#637: Stephen Wolfram — Personal Productivity Systems, Richard Feynman Stories, Computational Thinking as a Superpower, Perceiving a Branching Universe, and The Ruliad... The Biggest Object in Metascience

Brought to you by Tommy John https://tommyjohn.com/tim premium underwear, Eight Sleep’s Pod Cover http://eightsleep.com/Tim sleeping solution for dynamic cooling and heating, and ButcherBox http://butcherbox.com/tim premium meats delivered to your door. Stephen Wolfram (@stephen_wolfram https://twitter.com/stephen_wolfram) is the creator of Mathematica https://www.wolfram.com/products/mathematica/, Wolfram|Alpha https://www.wolframalpha.com/ and the Wolfram Language https://www.wolfram.com/language/; the author of A New Kind of Science https://www.amazon.com/New-Kind-Science-Stephen-Wolfram/dp/1579550088/?tag=offsitoftimfe-20; the originator of the Wolfram Physics Project https://www.wolframphysics.org/; and the founder and CEO of Wolfram Research https://www.wolfram.com/. Over the course of more than four decades, he has been a pioneer in the development and application of computational thinking and has been responsible for many discoveries, inventions, and innovations in science, technology, and business. Please enjoy! This episode is brought to you by ButcherBox http://butcherbox.com/Tim! ButcherBox http://butcherbox.com/Tim makes it easy for you to get high-quality, humanely raised meat that you can trust. They deliver delicious, 100% grass-fed, grass-finished beef; free-range organic chicken; heritage-breed pork, and wild-caught seafood directly to your door. This Black Friday, your search for amazing deals on high-quality protein ends with ButcherBox. ButcherBox is offering my listeners one of their best steak deals: Free Rib Eyes for a Year, plus $20 off http://butcherbox.com/tim. Get two, 10 oz rib eyes FREE in every box for a whole year when you join, plus an additional $20 off! Sign up today at butcherbox.com/Tim and use code TIM to get Free Rib Eyes for a Year, plus $20 off. * This episode is also brought to you by Eight Sleep http://eightsleep.com/Tim! Eight Sleep’s Pod Cover http://eightsleep.com/Tim is the easiest and fastest way to sleep at the perfect temperature. It pairs dynamic cooling and heating with biometric tracking to offer the most advanced (and user-friendly) solution on the market. Simply add the Pod Cover http://eightsleep.com/Tim to your current mattress and start sleeping as cool as 55°F or as hot as 110°F. It also splits your bed in half, so your partner can choose a totally different temperature. For a limited time, Eight Sleep is offering my listeners up to $450 off their Sleep Fit Holiday Bundle, which includes my personal favorite, the Pod 3 Cover. Go to EightSleep.com/Tim http://eightsleep.com/tim to get the exclusive holiday savings. Eight Sleep currently ships within the USA, Canada, the UK, select countries in the EU, and Australia. That’s EightSleep.com/Tim http://eightsleep.com/Tim * This episode is also brought to you by Tommy John https://tommyjohn.com/tim premium underwear! For men, Tommy John https://tommyjohn.com/tim offers six different styles so you can find the one that suits you best. Their line of men’s briefs and boxers is one of my top choices for all-day comfort. I tested their Second Skin Mid-Length Boxer Brief https://tommyjohn.com/tim and the Cool