1:57

       Easy to answer that question if you have that

3. 1:59 – 6:00

   When a situation warrants building a matrix.

   1. SWStephen Wolfram1:59

      data.

   2. TFTim Ferriss2:00

      So it's one thing to record or ingest information, it's quite another to structure your thinking. And I, in the process of doing research for this conversation, came across some discussion on Reddit involving creating matrices. So I wanted to explore your use of matrices for different projects, and I'm just gonna read a very, very short section here, which reads, "I actively avoid thinking about things where I don't have a matrix. I don't like to have disembodied ideas floating around," which is my current state of affairs, so I'm selfishly asking this.

   3. SWStephen Wolfram2:39

      [laughs]

   4. TFTim Ferriss2:39

      "Of course, when something's important enough to me, I try to build a matrix for it." Could you give an example of what such a matrix might look like?

   5. SWStephen Wolfram2:48

      What I mean by that is some kind of framework in which I'm doing something. So for example, if I have a small idea about molecular biology-

   6. TFTim Ferriss2:59

      Mm

   7. SWStephen Wolfram2:59

      ... I don't really have a good place to put that idea. If I'm doing a big project about molecular biology where I'm building up a whole structure, then I have to... a place to put that. So it's, it's that kind of thing. And, you know, I've been lucky enough, you know, the, the main, my, my main life work is building our computational language, Wolfram Language, which is this language that's supposed to represent sort of everything in the world computationally. So a large number of ideas that I have about how to represent things computationally can wind up in the matrix, which is the Wolfram Language. Similarly, I've found, you know, for example, writing, uh, my blog, like, kind of writings thing, that's another kind of matrix into which I can put... You know, when I do kind of historical studies of things, I'll write a piece about that historical study, and that's a place to put it. But, you know, when it's, when it's sort of too small a thing, I just don't have a place-

   8. TFTim Ferriss3:50

      Mm

   9. SWStephen Wolfram3:50

      ... to put it, and it tends to die on the vine. You know, I was... Since you're asking about this, I've, I've just been exposing myself to a very bizarre experience, which is-

   10. TFTim Ferriss4:00

       [laughs]

   11. SWStephen Wolfram4:00

       ... I've just been finishing a project that I started 50 years ago.

   12. TFTim Ferriss4:05

       Wow, okay.

   13. SWStephen Wolfram4:06

       And in the process of doing this... So I, I... Something that I started, I got interested when I was 12 years old. It's a question about physics and about the second law of thermodynamics and why sort of randomness gets generated in the world and so on. And I've made various pieces of progress on this question over the years. But finally now, with a bunch of the things that we've done recently in understanding the fundamental theory of physics, I think I can actually really nail this question. So I've, I've written a whole thing about kind of the, the scientific answer to that question. But then I thought I should write a piece kind of describing my 50-year journey of trying to answer this question. And so that got me back into, I'm looking at all my calendars from 1983 and, and, uh, I'm looking at all of these, uh, paper documents that I have scanned and so on. It's a very interesting experience, going back and seeing, you know, what mattered from 1983 and what didn't. How did I get to the things that were important in the end? How did those come to be? What were the, what were the kinds of steps that I had to go through? One of the things I really noticed, really striking to me, is there's often a large amount of time in which I was building some conceptual framework for something. Sometimes I had clues about how that framework should work. I didn't even recognize the clues, just didn't understand it. Finally, through this sort of very slow process, I build this intellectual framework, and then I get some other clue. I do some other computer experiment. Something else happens. And then literally I can trace, 'cause I have all the, you know, file creation dates, all this kind of thing. I can trace, you know, it was 15 minutes from the time when I saw this to the time when I started writing this and, and so on. And it, it's, it's really remarkable how much, you know, years can go by, but when sort of slowly building up the kind of conceptual framework needed, and then, then it's often very sudden to kind of take the next step. That was a, kind of a striking thing to me.

4. 6:00 – 11:22

   Science sometimes makes us look far back to move incrementally forward.

   1. TFTim Ferriss6:00

      So I wanna ask a few follow-up questions about- ... conceptual frameworks and perhaps just, uh, request an example of what such a conceptual framework might look like for people listening-

   2. SWStephen Wolfram6:10

      Mm-hmm

   3. TFTim Ferriss6:10

      ... and for me, frankly. But before we get to that, putting together a blog post or an article that chronicles your search for answers or exploration of these open questions is quite an undertaking. Reviewing calendars from 1983 and so on, I would imagine requires a good amount of time. Why do you do it? Or, or is it the reward in the process of writing? Is it, is it something gratifying in the process of writing? Are you hoping to impart something to those who read this piece? Why do that?

   4. SWStephen Wolfram6:42

      That's a good question. [laughs] I was wondering it myself. I thought it would be really easy, but it wasn't quite so easy.

   5. TFTim Ferriss6:46

      [laughs]

   6. SWStephen Wolfram6:47

      No, I have done quite a lot of kind of historical biography, usually of other people. I find it, you know, when I'm really trying to understand an idea, I need to know where that idea came from. So for example, the things I'm doing right now on the second law of thermodynamics thing. Second law of thermodynamics was developed in the 1860s. I think people took a wrong turn sometime shortly thereafter. So I think the thing that I've now figured out is a little different from what people had figured out at that time. And so when I'm saying I think they took a wrong turn, I really wanna know how did they come to take that wrong turn? And so that's my next project for the next week or so is, is going back, and I've collected the material for it. I c- get to go back and, and read all the original kind of sources of, of how people came to think about those things. But I don't feel confident that I know what was going on until I can kind of trace this person took that move because they thought this and they understood that and so on. And I thought for myself, I was mostly, well, a bit curious. I thought it was sort of an interesting story. It's a very rare case in kind of history of science where one actually has really precise detailed data on how some idea got developed. And so I thought, uh, it's kind of an interesting example of essentially computational history. You know, one thinks about computational X for all X, this is computational history. And it's kind of like what can you do in computational history? What kinds of things can you kind of expose in computational history? The other thing that's interesting to me is when I go back and think about things that I did or figured out, you know, 40 years ago, let's say, I sort of lived through it, but then when I look back, I realize there were threads that could be joined that I absolutely did not see at the time.

   7. TFTim Ferriss8:31

      Hm.

   8. SWStephen Wolfram8:32

      So, you know, give you an example. I was working on these, uh, simple programs, what do simple programs do. The big surprise was even very simple programs can do very complicated things. That was something I didn't expect. It was kind of a violation of my intuition. Took me a couple of years to kind of come to terms with the fact that that was possible. Same time, several of actually sort of top mathematicians who were sort of friends of mine were trying to work on sort of the things that I had uncovered. They said, "Let's go do math on these things. Let's figure out more stuff about them." And they worked for a while. I just found a bunch of their notes actually from going through these things from 1984 and so on. And they did a bunch of very sort of, uh, sophisticated math, and they couldn't figure out anything. And what I realized is, you know, at the time I was just like, okay, well, I'm figuring out my things. Their methods didn't happen to work, so what? What I then realized just now is the big innovation of mine was realizing that the fact that they couldn't figure out anything was itself a super interesting fact.

   9. TFTim Ferriss9:40

      Hm.

   10. SWStephen Wolfram9:40

       So in other words, there's this phenomenon I call computational irreducibility, which is basically kind of the big picture of why they couldn't figure out anyth- anything else. So, you know, usually you say, you say, "I know the rules by which some system operates." So then you might say, "Okay, great. I've got it nailed. I know everything about what's gonna happen in that system." Well, that's not true, because if the rules define some computation, it's, to know what the system does, you have to, you can find out by running the computation. The question is, can you outrun that computation? Can you say, "Okay, system, you went through a million steps of that computation, but I don't need to do that. I'm smarter than the system. I can just say the answer is 42 or something"? What computational irreducibility tells you is that in general, you are stuck kind of having to follow each step in the, in the evolution of the system. And that's a really important fact about science. It's kind of a way in which science explains from within science that science has questions that it can't readily answer.

   11. TFTim Ferriss10:44

       Hm.

   12. SWStephen Wolfram10:44

       And the thing that I realized only, you know, I don't know what, 35 years after the fact, is that in a sense, if I had an achievement, intellectual achievement in that whole process, it was realizing that the fact that one had gotten stuck was itself the most important thing to know. Not, oh, we got stuck, let's give up. But the fact that one got stuck meant that there was sort of a paradigmatic change that had to be made in the way that you think about these kinds of questions in science.

   13. TFTim Ferriss11:13

       Huh.

   14. SWStephen Wolfram11:13

       So that's an example that for me is, is quite useful to go back and, and see what really happened there, what was really important there, which I had not realized at the time.

5. 11:22 – 16:46

   Befriending the computational.

   1. TFTim Ferriss11:22

      Makes me think a bit of the, the Sherlock Holmes, the case of the dog that didn't bark in the night. [laughs] Uh, but the term that I'd love for you just to elaborate on a little bit, and I apologize, this is gonna be a muggle question. But for people who are non-technical, I'll put myself in that audience, when you say, for instance, computational history or computational X, how should someone who may have fear around the term computational think of that term, computational history as an example?

   2. SWStephen Wolfram11:53

      We humans like to sort of come up with abstract formal ways to describe things. Language itself is an example of that. You know, we, we see things out in, out there in the world and we say, "That's a tree, that's a dog, you know, that's whatever." The fact that we're able to sort of symbolically describe these things in the world, there are many different kinds of dogs and many different details, but we just say it's a dog. So it's a way of kind of organizing the things that we see, in that case, just using natural language. There have been in the, in, in sort of history a variety of kinds of organizational approaches. Logic, for example, was one from, you know, antiquity. Then mathematics is another kind of organizational approach to say, this is how you kind of structure the way that you talk about the world. As far as I'm concerned, the importance of computation is it's another way to structure how you talk about the world. And a big part of what I've spent my life doing is building this kind of computational language which provides sort of a precise way to take something like, I don't know, some description of some piece of food or some description of, uh, some position on the Earth or, or whatever else, and represent those things computationally in a sort of precise way that has the feature that, well, a human could read it and say, "Oh, I know what that means." But also, we have the extra sort of boost from the fact that a computer can read it, too, and then the computer can kind of help us to get further with that. So I mean, it, the, in a sense, you know, one of the big things that we as a species, you know, a big achievement is human language. You know, you can take sort of things about the world and describe them in a sort of somewhat precise, abstract way. I see computational language as being kind of another level in that evolution, except that we get to kind of share the burden of seeing what happens, not just with other humans, but with computers. And for me, that's kind of the, the big thing is, is describing the world computationally. Now, when I talk about, you know, simple programs and, and those kinds of things, what I tend to mean is kind of a meta model of the world. So there are models of actual trees and dogs and trajectories on the Earth and, and things like this. And then there are sort of, how do you break that down to something sort of even more primitive?

   3. TFTim Ferriss14:12

      Mm-hmm.

   4. SWStephen Wolfram14:12

      So then what you end up with are these sets of rules that say, well, you could describe what they are about in many different ways. But for example, one type that I've studied a lot, the technical name is cellular automata, and the typical sort of setup is you have a row of cells just... And each cell can be either black or white, let's say. And then the computational rule is you look at every cell and you say, what is the color of that cell and its two neighbors, let's say? Based on that, you say, "Okay, I'm gonna change the color of the cell to be, you know, white or to be black or whatever." You just keep running that rule over and over again. The big surprise is, and this is the thing I finally discovered in around 1984, the big surprise is that even with a rule that simple, you can just start it off with one black dot and it makes this incredibly complicated pattern.

   5. TFTim Ferriss15:06

      Mm.

   6. SWStephen Wolfram15:06

      A pattern so complicated that if you were to just look at, you know, a piece of the pattern and say, "Is this random or is there some, some regularity to it?" You would just say, "Looks completely random to me."

   7. TFTim Ferriss15:18

      Mm.

   8. SWStephen Wolfram15:18

      Even though the rule that made it is this very, very simple rule that you can easily describe or write down or, or feed to a computer or whatever else. So, so kind of for me, this notion of computation is kind of having this way to kind of structure the way that you talk about the world, and then there's this kind of meta modeling of that, which is to say, what are the very simplest elements of that computational process, and then talk about what, what one can do with those. I mean, I, I think a good analogy perhaps for, for sort of the computational description of the world is, comes from sort of the mathematical notation that one uses to talk about mathematics. I mean, it's sort of an interesting evolution that, that, um, if you look at mathematics done in antiquity and things like that, people didn't have a symbol for plus. They just used words. And then sometime around 500 years ago, people started inventing, you know, a plus sign, an equal sign, things like this. And it's when that sort of streamlining of the way to talk about math came online, that's where math really took off, and algebra got invented and then calculus, and then we have this whole sort of mathematical approach to science that was able to be done. And, you know, I, I guess my, my own sort of personal last 40 years of, of effort has been to sort of try to make a computational notation for talking about the world that is kind of a, a parallel for computation of what mathematical notation is for kind of the mathematical way of talking about the world.

6. 16:46 – 26:57

   How technology helps us navigate natural language.

   1. TFTim Ferriss16:46

      I have a question about natural languages, and, uh, I don't think I'm misquoting, but feel free to fact check this. You are so deeply aware of and able to work with language in, uh, in, in multiple, I would say, dimensions. I did read at one point you were considering a job with CERN, and I believe I read that you said you had practiced French but had never built up the nerve to use it, or something along those lines. And I don't know if that was a tongue in cheek comment. Uh-

   2. SWStephen Wolfram17:23

      No, no, that's from ancient times. But, you know, I went to fancy schools in England when I was growing up, and I, I learned three languages, Latin, Greek, and French.

   3. TFTim Ferriss17:32

      Mm-hmm.

   4. SWStephen Wolfram17:33

      Okay? You don't get to speak Latin or Greek, ancient Greek.

   5. TFTim Ferriss17:35

      [laughs] Right.

   6. SWStephen Wolfram17:36

      At least not in most places.

   7. TFTim Ferriss17:38

      [laughs]

   8. SWStephen Wolfram17:39

      But French you could, in principle, speak. And, you know, I can, I can read, like, scientific French pretty fluently.

   9. TFTim Ferriss17:44

      Mm-hmm.

   10. SWStephen Wolfram17:44

       But if you say, you know, if I'm in France and I'm like, "Can I order that piece of food or something?" I, I... No way. I can't do that.

   11. TFTim Ferriss17:52

       [laughs]

   12. SWStephen Wolfram17:53

       I'm, I'm... It's one of these things. I should get over it one day, 'cause I think I, you know, I have the vocabulary knowledge, I think, and all that. I just have never really gotten into that. You know, I've been very deeply involved in computational language.

   13. TFTim Ferriss18:04

       Mm-hmm.

   14. SWStephen Wolfram18:05

       I've not been deeply... I've been interested in human language, but I'm not From the point of view of sort of the, the practice of learning, learning lots of human languages. It's, it's one of those skills where I'm kind of, like, I could have put a lot of effort into it.

   15. TFTim Ferriss18:18

       Mm-hmm.

   16. SWStephen Wolfram18:18

       But it's like automatic translation is now getting to the point where, for many kinds of things, it's not so important anymore. Just like I could have been a champion map reader and, you know, I'm glad I didn't put huge effort into that because I just use a GPS now.

   17. TFTim Ferriss18:32

       Yeah, that's true. I suppose I am the opposite in the sense that I've spent a lot of time on natural languages, in part because I derive so much pleasure, and I think a sort of cognitive, uh, exercise from pursuing it. But looking at the progression, say, in Google Translate from my last trip to Japan, which was pre-COVID, to just about six weeks ago, it is astonishing how, how much it has improved. And, uh, you know, fortunately, I already s- speak, read, and write Japanese reasonably well because I went there as an exchange student when I was 15. But the extent to which someone can now use their voice pretty synchronously to communicate with someone with automatic translation is remarkable. Where do you see that, or how do you see that developing, say, in, in the next handful of years or in the near term? I mean, this is something I, I would imagine you probably have a view on. How do you think we'll be using this type of technology in the next, call it, five years?

   18. SWStephen Wolfram19:42

       You know, I think one of the things that it really kind of drills into is the kind of, the whole question of can you actually express the same thoughts in different human languages?

   19. TFTim Ferriss19:53

       Yeah.

   20. SWStephen Wolfram19:54

       And that's a, kind of a deep issue, and I think what we realize is that language is one kind of representation of kind of organized human thoughts.

   21. TFTim Ferriss20:04

       Mm-hmm.

   22. SWStephen Wolfram20:04

       And the, in a sense, it is a s- kind of societal construction of, you know, we all kinda know what a chair is, so when we use the word chair, we kind of know what each other is talking about.

   23. TFTim Ferriss20:17

       Yeah.

   24. SWStephen Wolfram20:17

       But if you have a language that comes from a place where the environment, the culture is very different, you'll end up with words where there really just, quotes, isn't a translation for that word.

   25. TFTim Ferriss20:28

       Yeah.

   26. SWStephen Wolfram20:28

       Because there just isn't the sort of shared cultural understanding of what one's talking about there. So I think the thing that will be pretty interesting to see is, you know, as we see kind of the tightening up of the kind of the structural aspects of translation, at what point do we really realize, you know, in that culture, there are thoughts that we just don't have in, in some other culture? And that's something, you know, as you, as you start generalizing that, it's kind of like, okay, how do we communicate with sort of the alien intelligences?

   27. TFTim Ferriss20:57

       Mm.

   28. SWStephen Wolfram20:58

       You know, how do you communicate with cats and dogs? How do you communicate with AIs?

   29. TFTim Ferriss21:01

       Mm.

   30. SWStephen Wolfram21:01

       Things like this. These are all kind of examples of, of alien intelligences with which we share certain kinds of things. You know, we share some emotional responses with pets and things like this.
7. 26:57 – 27:55

   How Stephen chose subjects for his book Idea Makers.