Cotton Trunk https://tommyjohn.com/tim. Shop Tommy John’s Black Friday sale going on right now, and get 30 percent off sitewide at TommyJohn.com/Tim http://TommyJohn.com/Tim. See the website for details. * [06:58] How Stephen collects information for his vast personal archives. [08:40] When a situation warrants building a matrix. [12:31] Science sometimes makes us look far back to move incrementally forward. [17:49] Befriending the computational. [22:59] How technology helps us navigate natural language. [32:30] How Stephen chose subjects for his book Idea Makers. [35:09] On spending time with Richard Feynman. [37:33] Thoughts on Srinivasa Ramanujan. [39:57] When Stephen started solving science problems with computers. [42:00] Heresies today, gospels tomorrow. [50:14] Ruminations on the ruliad. [1:03:46] What is time? [1:12:03] What constitutes consciousness? [1:15:56] Personal infrastructure and productivity. [1:23:25] Maintaining energy in the midst of a busy life. [1:29:37] Avoiding once-inevitable sickness after air travel. [1:31:50] Making time count — in sickness and in health. [1:32:45] Parting thoughts. * For show notes and past guests on The Tim Ferriss Show http://tim.blog/podcast, please visit tim.blog/podcast https://tim.blog/podcast/?utm_source=podcast&utm_medium=podcast&utm_campaign=podcast-description. For deals from sponsors of The Tim Ferriss Show http://tim.blog/podcast, please visit tim.blog/podcast-sponsors http://tim.blog/podcast-sponsors Sign up for Tim’s email newsletter (5-Bullet Friday) at tim.blog/friday https://go.tim.blog/5-bullet-friday-1/. For transcripts of episodes, go to tim.blog/transcripts http://tim.blog/transcripts. Discover Tim’s books: tim.blog/books http://tim.blog/books. Follow Tim: Twitter: twitter.com/tferriss https://twitter.com/tferriss Instagram: instagram.com/timferriss https://instagram.com/timferriss/ YouTube: youtube.com/timferriss https://www.youtube.com/timferriss Facebook: facebook.com/timferriss https://www.facebook.com/TimFerriss/ LinkedIn: linkedin.com/in/timferriss http://linkedin.com/in/timferriss Past guests on The Tim Ferriss Show http://tim.blog/podcast include Jerry Seinfeld https://tim.blog/2020/12/08/jerry-seinfeld/, Hugh Jackman https://tim.blog/2020/06/26/hugh-jackman/, Dr. Jane Goodall https://tim.blog/2020/04/16/jane-goodall/, LeBron James https://tim.blog/2018/11/27/lebron-james-mike-mancias/, Kevin Hart https://tim.blog/2020/05/20/kevin-hart/, Doris Kearns Goodwin https://tim.blog/2018/09/07/doris-kearns-goodwin-leadership/, Jamie Foxx https://tim.blog/2015/12/06/jamie-foxx/, Matthew McConaughey https://tim.blog/2020/10/19/matthew-mcconaughey/, Esther Perel https://tim.blog/2017/05/21/esther-perel/, Elizabeth Gilbert https://tim.blog/2020/05/08/elizabeth-gilbert/, Terry Crews https://tim.blog/2017/12/20/terry-crews-how-to-have-do-and-be-all-you-want/, Sia https://tim.blog/2020/08/12/sia/, Yuval Noah Harari https://tim.blog/2020/10/27/yuval-noah-harari/, Malcolm Gladwell https://tim.blog/2016/06/21/malcolm-gladwell/, Madeleine Albright https://tim.blog/2020/05/27/secretary-madeleine-albright/, Cheryl Strayed https://tim.blog/2017/03/30/cheryl-strayed/, Jim Collins https://tim.blog/2019/02/18/jim-collins/, Mary Karr, https://tim.blog/2020/11/11/mary-karr/ Maria Popova https://tim.blog/2014/10/21/brain-pickings/, Sam Harris