   1. TFTim Ferriss26:58

      let me ask you a question about the type of, mm, sort of scientific forensic analysis that you've done where you're looking at how someone took a left turn in, say, thermodynamics at some point in time. I have not read this book of yours, Idea Makers, it's a compilation of essays. How did you choose the players on the field for this? How did you choose the people you included?

   2. SWStephen Wolfram27:23

      Oh, it was always opportunistic. I'm afraid some of it was somebody died, and I knew them, and I wanted to write an obituary post.

   3. TFTim Ferriss27:31

      Hmm.

   4. SWStephen Wolfram27:32

      Others were somebody was having a big anniversary, and there was a big sort of shindig associated with that. So rather opportunistically. But it happened to cover a, a rather nice collection of different types of, types of folks from, you know, from Dick Feynman and Steve Jobs, who are both people I knew, to, uh, people like Ada Lovelace and Ramanujan, who are people who, you know, died long before

8. 27:55 – 30:26

   On spending time with Richard Feynman.

   1. SWStephen Wolfram27:55

      I was born.

   2. TFTim Ferriss27:56

      Dick Feynman. I'd love to, if you would indulge me, just to tell me a bit of your experience with Dick Feynman. So I own the set of Encyclopedia Britannica that he bought when he was, I think, 43 years old. I ended up buying it on my 43rd birthday as a reminder to never stop [laughs] searching and learning.

   3. SWStephen Wolfram28:18

      That's cool.

   4. TFTim Ferriss28:19

      And I, I do have a few diagrams of his as well, which I prize. And I wish I knew more physics. I, I really enjoyed it when I was younger. I did not pursue it to an advanced level at all. So I, I really wish I could appreciate his genius in a, in a higher fidelity way. But what was it like to spend time with him, and how did you know him? What was he like in person?

   5. SWStephen Wolfram28:43

      I met him when I was 18 and he was 60.

   6. TFTim Ferriss28:46

      Mm-hmm.

   7. SWStephen Wolfram28:47

      Okay?

   8. TFTim Ferriss28:47

      Yeah.

   9. SWStephen Wolfram28:47

      And he would always say, you know, "I was as quick as you were, but now I'm three times older than you are."

   10. TFTim Ferriss28:54

       [laughs]

   11. SWStephen Wolfram28:56

       So he could be quite competitive in those kinds of things. But, um, you know, the thing that I liked about him, like whenever I see it, is he just would think about anything. It's like, you know, the thinking apparatus is engaged and will stay engaged whatever the topic, so to speak.

   12. TFTim Ferriss29:16

       Hmm.

   13. SWStephen Wolfram29:17

       And he liked kind of drilling down to really get what is the real point, what's the, what's the essence of what's going on. And, you know, sometimes he would play a little trick on the world, which was one of the things he was really good at was calculating things by hand. He used computers a little bit, but, uh, mostly hand calculation, complicated math, these kinds of things. And so he would do... You know, you have some question, he would do all this complicated math to work out the answer. Then he would get this answer, and then he would think, "Well, how can I have figured out that answer by just some intuitive argument without having to go through all the complicated math?" I think he thought, I remember talking to him about this, he thought that, you know, everybody can do the complicated math, but it's really impressive if you can figure this out by intuition.

   14. TFTim Ferriss30:04

       [laughs]

   15. SWStephen Wolfram30:04

       And so he would then figure out this intuitive answer, throw away the math, tell people only the intuition. And so people were... You know, there's some fields where, where he did that, and people are like, "We don't know how on earth he figured this out." And, you know, people have been trying to reverse engineer the math for years.

   16. TFTim Ferriss30:22

       [laughs]

   17. SWStephen Wolfram30:23

       But that was, that was one of his little sort of tricks on the world,

9. 30:26 – 32:59

   Thoughts on Srinivasa Ramanujan.

   1. SWStephen Wolfram30:26

      so to speak.

   2. TFTim Ferriss30:27

      That's incredible intellectual sleight of hand. Would Ramanujan, this is, like, someone I know even less about, personify the intuition that Feynman was referring to on some level? Or would the-

   3. SWStephen Wolfram30:45

      Well, Ramanujan is a different kind of story. So R- Ramanujan was a kind of, um, slightly, you know, decently educated kind of person just hanging out in India and producing remarkable mathematical results. Ramanujan, like Feynman, was a very good calculator, and it really confused the mathematicians because he would say, "I've got this amazing formula for pi. Nobody's ever seen anything like it." And he'd say, "Here it is." And, and then when he started corresponding with mathematicians in England in 1913 or whatever, they were like, "Well, how did you prove this? How do you know this?" And eventually he got so fed up, I think, that he told them, "Well, the, the goddess so-and-so told it to me in a dream."

   4. TFTim Ferriss31:27

      [laughs]

   5. SWStephen Wolfram31:28

      Okay? But the truth of it was he was a really good calculator, and so he just worked out, you know, this particular series is the same as pi to this number of decimal places, and he had good enough mathematical intuition to say, "And it's just gonna be correct. It's not just gonna be an approximation. It's going to be exactly right." Occasionally, that intuition failed him. He had a, a result about prime numbers, for example, where he had done many, many, many cases, and it looked like it was true. Turns out the result isn't true, but the first exception is at 10 to the 10 to the 100 or something, you know, some huge place which, which he couldn't reach with calculation. So in a sense, he was, he was kind of, I think, a, a great experimental mathematician. Had he used computers, he would have, you know, had a whole different set of things he could have discovered. But even with himself as the computer, so to speak, he was discovering all kinds of things. And literally, the mathematicians of the time had never seen anything like it. And so for them, it just seemed to be this kind of magical thing where he was just pulling formulas from nothing. A bit like Dick Feynman, he was often pulling formulas from a lot of hard work of computation. And, you know, I, I remember when, when I was younger, I happened to start using computers to do physics sort of very early on when I was a, a teenager and so on. And for some reason, you know, the tools existed, but to be able to do some mathematical computations by computer, but people weren't using them.

10. 32:59 – 35:07

    When Stephen started solving science problems with computers.

    1. SWStephen Wolfram32:59

       One of the experiences that I had when I was kind of a kid was I kind of discovered the fact that computers can be really powerful for doing science and so on when I was kind of 13, 14, 15 years old. And I started using them to do that, and I started being able to derive all kinds of complicated mathematical formulas and so on by computer. For whatever crazy reason, other people just weren't doing that. And so I could write physics papers where I would have these very elaborate formulas that I'd derived and so on, and people were like, "You must be amazingly good at doing all this calculational stuff." And it's like, "Well, no, actually. [laughs] I'm actually pretty bad at it. But, you know, me with a computer, we're pretty good."

    2. TFTim Ferriss33:46

       [laughs]

    3. SWStephen Wolfram33:47

       But they didn't really even understand the fact that that was a thing back in those days. So yeah, I've, I've seen this kind of interesting phenomenon when you use tools that, you know, where you don't necessarily, where people don't necessarily even understand that those tools exist.

    4. TFTim Ferriss34:02

       Yeah.

    5. SWStephen Wolfram34:02

       It's kind of has some interesting consequences.

    6. TFTim Ferriss34:05

       The attribution I'm gonna skip, but what was it? Any sufficiently advanced form of technology is indistinguishable from magic. Something like that. I can't remember the attribution.

    7. SWStephen Wolfram34:12

       Yeah, I think it may be an Arthur C. Clarke.

    8. TFTim Ferriss34:14

       Yeah, think that sounds like Arthur C. Clarke.

    9. SWStephen Wolfram34:17

       I've spent a lot of my kind of scientific effort getting intuition from doing computer experiments.

    10. TFTim Ferriss34:26

        Mm-hmm.

    11. SWStephen Wolfram34:26

        And, you know, in another age, I would've been there with test tubes and other things doing physical experiments. Thank goodness I can get away with doing computer experiments 'cause it's a lot better for me, so to speak.

    12. TFTim Ferriss34:38

        [laughs]

    13. SWStephen Wolfram34:38

        But, uh, you know, you do these experiments, and there's a certain art to doing a good computer experiment. But you can discover things that you never thought were there, and they kind of inform your intuition and allow you to build things up. And it's kind of like this thing that comes from nowhere, 'cause it's just coming from, from not the natural world, but kind of the computational world. You're just, you know, turning over this rock in the computational world, and suddenly you discover that there's this whole, whole crazy thing going on underneath

11. 35:07 – 43:30

    Heresies today, gospels tomorrow.

    1. SWStephen Wolfram35:07

       it, so to speak.

    2. TFTim Ferriss35:08

       I would love to pose a question that was posed at a group dinner I attended not too long ago, and it's related to what the moderator called heresies. And the heresy in this context was something that the people in this small group, about six to eight people, would disagree with you about. And these were a lot of technical folks, and, uh, I think each person in the group could have put out many things they believed that the broader population would disagree with them about. But are there any particular beliefs that you have, or scientific insights, computational insights, this could be related to the physics project, could be related to other things, things you believe that you have high conviction in that many people would disagree with you on now, but let's just say hopefully 10 years from now, looking back, they would say, "Ah, yes, that was actually, in fact, had some grounds to it"? Does anything come to mind?

    3. SWStephen Wolfram36:07

       I mean, there's several, but there's one example of a big one, but this one is kind of the, the resistance is crumbling rapidly.

    4. TFTim Ferriss36:17

       Mm-hmm.

    5. SWStephen Wolfram36:18

       So maybe it doesn't, it doesn't quite count as well, but I think it would still be the case that, uh, if you poll Let's say physicists, the resistance would s- not have completely crumbled. So-

    6. TFTim Ferriss36:30

       Mm-hmm

    7. SWStephen Wolfram36:31

       ... and that- that's the question of, what is space?

    8. TFTim Ferriss36:33

       Mm.

    9. SWStephen Wolfram36:34

       And is space made of anything? So go back, let's say, 120 years.

    10. TFTim Ferriss36:41

        Mm-hmm.

    11. SWStephen Wolfram36:42

        People said, "What's water made of?" Water isn't made of anything. Water is just a fluid that flows in the way it flows. Turns out, what became clear in the late 19th century is actually water is made of something. People had guessed it much earlier. It's made of molecules. So the question now is, what is space made of? This, this thing that we kind of move around in, is it just a, a thing where we get to place something wherever we want, or does it have an inner structure?

    12. TFTim Ferriss37:12

        Mm-hmm.

    13. SWStephen Wolfram37:13

        And I've been pretty sure for quite a while that space has kind of an inner structure. It's just made of these discrete sort of, uh, atoms of existence, kind of, you can think of in the case of space, atoms of space. And all that one can say is how these atoms of space are connected to other ones. So there's this kind of giant network that defines the structure of space, and that's what space ultimately is. And everything that exists in the universe is a feature of the way those connections work in the underlying structure of space.

    14. TFTim Ferriss37:44

        Mm.

    15. SWStephen Wolfram37:44

        That's kind of like if you have a, a fluid, there's a bunch of these molecules bouncing around. But let's say you just look at a little vortex, a little eddy on the surface of the fluid, little whirlpool-type thing.

    16. TFTim Ferriss37:55

        Mm-hmm.

    17. SWStephen Wolfram37:55

        There is a... We can say, "There's a whirlpool. You can see it go by," and we can talk about it and so on. But ultimately, it's just made of a bunch of molecules moving in a particular organized kind of fashion. And it's my strong belief that sort of everything we know in the universe, all the electrons and photons and the things we, that get made up of those, they're all just sort of things like eddies in the structure of this giant network that is the sort of underlying data structure of the universe-

    18. TFTim Ferriss38:24

        Mm

    19. SWStephen Wolfram38:24

        ... uh, and the underlying thing that space is made of.

    20. TFTim Ferriss38:27

        Where would dark matter fit into this, be vetoed by this, be compatible or incompatible?

    21. SWStephen Wolfram38:33

        It's kind of a detail.

    22. TFTim Ferriss38:34

        Yeah.

    23. SWStephen Wolfram38:36

        The bigger picture is something which is a, a more embarrassing feature of current physics.

    24. TFTim Ferriss38:43

        Mm.

    25. SWStephen Wolfram38:43

        So, you know, dark matter is, the rotations of galaxies look like there's more stuff inside the galaxy than you can account for by looking at the luminous stars and so on. But there's a bigger embarrassment, which is that in quantum field theory, the kind of standard theory of the way sort of small-scale stuff happens in physics, there is this phenomenon called zero-point fluctuations, and they're an infinite collection of zero-point fluctuations in the universe that are associated with energy that has a gravitational effect that would roll the universe up into a tiny ball. You know, that is not what we see. We see a universe that's a big universe, not a universe that's just rolled up into a tiny ball. And so that's kind of the, in terms of sort of missing energy, that is a much bigger, by a factor of, uh, 100 orders of magnitude or more, that's a bigger problem, so to speak, than the dark matter problem. These are all kind of features of, there's aspects of the universe where there's energy, but where the energy doesn't seem to have the effect that we would expect to have, or we don't know where the energy is coming from, and so on. One feature of, of our sort of model of physics is that the, the very processes that are leading to those vacuum fluctuations and so on, those are the processes that knit together the structure of space.

    26. TFTim Ferriss40:04

        Mm.

    27. SWStephen Wolfram40:04

        So in the usual theory, it's like there's space, and that's a thing, and then there's all this matter that is doing all these weird quantum fluctuations in space, and that matter should have more of an effect on space. But in our models, those sort of quantum fluctuation-like things, those are what make space.

    28. TFTim Ferriss40:22

        Mm-hmm. Right.

    29. SWStephen Wolfram40:22

        And so it's kind of not surprising, and the math works out this way, that the thing that makes space doesn't itself have the effect on space of doing something like curling the universe up into a tiny ball. So that's a, that's an example of how something like that works out in, in our kind of model of physics.

    30. TFTim Ferriss40:40

        I do have a question about time, which I'll get to in a second, but any other heresies that would be on the shortlist of things that come to mind?
12. 43:30 – 58:24

    Ruminations on the ruliad.

    1. SWStephen Wolfram43:30

       be that way. What has become clear from our physics project is that all three of these theories sort of come from the same place, and they're all as derivable as each other, and they're all derivable in a, a really interesting way. They're all derivable ultimately from this strange thing we call the ruliad, which is this limit of all possible computations, the kind of entangled limit of all possible computations. And what turns out to happen is all three of those theories are the result of observers like us sampling this ruliad object. And what matters is that, uh, that we have certain attributes as observers. For example, we are computationally bounded. We can only fit a limited amount of sort of computational stuff into our minds. We can't describe, "Oh, here's where every atom in the universe went." In our minds, the narrative that we have for describing the universe is far away from, "Let's describe where every atom went." We're just talking about these much more sort of, uh, uh, filtered versions of what's going on in the universe. That, that turns out to be one of the important things. The other one is that we believe we are persistent in time. So in other words, even though at every moment we are made from different atoms of space, we are being, the atoms of space that we were at one moment are being destroyed, new ones are being created, and so on. Despite that, we believe that we are persistent in time. It's kind of like the little eddy on the water. The molecules that make that eddy, it's different molecules at every moment in time, yet there is a definite thing which, if the eddy was, had a mind, so to speak, it could think it is persistent in time. So tho- those two features that our minds are computationally bounded and we believe we are persistent in time, those two features determine kind of how we sample this ruliad thing, which is kind of the ultimate limit of all possible processes, and the sampling that we get to do is one that gives us those three features, those three big theories of 20th century physics.

    2. TFTim Ferriss45:34

       How do you spell ruliad?

    3. SWStephen Wolfram45:36

       R-U-L-I-A-D.

    4. TFTim Ferriss45:39

       Oh, I got it. Look at that. Incredible. Now, it's, is there a lay explanation or ex- exploration of the ruliad that isn't completely corrupted, that one like myself might digest?

    5. SWStephen Wolfram45:53

       The first thing to think about is, is a little bit of a story that gets to it.

    6. TFTim Ferriss45:59

       Mm-hmm.

    7. SWStephen Wolfram46:00

       You know, one of the things I've long been interested in is, is there a simple rule from which, where you just run that rule long enough and you'll get everything that happens in the universe?

    8. TFTim Ferriss46:09

       Mm-hmm.

    9. SWStephen Wolfram46:10

       So in other words, I was talking before about how, you know, simple computational rules, you run them, they do really complicated things.

    10. TFTim Ferriss46:16

        Right.

    11. SWStephen Wolfram46:16

        Sort of the most complicated thing we know about is the whole universe. So could we find a rule where we just write down this rule and, you know, we could run it long enough, it would just make the whole universe? Okay, so then you start thinking, well, let's imagine that we had that rule. Let's imagine that we'd found that r- Let me, let me go actually one, one other place first, which is how quantum mechanics works.

    12. TFTim Ferriss46:42

        Mm-hmm.

    13. SWStephen Wolfram46:42

        So in classical mechanics, you have laws that describe sort of how things move or, or what happens in, in the world. So, uh, uh, you know, there might be something that says, "I throw a ball with a certain velocity, it will move in a certain trajectory." Definite answer.

    14. TFTim Ferriss47:00

        And by classical, you mean Newtonian in this case? Or is that-

    15. SWStephen Wolfram47:03

        Newtonian physics, yes.

    16. TFTim Ferriss47:04

        Got it. Mm-hmm.

    17. SWStephen Wolfram47:05

        Actually, relativistic physics works the same way.

    18. TFTim Ferriss47:08

        Got it. Okay.

    19. SWStephen Wolfram47:08

        That's, that's sort of the distinction between classical, as in not quantum, and quantum.

    20. TFTim Ferriss47:14

        Okay.