https://tim.blog/2020/05/15/sam-harris-2/, Michael Phelps https://tim.blog/2021/01/21/michael-phelps-grant-hackett/, Bob Iger https://tim.blog/2020/01/16/bob-iger/, Edward Norton https://tim.blog/2019/10/31/edward-norton-motherless-brooklyn/, Arnold Schwarzenegger https://tim.blog/2015/02/02/arnold-schwarzenegger/, Neil Strauss https://tim.blog/2014/06/24/neil-strauss/, Ken Burns https://tim.blog/2019/09/12/ken-burns/, Maria Sharapova https://tim.blog/2017/08/26/maria-sharapova/, Marc Andreessen https://tim.blog/2016/05/29/marc-andreessen/, Neil Gaiman https://tim.blog/2019/03/28/neil-gaiman/, Neil de Grasse Tyson https://tim.blog/2019/10/03/neil-degrasse-tyson/, Jocko Willink https://tim.blog/2016/09/21/jocko-willink-on-discipline-leadership-and-overcoming-doubt/, Daniel Ek https://tim.blog/2020/12/03/daniel-ek/, Kelly Slater https://tim.blog/2020/09/08/kelly-slater/, Dr. Peter Attia https://tim.blog/2019/11/27/peter-attia-fasting-metformin-longevity/, Seth Godin https://tim.blog/2016/02/10/seth-godin/, Howard Marks https://tim.blog/2018/09/25/howard-marks/, Dr. Brené Brown https://tim.blog/2020/02/06/brene-brown-striving-self-acceptance-saving-marriages/, Eric Schmidt https://tim.blog/2019/04/09/eric-schmidt/, Michael Lewis https://tim.blog/2020/05/01/michael-lewis/, Joe Gebbia https://tim.blog/2018/03/08/joe-gebbia-co-founder-of-airbnb/, Michael Pollan https://tim.blog/2018/05/06/michael-pollan-how-to-change-your-mind/, Dr. Jordan Peterson https://tim.blog/2021/03/01/jordan-peterson/, Vince Vaughn https://tim.blog/2017/05/31/vince-vaughn/, Brian Koppelman https://tim.blog/2020/04/23/brian-koppelman/, Ramit Sethi https://tim.blog/2019/05/07/ramit-sethi/, Dax Shepard https://tim.blog/2020/11/18/dax-shepard/, Tony Robbins https://tim.blog/2014/10/15/money-master-the-game/, Jim Dethmer https://tim.blog/2020/05/18/jim-dethmer/, Dan Harris https://tim.blog/2020/11/19/dan-harris/, Ray Dalio https://tim.blog/2017/09/13/ray-dalio/, Naval Ravikant https://tim.blog/2015/08/18/the-evolutionary-angel-naval-ravikant/, Vitalik Buterin https://tim.blog/2021/03/08/vitalik-buterin-naval-ravikant/, Elizabeth Lesser https://tim.blog/2021/03/16/elizabeth-lesser/, Amanda Palmer https://tim.blog/2019/04/18/amanda-palmer-2/, Katie Haun https://tim.blog/2021/02/18/katie-haun/, Sir Richard Branson https://tim.blog/2017/10/09/richard-branson/, Chuck Palahniuk https://tim.blog/2020/09/02/chuck-palahniuk/, Arianna Huffington https://tim.blog/2017/10/18/arianna-huffington/, Reid Hoffman https://tim.blog/2015/08/31/the-oracle-of-silicon-valley-reid-hoffman-plus-michael-mccullough/, Bill Burr https://tim.blog/2017/09/17/bill-burr/, Whitney Cummings https://tim.blog/2015/06/26/whitney-cummings/, Rick Rubin https://tim.blog/2015/05/15/rick-rubin/, Dr. Vivek Murthy https://tim.blog/2020/03/26/vivek-murthy/, Darren Aronofsky https://tim.blog/2017/09/09/darren-aronofsky/, Margaret Atwood https://tim.blog/2022/02/22/margaret-atwood/, Mark Zuckerberg https://tim.blog/2022/03/24/mark-zuckerberg/, Peter Thiel https://tim.blog/2014/09/09/peter-thiel/, Dr. Gabor Maté https://tim.blog/2018/02/20/gabor-mate/, Anne Lamott https://tim.blog/2021/07/09/anne-lamott/, Sarah Silverman https://tim.blog/2022/01/12/sarah-silverman/, Dr. Andrew Huberman https://tim.blog/2021/07/06/andrew-huberman/, and many more. 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• 0:00Tim Ferriss?

  This episode is brought to you by ButcherBox. ButcherBox makes it easy for you to get high-quality, humanely-raised meat that you can trust. They deliver delicious, 100% grass-fed, grass-finished beef, free-range organic chicken, heritage-breed pork, and wild-caught seafood directly to your door. For me, in the past few weeks, I've cooked a ton of their salmon, as well as two delicious barbecue rib racks, in the oven. Super simple. They were the most delicious pork ribs I've ever prepared, and my freezer is full of ButcherBox. When you become a member, you're joining a community focused on doing what's better for all. That means caring about the lives of animals, the livelihoods of farmers, treating our planet with respect, and enjoying better meals together. ButcherBox partners with folks, small farmers included, who believe in going above and

• 0:44Tim Ferriss?

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• 1:27Tim Ferriss?

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• 2:03Tim Ferriss?

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• 2:48Tim Ferriss?

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• 3:31Tim Ferriss?

  reduce sleep interruptions by up to 40%, and get more restful sleep overall. I can personally attest to this because I track it in all sorts of ways. It's the total solution for enhanced recovery so you can take on the next day feeling refreshed. And good news: Eight Sleep has launched the next generation of the Pod. The new Pod 3 enables more accurate sleep and health tracking with twice the number of sensors. It's just a smoother, better experience that delivers you the best sleep on earth. At least, that has been true for me. Simply add this to your existing mattress, and you're all set. It is not magic, but sometimes it does feel like it. It just works. For a limited time, Eight Sleep

• 4:12Tim Ferriss?

  Is offering my listeners, that's you guys, up to $450 off of their Sleepfit Holiday Bundle, which includes my personal favorite, the Pod 3 cover. Go to eightsleep.com/tim to get the exclusive holiday savings. That's all spelled out, E-I-G-H-T. Eightsleep.com/tim. Eight Sleep currently ships within the USA, Canada, the UK, select countries in the EU, and Australia. That's eightsleep.com/tim.

• 4:38Speaker 01

  At this altitude, I can run flat out for a half mile before my hands start to shake. Can I ask you a personal question?

• 4:46Tim Ferriss?

  No, we're just seeing an appropriate time.

• 4:49Speaker 01

  What if I did the opposite? I'm a cybernetic organism living tissue over metal endoskeleton.

• 4:54Tim Ferriss?

  Hello, boys and girls, ladies and germs. This is Tim Ferriss, and welcome to another episode of The Tim Ferriss Show, where it is my job to attempt to deconstruct world-class performers from all different fields, to dissect how they do what they do, how they think, the mental models they use, what it is that makes them tick, makes them work in the way that they do. My guest today is Steven Wolfram. You can find him on Twitter, at Steven underscore Wolfram. That's S-T-E-P-H-E-N underscore W-O-L-F-R-A-M. He is the creator of Mathematica, Wolfram Alpha, and the Wolfram Language, the author

• 5:38Tim Ferriss?

  of A New Kind of Science, the originator of the Wolfram Physics Project, and the founder and CEO of Wolfram Research. Over the course of more than four decades, he has been a pioneer in the development and application of computational thinking, and has been responsible for many discoveries, inventions, and innovations in science, technology, and business. You can find all things Steven Wolfram at stevenwolfram.com. He published his first scientific paper at the age of 15, and had received his PhD in theoretical physics from Caltech by the age of 20. I'm just going to mention a few more things to give you some flavor before we dive into the conversation. In recognition of his early work in physics and computing, Wolfram became, in 1981, the youngest recipient of a MacArthur Fellowship that's also nicknamed the Genius Fellowship.

• 6:22Tim Ferriss?

  Or genius Grant, the release of Wolfram Alpha in May 2009 was widely regarded as a historic step that has defined a new dimension for computation and artificial intelligence, and is now relied on by millions of people every day to compute answers both directly and through intelligent assistants such as Siri and Alexa. Stephen has incredible endurance, incredible energy, incredible breadth of interest and expertise. And without further ado, please enjoy this wide ranging conversation with none other than Stephen Wolfram.

• 6:59Tim Ferriss?

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

• 7:01Speaker 02

  Pleased to be here.

• 7:03Tim Ferriss?

  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?