    21. SWStephen Wolfram47:14

        So this was kind of the, the dividing line is kind of around 1920. It's about 100 years old.

    22. TFTim Ferriss47:18

        Mm-hmm.

    23. SWStephen Wolfram47:19

        And so in the quantum view of the world, it isn't the case that definite things happen. Instead, the quantum view is there are many paths that get followed. That was kind of a, a Dick Feynman idea, th- this idea of path integrals and, and following many quantum paths. But the, the kind of the notion is that in quantum mechanics, lots of different things happen. The ball goes on many different possible trajectories. We, as observers of what happened, we get to sample across those possibilities and just get to say, "Oh, there was a, a certain probability that this would happen. There's a certain probability that would happen." So that's kind of the, the traditional view of quantum mechanics. So in our models, you have this giant graph that represents this giant network that represents the structure of the universe, and it's continually being re- rewritten according to some rule. What turns out to happen is there are many different possible rewrites that could occur. Those different possible rewrites give you these different paths of history. They give you essentially different, different threads of time, so to speak, different, different possible things that could happen in the universe. Those, those threads of history, they sometimes they branch because two different things could happen next. Sometimes they merge. Because two things end up producing essentially the same universe. So you end up with this whole complicated structure of branching and merging of possible histories for the universe. So now the question is, how do we perceive what's going on in that universe? And why do we not see the universe as this thing where it's branching all over the place and, you know, how can we tell what's happening? Well, the thing we have to realize is that we ourselves are embedded in this branching universe. So our minds are branching just like everything else in the universe is branching. So it turns out sort of the core question of, of sort of how one perceives quantum mechanics is, how does a branching mind perceive a branching universe? And so then this thing that I mentioned that's a feature of us, is we believe that we are persistent in time. And so we, even though at some, in some sort of external God's eye view, so to speak, the universe is branching like crazy. We, we believe that our minds are going through a single thread of experience.

    24. SPSpeaker49:40

        Mm-hmm.

    25. SWStephen Wolfram49:40

        And so that means as we impose that belief on what's actually going on in the universe, we sort of conflate lots of different paths that from the outside would look like the universe is doing different things. But we so know actually those are all in some sense the same thing, because that's what we have to believe in order to have this conceit that we have a definite thread of experience.

    26. SPSpeaker50:04

        Mm.

    27. SWStephen Wolfram50:04

        And so that process is kind of what drives kind of the understanding of how quantum mechanics works. And actually, returning to Dick Feynman again, he always used to say that having worked his whole life on quantum mechanics, he always was very fond of saying, "Nobody understands quantum mechanics."

    28. SPSpeaker50:20

        [laughs]

    29. SWStephen Wolfram50:20

        And he was very, um... And I would talk to him for ages and ages about that. And, and, um, and I, I, I wish he was still around because I think I can finally say, I think I actually understand quantum mechanics.

    30. SPSpeaker50:30

        Mm.
13. 58:24 – 1:06:21

    What is time?

    1. TFTim Ferriss58:24

       I have tried to stretch my, the boundaries of, of how I consider or define time by reading and listening to, say, Carlo Rovelli, who I think, uh, focuses a fair amount of quantum gravity. I, I don't know his research very well. How do you think about time? Is, uh, is how humans experience or think about time just a very convenient collective delusion in terms of its linear past to future nature?

    2. SWStephen Wolfram58:52

       First thing is, what is time?

    3. TFTim Ferriss58:53

       Exactly. [laughs]

    4. SWStephen Wolfram58:56

       That's something that I think we really kind of nailed in, in the way we think about our theory of physics.

    5. TFTim Ferriss59:01

       Mm-hmm.

    6. SWStephen Wolfram59:01

       I mean, time is the inexorable progress of computation.

    7. TFTim Ferriss59:05

       Hmm.

    8. SWStephen Wolfram59:06

       So in other words, the universe is in some state, then the universe is going to be transformed to another state, and another one. That progressive process of transformation is the passage of time.

    9. TFTim Ferriss59:18

       Mm-hmm.

    10. SWStephen Wolfram59:19

        And this phenomenon of computational irreducibility that I was mentioning before, that you kind of can't jump ahead, that is the fact that time is meaningful. There is something, you can't just say, "Oh, I didn't have to go through those moments of time. I could always just jump ahead." Now, in most of the universe, time is just progressing. It's just as the universe is sort of updated, so that corresponds to the passage of time. Now, now, we are part of the universe, so we're being updated, too. If the universe just stopped, we wouldn't know it had stopped because we'd be stopped, too.

    11. TFTim Ferriss59:55

        Mm.

    12. SWStephen Wolfram59:55

        So for example, one, one place where that happens, in the simplest kind of black hole. At the center of the simplest kind of black hole is a space-time singularity, which has the property that it's a place where time stops. And so in our model of physics, what's happening is this universe is being updated, this network is being updated, it's being updated, but if you're at the center of the black hole, it just stops. There's no more update that can be applied. It's like, actually, if you're doing math, you kind of want to get to that point. If you're doing a calculation, you do, oh, we're calculating, these things are happening, and eventually you get to the answer.

    13. TFTim Ferriss1:00:29

        Right.

    14. SWStephen Wolfram1:00:29

        And that's a place where it's fixed. Nothing changes anymore. That's what happens at the center of the black hole. It's kind of bad news in a sense, if you want to have a future, so to speak-

    15. TFTim Ferriss1:00:39

        [laughs]

    16. SWStephen Wolfram1:00:39

        ... because time just stopped. And, [laughs] uh, you know. So time, as far as I'm concerned, is this inexorable progress of computation. And the time is, in the actual way that it manifests in the universe, has many complicated features. So for example, you know, in, in relativity and gravitation theory and so on, there are all kinds of ways in which the notion of when's it the same time as somewhere else is complicated. Like we say, you know, let's say we have a Mars colony one day-

    17. TFTim Ferriss1:01:11

        Mm.

    18. SWStephen Wolfram1:01:12

        And we define, you know, Earth Standard Time. Okay, it's, it's 12:00 noon at this point. Well, it's 20 light minutes away to Mars, for example. Do we say that the 12:00 noon is the time when the light signal from our clock that said it was 12:00 noon on Earth reaches Mars? Or do we try and sort of back-calculate that and say, "Well, it's the time when, you know, it would've reached if the clock had been 20 minutes early," and so on? That whole question of sort of the way in which you put these slices across the universe to define what counts as simultaneity and time, that's kind of the story of relativity theory and gravitation theory and so on, and, uh, that's a, that's another kind of twist in this whole thing. But in quantum mechanics, the big issue is, is there just one thread of time or are there many threads of time? Now, we humans normally only perceive one thread of time. I've sort of wondered whether there's some, you know, some trance that people can go into that's kind of a multi-way trance where, where they actually have multiple threads of experience that, that are going on at the same time. But for most of us, most of the time, it's just there's a, you know, there's a definite thread of experience that we have.

    19. TFTim Ferriss1:02:26

        If I may interrupt for a second, what, what prompted that wonder or question about whether there are people who-

    20. SWStephen Wolfram1:02:31

        One of the features of kind of our model of physics is what ultimately drives the mathematical structure of quantum mechanics is this assumption that we have that we are persistent in time, and that we can conflate things to the point where we have a single thread of experience. If that isn't the case, then we've got a different theory of quantum mechanics, because quantum mechanics ends up being something which says, you do all this quantum mechanical stuff, it has these many paths of history, but in the end, we want to get an answer. We don't wanna be saying we've got two different answers in mind. We've gotta say, "We say a definite thing happened." And so, you know, for example, when people talk about making quantum computers, the big thing that one hopes for is that one can use these multiple threads of history to each run a different computation.

    21. TFTim Ferriss1:03:23

        Mm.

    22. SWStephen Wolfram1:03:23

        And so then you can do all these things in parallel. Now, the big problem, and again, I, I seem to be mentioning Dick Feynman too much here, but, but, uh-

    23. TFTim Ferriss1:03:31

        [laughs] Doesn't bother me. [laughs]

    24. SWStephen Wolfram1:03:32

        He and I worked on quantum computers back in 1981 or so, and it was kind of a funny experience because he did all his calculation by hand, and I was using a computer. I actually found one of the, one of the computations that I did from that just recently. And, you know, he would do these calculations by hand, and I had no idea why the answers he got were right. 'Cause it's just like you do this calculation and it's like you could've done this or this or this. You could've made this or this as- assumption at this point. I don't know why that assumption is right. And he'd look at the stuff I did on a computer, and he'd say, "I have no idea why any of that's right." [laughs]

    25. TFTim Ferriss1:04:05

        [laughs]

    26. SWStephen Wolfram1:04:05

        And, uh, so it was an interesting challenge, so to speak. But, but actually even at that time, we, we kind of concluded that the big question about sort of making use of quantum mechanics to compute things is, how do you determine the answer? In the formal theory of quantum mechanics, it's how does the measurement work in quantum mechanics? How do you actually measure what happened in the quantum process? Well, now what we see is there are all these threads of history, and at the end, us humans, if we want to get a definite answer, have to knit together all those threads of history. And the big question is, how hard is it to knit together those threads of history? And if it's as hard to knit them together as what you gain by having multiple threads, then you don't get an advantage in the end. And that's a, that's a difficult thing to figure out and, you know, it's something we're trying to figure out.