• 7:27Speaker 02

  I keep an awful lot of stuff. So I've got all my email going back 30 years. I have a habit of writing kind of trip reports for myself whenever I go to some event or something like that. And I have also scans of paper documents. You weren't a paper document. You're more recent 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 I generated 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.

• 8:03Tim Ferriss?

  How do you use the logging of the keystrokes?

• 8:07Speaker 02

  I don't usually.

• 8:08Tim Ferriss?

  You do not?

• 8:10Speaker 02

  Usually I don't. 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 because I had it recorded. That was the thing that caused me like 25 years ago to start recording those. There's one crash. And then I decided 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? You know, those kinds of things.

• 8:35Tim Ferriss?

  And you can track that type of thing?

• 8:37Speaker 02

  Easy to answer that question if you have that data.

• 8:40Tim Ferriss?

  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 going to 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. "Of course, when something is important enough to me, I try to build a matrix for it."

• 9:23Tim Ferriss?

  Could you give an example of what such a matrix might look like?

• 9:27Speaker 02

  Yeah, 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, 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 a place to put that. So it's that kind of thing. And you know, I've been lucky enough. 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 found, you know, for example,

• 10:11Speaker 02

  writing 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. When it's sort of too small a thing, I just don't have a place to put it, and it tends to die on the vine. You know, since you're asking about this, I've just been exposing myself to a very bizarre experience, which is, I've just been finishing a project that I started 50 years ago.

• 10:40Tim Ferriss?

  Wow, okay.

• 10:42Speaker 02

  And in the process of doing this, something that I started, I got interested in 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 written a whole thing about kind of 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.

• 11:19Speaker 02

  And so that got me back into, I'm looking at all my calendars from 1983 and I'm looking at all of these 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 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, this sort of very slow process, I build this intellectual framework.

• 12:03Speaker 02

  And then I get some other clue, I do some other computer experiments, something else happens. And then literally I can trace, because 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 so on. And 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, then it's often very sudden to kind of take the next step. That was a kind of a striking thing to me.

• 12:33Tim Ferriss?

  Ask a few follow up questions about conceptual frameworks and perhaps just request an example of what such a conceptual framework might look like for people listening 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 is it the reward in the process of writing? Is it something gratifying in the process of writing? Are you hoping to impart something to those who read this piece? Why do that?

• 13:14Speaker 02

  That's a good question. I was wondering it myself. I thought it would be really easy, but it wasn't that easy. I have done quite a lot of historical biography, usually of other people. I find that 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, sometimes 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 want to know, how did they come to take that wrong turn? And so that's my next project for the next

• 13:55Speaker 02

  week or so is going back and I collected the material for it. I get to go back and read all the original sources 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, but one actually has really precise detailed data on how some idea got developed. And so I thought, kind of an interesting example of essentially computational history. You know, one thinks

• 14:35Speaker 02

  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 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. So, you know, give you an example. I was working on these 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.

• 15:18Speaker 02

  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 are sort of friends of mine, were trying to work on 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 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

• 16:02Speaker 02

  was realizing that the fact that they couldn't figure out anything was itself a super interesting fact. So in other words, there's this phenomenon I call computational irreducibility, which is basically the big picture of why they couldn't figure out anything else. So, you know, usually 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 going to 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 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.

• 16:46Speaker 02

  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 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. 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."

• 17:31Speaker 02

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

• 17:49Tim Ferriss?

  Makes me think a bit of the Sherlock Holmes, the case of the dog that didn't bark in the night. But the term that I'd love for you just to elaborate on a little bit, and I apologize, this is going to 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 is an example.

• 18:18Speaker 02

  We humans like to sort of come up with abstract, formal ways to describe things. Language itself is an example of that. We see things 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, there are 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've been in the in sort of history, a variety of kinds of organizational approaches. Logic, for example, was one from 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

• 19:01Speaker 02

  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 a precise way to take something like, I don't know, some description of some piece of food, or some description of some position on the earth, 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 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.

• 19:43Speaker 02

  So I mean, in a sense, one of the big things that we as a species, you know, big achievement is human language. You can take things about the world and describe them in a sort of somewhat precise, abstract way. I see computational languages 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 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.