    27. TFTim Ferriss1:04:53

        Uh.

    28. SWStephen Wolfram1:04:53

        I'm not hopeful about the true quantum advantage. I think that the formalism of quantum mechanics is super interesting and, you know, is very... This whole idea of, of these, what we call multi-way graphs and this whole multiple threads of history and so on, that's a very interesting formal thing relevant to many fields. But this idea that you're actually going to be able to make an engineering system out of it and get this sort of quantum advantage, less convincing. I, it's also, as a practical matter, you know, the whole quantum computing effort has caused people to think, "Oh, can we make computers out of things other than electronics and semiconductors and so on?" And that's a completely worthwhile thing as well. So the two ends are worthwhile. I'm not sure that the thing in the middle is so worthwhile.

    29. TFTim Ferriss1:05:36

        [laughs]

    30. SWStephen Wolfram1:05:37

        So that's our notion of time. Now, in terms of people's perception of time, uh, you know, it is this process of, you know, we are undergoing these computations, our minds are undergoing these computations, uh, and so is the rest of the universe, and that's kind of, it's the alignment of the computations going on in our minds with the computation going on in the universe that leads these different forms of time, like the time in thermodynamics of, of things sort of decaying down to heat, or the time in the expansion of the universe, things, you know, things about cosmology and so on. The fact that all those different arrows of time align is a consequence of the fact that they're actually the same thing. They're all just a sort of inexorable process of computation that's happening in the universe.

14. 1:06:21 – 1:10:23

    What constitutes consciousness?

    1. TFTim Ferriss1:06:21

       I'm gonna use a term that is, uh, might be frustratingly undefined, overused to the point that it's often undefined at least. But I'm gonna ask this question anyway, which is, do you have any thoughts on what constitutes consciousness? It can be defined any way you want, or it can just be tossed. Or if that is an emergent property or s- or subjective experience with certain underpinnings that can be ... currently explained. How do you think about, if at all, this may be a terrible question-

    2. SWStephen Wolfram1:06:53

       Yeah, yeah. Well, I've always sort of avoided it because I've, it's always seemed like a deeply slippery thing. But-

    3. TFTim Ferriss1:06:58

       Yeah, I was gonna- [laughs]

    4. SWStephen Wolfram1:06:58

       ... recently kind of confronted with, I need to apply the idea of consciousness. I may not have to... And, and here's how. In the universe, ultimately there are all these possible computations that can happen. And, but our minds don't do all possible computations. Our minds, they're much more filtered in what they do. And in particular, they have these features of computational boundedness, belief and persistence, and so on. And I think these are, for me, those are the things we need to use about consciousness to derive things in physics. So those are features of consciousness that distinguish us from the rest of the universe. It's kind of actually a little disappointing, because we might have thought, oh, there's, you know, inanimate matter, and there's this and that, and we've got this big stack we're building, and it goes through life, and eventually we get to intelligence, consciousness. We are the tippy top. You know, we are the best thing in the universe, so to speak.

    5. TFTim Ferriss1:07:54

       [laughs]

    6. SWStephen Wolfram1:07:55

       But actually, what I've come to realize is that, that that's not true at all, that the universe has much more capability than we have, and this thing we call consciousness is a filtering of that capability to something specific where we believe, for example, that there's a single thread of experience that we have. And that that's kind of the, the thing that, that consciousness, the sort of the application of consciousness to science, is this thing where it's not about everything in the universe. It's just about the particular things that w- are our, sort of the way that our minds perceive things.

    7. TFTim Ferriss1:08:31

       Hmm.

    8. SWStephen Wolfram1:08:31

       People talk about, well, how can you talk about this in this kind of very materialistic way? And isn't there some magic thing in consciousness that is this sort of spark that is different from everything else in the universe? Well, to us, inside, there absolutely is. To us inside, we are this one point in ruliad space where there is this set of things going on, that is our experience of the universe, and it's completely unique. And, you know, there may be some other point in ruliad space, some other mind that is fairly close by where we can say, "We're experiencing these things. We can tell that they're similar to what being experienced here." But each sort of consciousness is, is unique in that sense. Now, you know, I, I was kind of doing an exercise recently, which I need to finish, which is to kind of describe what it's like to be a computer.

    9. TFTim Ferriss1:09:21

       Mm.

    10. SWStephen Wolfram1:09:21

        And you imagine we humans, you know, we live our lives, we remember a bunch of stuff through our lives. Eventually, it's all lost when we die. And, uh, the question is, for a computer, from the time it boots up to the time the operating system crashes, that's a period of time over which the computer has sort of its life experiences. And how do those life experiences compare to the quote's life experiences that we humans have? You know, there is a, a kind of a whole sort of inner thinking that's going on for the computer. How does that compare with us humans? There's sort of the communication with other computers, the, the experience of the outside world, and so on. You know, how does that compare? How can we describe that in, uh, uh, what it's, what it's like to be even a current computer? Forget sort of the science fiction AI of the future. Just talk about a current computer. What would it be like to be the, the sort of inside that, experiencing things from the point of view of, of the machine, so to speak?

15. 1:10:23 – 1:18:04

    Personal infrastructure and productivity.

    1. TFTim Ferriss1:10:24

       Let's segue to personal productivity. So this is something I imagine you do still think about a fair amount. And I've read a fair amount of your writing on personal infrastructure hacks and so on, and it seems like there are, as I think you might describe them, nerdy productivity hacks that then later become more mainstream or more accepted, more widely distributed. Are there any personal productivity or infrastructure tools or hacks that you are using now that you think will gain more adoption in some form in the not so distant future?

    2. SWStephen Wolfram1:11:05

       I started live streaming a bunch of sort of working meetings that I do.

    3. TFTim Ferriss1:11:11

       Mm-hmm.

    4. SWStephen Wolfram1:11:11

       And we started this about, uh, when was it? 2017. Um, so a few years ago. And it's really an interesting process because, you know, a large fraction of software design reviews that we do are live streamed. And that means, you know, people who are in the meeting are a little bit more paying attention because they kind of know it's going out to the world. But it's also really nice because there's kind of an immediate feedback. We'll get-

    5. TFTim Ferriss1:11:41

       Mm-hmm

    6. SWStephen Wolfram1:11:41

       ... you know, if we announce some particular topic we're gonna work on, we'll get some world experts in that topic often will show up because, gosh, they know they're gonna be stuck using our tools, and they might as well contribute-

    7. TFTim Ferriss1:11:53

       [laughs]

    8. SWStephen Wolfram1:11:53

       ... to getting them to be designed right, and also people who are just energetic users of our technology. And it's really a wonderful kind of immediate feedback. And I think it's, to me, it helps me feel that the time I'm spending doing, you know, very detailed, grinding away, trying to figure out how software should be designed and so on, it, it feels like the fact that I'm leaving some record of this-

    9. TFTim Ferriss1:12:19

       Mm-hmm

    10. SWStephen Wolfram1:12:19

        ... feels like it makes it more meaningful. And I know people have used some of our live streams for software engineering classes and things like this. And so it's, uh, you know, it helps me make it seem more meaningful, so to speak.

    11. TFTim Ferriss1:12:31

        Mm-hmm.

    12. SWStephen Wolfram1:12:31

        I think I've been doing... The even more extreme version of that is that I've been doing video work logs, which means I'm just sitting by myself and I'm working on something and I'm writing some, you know, some document or something like that, and I just record it. And, you know, I, like last night, I probably recorded five hours of w- video work logs. I'm basically was working on this sort of personal journey history thing, and I'm recording my screen, and I'm just recording what I'm doing. Now, you know, why am I doing this? Because it's easy to do, and somehow it makes it feel a little bit more meaningful to me. It sort of makes me think, oh, I'm not gonna goof off in that way because I'm screen recording everything.

    13. TFTim Ferriss1:13:11

        [laughs]

    14. SWStephen Wolfram1:13:12

        Uh, okay, I admit I have a secondary screen, so I can goof off on-

    15. TFTim Ferriss1:13:15

        [laughs]

    16. SWStephen Wolfram1:13:16

        ... on the secondary screen. Um, but, uh, and the other thing is, when I'm doing science stuff, what has happened a number of times is people say, "Well, how did you figure that out?" I'm saying, you can really find out how I figured that out. Just go look at this video-

    17. TFTim Ferriss1:13:35

        Just watch it

    18. SWStephen Wolfram1:13:35

        ... and you can find the minute where I figured this out, and maybe I got it wrong. And you'll see, look, you know, he did something really stupid there, and you can see that moment and you can then un- unwind it. Same thing, by the way, for our software design meetings. The people who do project management routinely go back and look at, you know, all kinds of pieces of the meetings. What actually happened? How did we decide this? Oh, you know, a bug showed up there. Let's, let's go carve that piece of the video out and, and send it to people and so on.

    19. TFTim Ferriss1:14:07

        Hmm.

    20. SWStephen Wolfram1:14:07

        You know, I think this thing about doing sort of, uh, actual sort of production meetings, so to speak, live streamed is, I don't know anybody else who does that. I think nobody else is crazy enough to do it. And, uh, you know, part of why we can do it is that we're in a unique place and sort of technology space where it's not like... I mean, I, I know people who've wanted to compete with us have watched live streams. It's like, good luck, you know?

    21. TFTim Ferriss1:14:30

        [laughs]

    22. SWStephen Wolfram1:14:31

        You just spent 35 years building all this stuff. One live stream is not-

    23. TFTim Ferriss1:14:34

        Yeah

    24. SWStephen Wolfram1:14:34

        ... gonna let you rebuild that tower. So, you know, that's one thing. The other thing that I myself have become sort of confident enough that even though I know I'm gonna make, you know, say really stupid things on these live streams, I don't care.

    25. TFTim Ferriss1:14:48

        Yeah.

    26. SWStephen Wolfram1:14:48

        These are sort of real-life things where, yes, I'm gonna make mistakes. People are going to say, "You're wrong, you're wrong," and we're gonna have a little argument and eventually I'm gonna say, "Hey, okay, you're right."

    27. TFTim Ferriss1:15:00

        Mm-hmm.

    28. SWStephen Wolfram1:15:00

        And I don't have a internal sort of ego issue with either that process happening or that being something that people can go back and find it, I'm sure. I'm sure it's possible to find all kinds of terrible, stupid things that I said in these live streams and so on. Another, okay, so another productivity hack I suppose related to live streaming is this. So I've also been doing, at the beginning of the pandemic, I thought, oh, all these kids are gonna be out of school. I know a bunch of stuff about science. Every so often I'll do a Q&A. You know, once a week I'll do a Q&A about science and tech for kids and others. So I started doing this at the beginning of the pandemic, and I've still been doing it. I've done 100 episodes or more now of this, you know, hour, hour and a half on Fridays of science and technology Q&A for kids and others. Okay, so what has that done for me? Well, people ask all kinds of crazy things, and it makes me think about stuff. And I find that this process of I'm just, you know, sitting here looking at the camera and no notes, no looking anything up, just how can I figure out the answer to that question? A couple of days ago, there was a question somebody asked that made me realize some piece of physics that is relevant to our physics project-

    29. TFTim Ferriss1:16:17

        Hmm

    30. SWStephen Wolfram1:16:17

        ... that I'd never realized before. And the process of explaining it, particularly with the forced feature that I just, I'm just gonna go on talking at the camera, so to speak. It's that forcing function of so now, you know, you gotta figure something out I found really useful for understanding things. And I've been doing actually two other alternating alternate weeks Q&As, one about history of science and technology, and the other about business innovation and managing life. More your kind of territory.
16. 1:18:04 – 1:24:49

    Maintaining energy in the midst of a busy life.

    1. TFTim Ferriss1:18:04

       Let's look at maybe some of the, if there is a there there, we'll find out, some of the physiological underpinnings of productivity. So we have these physical bodies, and you seem to, uh, this could just be my perception, but have energy reserves. I'm not using energy in a very precise physics way, but more in a metabolic way, right? Like, you're producing enough neurotransmitters and, uh, you store enough glycogen and so on that you are able to maintain a very high, seems like a very high rate of output. Do you think about energy management in that context? Or is that something that just comes so naturally out of the box that you just have that advantage and you don't have to think about it?

    2. SWStephen Wolfram1:18:50

       I think I'm lucky that I'm fairly energetic. It's always amusing to me that, you know, I'm an old guy now and, you know, I can, I can sort of out-energize-

    3. TFTim Ferriss1:18:57

       [laughs]

    4. SWStephen Wolfram1:18:58

       ... you know, lots of young folk who are working with me and so on.

    5. TFTim Ferriss1:19:01

       [laughs]

    6. SWStephen Wolfram1:19:01

       Actually, I get a kick out of being able to do that. So-

    7. TFTim Ferriss1:19:04

       [laughs] Yeah, why not?

    8. SWStephen Wolfram1:19:05

       That helps add energy to the whole, to the whole picture But no, I, I think one thing is that I do things that I like to do, and for me that's a, that's a huge energizing force. I mean, if I was like, "Oh gosh, I have to do this, and I don't really want to do it, and I'm not very interested," and it's like, you know, I'm jumping into things where I really want to do this.

    9. TFTim Ferriss1:19:27

       Mm.

    10. SWStephen Wolfram1:19:28

        Okay, another strange thing I just did. I seem to have been reliving my life 50 years ago in the last few weeks because I, I had just, I decided to organize, a couple of months ago I initiated this, a reunion for my elementary school graduating class, which was 1972. Small sort of sub group of people. And so it was kind of the 50-year follow-up. It was a l- actually it was, uh, you know, I liked these people 50 years ago, I like them 50 years later. That was nice.

    11. TFTim Ferriss1:19:58

        Mm.

    12. SWStephen Wolfram1:19:58

        But, uh, I realized, you know, one of the things that's a little disappointing is some fraction of these people were like, they're writing little blurbs about what we've been doing, and they're like, "I retired. I retired." Et cetera, et cetera, et cetera. And they're British folk, so they had lots of witty things to say-

    13. TFTim Ferriss1:20:14

        [laughs]

    14. SWStephen Wolfram1:20:14

        ... about, you know, what they were doing in their retirement. But so I was realizing, well, I'm not retired and I'm not even... And I realized I've been working more than 12 hours a day every day for basically all of the last 50 years.

    15. TFTim Ferriss1:20:29

        Mm.

    16. SWStephen Wolfram1:20:29

        And I'm having a good time. You know, I've been lucky enough to be able to mostly do things that sort of add energy to me rather than taking it away. I mean, the things, you know, when you do, when I do creative kinds of things and I figure stuff out, and even write things and so on, the process of like finishing them and getting them done is energizing to me.

    17. TFTim Ferriss1:20:52

        Mm-hmm.

    18. SWStephen Wolfram1:20:52

        And I think that's, you know, if, if I was doing things where I'm like, oh, I don't know, back in, back in the day before, before we realized this just didn't work, I would occasionally go shopping with my wife.

    19. TFTim Ferriss1:21:04

        [laughs]

    20. SWStephen Wolfram1:21:05

        Okay? Long, long ago.

    21. TFTim Ferriss1:21:06

        Uh-huh.

    22. SWStephen Wolfram1:21:06

        And I would try and take my wife to science museums, okay? So my wife is a mathematician, so the science museums, they're not so far away, but they're far enough away that, that she's like, "Oh, I'm getting so tired walking around the science museum." So for me, it would have a physiological effect on me going around, walking around shops. I, you know, I'm like, "I feel really tired." [laughs] You know, I have to-

    23. TFTim Ferriss1:21:28

        [laughs]

    24. SWStephen Wolfram1:21:28

        ... I have to kind of, you know-

    25. TFTim Ferriss1:21:29

        Getting so sleepy

    26. SWStephen Wolfram1:21:30

        ... lie down, et cetera, et cetera, et cetera.

    27. TFTim Ferriss1:21:32

        [laughs]

    28. SWStephen Wolfram1:21:32

        Um, I think the effect that I'm doing things I really want to be doing is an important effect.

    29. TFTim Ferriss1:21:38

        Mm.

    30. SWStephen Wolfram1:21:38

        Now, you know, having said that, I, I did discover when I was kind of like 40 years old, "Hey, you should do some exercise." And that helped, for me, I think add a bunch of energy. I mean, I've, for the last three years I've, I've walked more than 10,000 steps every single day for the last three years.
17. 1:24:49 – 1:27:11

    Avoiding once-inevitable sickness after air travel.

    1. TFTim Ferriss1:24:49

       Yeah.

    2. SWStephen Wolfram1:24:49

       But, uh, you know, I did, I did learn, okay, so this is one not yet very scientific hack fact, okay?

    3. TFTim Ferriss1:24:56

       Mm-hmm.

    4. SWStephen Wolfram1:24:56

       Which is I was curious what has caused me to get sick. When I've gotten sick, why have I gotten sick? And so I have the data for I think 27 years maybe of, um, I think all the times I've gotten sick. It's always upper respiratory, you know, things, right? And so I think I've gotten sick 25 times in 27 years, and the question is what was I doing when I got sick? And was it, you know, oh, I went out and I'd met a bunch of people, or was it whatever? And the one correlation, and I haven't been completely scientific about this, the one correlation has, was it was often two days after I was on a flight, on a plane.

    5. TFTim Ferriss1:25:38

       Huh. Yeah.

    6. SWStephen Wolfram1:25:38

       Okay? And in a few cases, that was not a commercial plane. That was a private plane, so it... without a lot of other people on it.

    7. TFTim Ferriss1:25:48

       Yeah.

    8. SWStephen Wolfram1:25:48

       And so it's kind of interesting. And so then I ask my medical research friends and so on, "Hey, what's going on here?" And here's the theory. The theory would be, you know, a big part of upper respiratory defense, so to speak, is the innate immune system operating like in one's nose and so on.

    9. TFTim Ferriss1:26:06

       Mm.

    10. SWStephen Wolfram1:26:06

        And if you get your nose dried out and so on from being in the, you know, dry air and on planes and things like that, your little innate immune system doesn't stand a chance. So my, my hack has been take things like wheat germ and so on that stimulate, um, just before I go on a plane, take that and a couple of other things, and so far we only have an N of about eight or something [laughs] of trips I've done.

    11. TFTim Ferriss1:26:34

        [laughs]

    12. SWStephen Wolfram1:26:34

        So far I haven't gotten sick.

    13. TFTim Ferriss1:26:36

        So far so good. Well, it also makes me think of ways that you could n- not necessarily humidify, but maintain the sort of m- moisture integrity-

    14. SWStephen Wolfram1:26:48

        Yes

    15. TFTim Ferriss1:26:48

        ... of the sinal lining as well with a spray or something like that.

    16. SWStephen Wolfram1:26:53

        Yeah, I thought about that. My most relevant medical research friend claimed it's easier to just take choline than it is to try and do that.

    17. TFTim Ferriss1:27:00

        Try to keep the nose well-hydrated. [laughs]

    18. SWStephen Wolfram1:27:03

        It's kind of a strange thing, you know. You're on some flight going somewhere and you're, like, continually-

    19. TFTim Ferriss1:27:08

        [laughs]

    20. SWStephen Wolfram1:27:08

        ... tapping things into your nose or whatever.

    21. TFTim Ferriss1:27:09

        [laughs]

18. 1:27:11 – 1:28:11

    Making time count — in sickness and in health.

    1. SWStephen Wolfram1:27:11

       But, but you know, one of the things I've found that, that for me, it's like keep the list of things to do when I'm tired because for me, in terms of motivation and so on, it's always nice. You know, like, if I'm sick, I might be like, "Oh my gosh, I'm sick. I'm so... That's so terrible." But in a sense, I'm like, great, now I have a chance to do these things-

    2. TFTim Ferriss1:27:31

       [laughs]

    3. SWStephen Wolfram1:27:31

       ... that I knew I had to do. So I'm, I do the same thing when I'm driving places. You know, I always maintain a call-while-driving list. You know, phone calls that are slightly more, you know, I've gotta do this sometime. I don't need to be in front of a computer. This is something I can do then. It's actually good for lots of kinds of interactions that I do where I, I kind of wouldn't... I'd never get around to it. It's just like, you know, if there's a person who lives in the same city that you do, you never see them.

    4. TFTim Ferriss1:27:56

       [laughs]

    5. SWStephen Wolfram1:27:57

       But if they live somewhere completely different, you know, oh, I'm coming to wherever for a day, and you end up seeing them. And I... It's been kind of the same thing for me with call while driving. It's like, well, I'm going to call somebody, and so, you know, this is that process.

19. 1:28:11 – 1:35:23

    Parting thoughts.

    1. TFTim Ferriss1:28:12

       Well, Stephen, I'm so continually impressed with not just the breadth of your thinking, but how you log and track and interpret so much data. I mean, I think that I take a lot of notes, but you mentioned at the top of this conversation a quarter million pages or something [laughs] along those lines. It's just incredible.

    2. SWStephen Wolfram1:28:36

       That's the stuff on paper, actually. I have three million emails as well, so yeah. A lot of stuff over a long period of time.

    3. TFTim Ferriss1:28:42

       So a lot of stuff over a long period of time, and I would, uh, love to at some point do a round two. We could do themed conversations on probably several dozen different topics. Is there anything else that you would like to mention in this conversation or call my audience's attention to?

    4. SWStephen Wolfram1:29:02

       Oh, my.

    5. TFTim Ferriss1:29:02

       Anything at all in terms of closing remarks, comments, any grievances you'd like to air publicly? Uh [laughs]

    6. SWStephen Wolfram1:29:09

       [laughs] I don't-

    7. TFTim Ferriss1:29:09

       Anything at all that you'd like to mention before we-

    8. SWStephen Wolfram1:29:13

       Makes me want to ask you for a bunch of personal productivity hacks and so on, and the what am I missing type thing, 'cause that's-

    9. TFTim Ferriss1:29:19

       Oh, boy

    10. SWStephen Wolfram1:29:19

        ... that's always, you know-

    11. TFTim Ferriss1:29:20

        Yeah

    12. SWStephen Wolfram1:29:21

        ... one slowly accumulates these things. And I find, you know, I'll try things.

    13. TFTim Ferriss1:29:25

        Mm-hmm.

    14. SWStephen Wolfram1:29:25

        And probably two-thirds of the things I try work-

    15. TFTim Ferriss1:29:28

        Mm-hmm

    16. SWStephen Wolfram1:29:28

        ... and one-third don't. But I want to keep trying them anyway, so yeah, I think, uh, no, I... We've covered all kinds of things.

    17. TFTim Ferriss1:29:36

        I look forward to hopefully seeing you again in person at some point, but this has been delightful and very fun for me. I've taken copious notes, so I will be doing lots of follow-up on my own. And you seem to be doing pretty well on the productivity side. If I think of anything that is a, a gross omission, I will be sure to send it to you. [laughs]

    18. SWStephen Wolfram1:29:56

        Okay. Great.

    19. TFTim Ferriss1:29:56

        People can find you on Twitter, Stephen, that's a P-H, Stephen_Wolfram. Then Facebook/stephenwolfram, linkedin.com, also your name and then the website stephenwolfram.com. And we'll link to everything that you've mentioned. Is there anything that you would like to point people to that is top of mind for you at the moment, or any resources that people may not find on their own?

    20. SWStephen Wolfram1:30:23

        The stuff I write ends up in writings.stephenwolfram.com. I put lots of effort into writing these things, so hopefully some people find them fun to read. Although even the process of writing them, as I was explaining, is a useful process in its own right. There's also a recent thing for me is we just launched our Wolfram Institute, which is a, um... That's kind of a, I suppose a, an attempted productivity hack. You know, I've... My company, which I started now 36 years ago, is kind of my machine for turning ideas that I have into real things. And it's, you know, it's 800 people who are really, really good at doing that and coming up with their own ideas as well. But that's been a thing where we mostly, we make products. But one of the problems I've been trying to solve is if you're making basic science What's the machine that does that? And I've-

    21. TFTim Ferriss1:31:16

        Mm-hmm

    22. SWStephen Wolfram1:31:16

        ... sort of carved off a bit of resources from the company and so on to do it. But we just, just recently launched Wolfram Institute, which is a thing whose goal is to do basic science, and that's kind of a new thing in the last just few weeks. So stay tuned for interesting things that are happening there, and I guess, um, there'll be more, yet more live streaming of science in action and so on there. So those are a few things. I suppose the other, you know, I have to plug my life work. My life work is building Wolfram Language and Wolfram|Alpha and Mathematica and so on, uh, which are all part of the same idea of sort of make the world computational. And I suppose the, the one sort of pitch I would, I would make is what we've built, I can inexorably see is an artifact from the future.

    23. TFTim Ferriss1:32:08

        Hmm.

    24. SWStephen Wolfram1:32:09

        In other words, the direction that things are going in is going in this direction of representing the world computationally and being able to really make use of that. But, you know, there are m- a few million people who actually do make use of it in our technology stack, but there are a lot of millions of people who don't. And, you know, this is sort of an inexorable piece of the future, and it's a big advantage if you can kind of grab the magic from the future. You know, I, I've taken to a lot of work with kids who are learning our stuff and doing projects and so on, and I've taken to referring to, you know, learning computational language is a superpower.

    25. TFTim Ferriss1:32:48

        Hmm.

    26. SWStephen Wolfram1:32:48

        You get to do that, and then you can do all kinds of magic things with it. Learn that superpower.

    27. TFTim Ferriss1:32:52

        Yeah.

    28. SWStephen Wolfram1:32:53

        More people should do it, and it's, it's one of these things where you can kind of see in, in the world when things involve sort of big ideas, there's a certain inexorable slowness to the way that they get adopted, and there are always some, some number of early adopters who, you know, are the ones that run out in front.

    29. TFTim Ferriss1:33:12

        Mm-hmm.

    30. SWStephen Wolfram1:33:13

        So my parting pitch would be, you know, if you don't understand computational language and Wolfram Language and so on, try to understand it because it is, it is for me, the... You know, you talk about productivity hacks. The biggest amplifier, hugest productivity hack is the whole computational language idea. That's what, you know, all the things I've done in science and in technology, they kind of are all based on that idea and the kind of tower of technology that, that we built around that. So that's my, that's my kind of parting ultimate productivity hack.

Episode duration: 1:35:44