• 20:26Speaker 02

  And then there are, how do you break that down to something even more primitive? 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 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 going to change the color of the cell to be white or to be black or whatever. You just keep running that rule over and over again.

• 21:10Speaker 02

  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. 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 regularity to it? You would just say, it looks completely random to me. 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 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.

• 21:51Speaker 02

  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 think a good analogy perhaps for for sort of the computational description of the world comes from sort of the mathematical notation that one uses to talk about mathematics. I mean, it's sort of an interesting evolution that 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.

• 22:34Speaker 02

  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 I guess 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 parallel for computation of what mathematical notation is for kind of the mathematical way of talking about the world.

• 23:00Tim Ferriss?

  I have a question about natural languages. And 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 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.

• 23:34Speaker 02

  That's from ancient times, but you know, I I went to fancy schools in England when I was growing up and I I learned three languages, Latin, Greek and French. Okay, you don't get to speak Latin or Greek, ancient Greek, at least not in most places. But French you could in principle speak and, you know, I can, I can read like scientific French pretty fluently. 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, no way. I can't do that. I'm, but I, it's one of these things I, I should get over it one day because I think I, you know, I have the vocabulary knowledge, I think, and all that. I just have never really gotten into that. And I'm, I'm not really, you know,

• 24:15Speaker 02

  I've been very deeply involved in computational language. 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 could have put a lot of effort into it, but it's like automatic translation is now going to the point where the many kinds of things not so important anymore. Just like I could have been a champion map reader and I'm glad I didn't put huge effort into that because I just use a GPS now.

• 24:42Tim Ferriss?

  Yeah, 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 you sort of cognitive 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 much it has improved. And fortunately, I already 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

• 25:26Tim Ferriss?

  translation is remarkable. Where do you see that? Or how do you see that developing, say, in the, in the next handful of years or in the near term? I mean, this is something I would imagine you probably have a view on. But where, how do you think we'll be using this type of technology in the next, call it five years?

• 25:45Speaker 02

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

• 26:06Speaker 02

  And in a sense, it is a kind of societal construction of, you know, we all kind of know what a chair is. So when we use the word chair, we kind of know what each other is talking about. 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 they're really just quotes, isn't a translation for that word. 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 as we see the tightening up of the kind of the structural aspects of translation, at what point do we really realize in that culture, there are thoughts that we just don't have in some other culture?

• 26:49Speaker 02

  And that's something, you know, as you start generalizing that, it's kind of like, okay, how do we communicate with sort of the alien intelligences? You know, how do you communicate with cats and dogs? How do you communicate with AIs? 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. But we don't share probably some sort of deep philosophical convictions and so on. And so sort of interesting to see how this process of translation can work and sort of how far out can you translate things? And I guess for computers, you know, the thing I've been most involved in is how do you go from the things we think about in our minds

• 27:34Speaker 02

  to the things that we can represent for a computer? Computers can compute all kinds of things. Many of the things they can compute, we humans don't at least currently care about. There's a certain small set of possible things computers can do that are things that relate to the things that we humans in the current state of our civilization and so on have decided we care about. And so sort of an interesting question to understand kind of to what extent we can translate the things we we think we care about into something which can be represented, computation, and it comes back again. And I suppose, I suppose after one spent one's life working on something, everything somehow relates to these questions like, how do you make this kind of computational language

• 28:17Speaker 02

  to represent kind of human thoughts in a computational way? Now, when you talk about natural language translation and so on, What we've done, you know, when we make our Wolfram Alpha system and intelligent assistant uses of that and so on, what it's doing is it's taking a natural language question like, what's the population of India divided by China in 1960 or something? And it's taking that and it is turning that into a precise kind of computational question, precise sort of symbolic representation that we can then compute the answer from. But whatever poetry there might have been in that question, like, can you tell me the

• 28:59Speaker 02

  population of the some poetic name for some country and some other thing? We crush all the poetry out of that. We're just turning it into, so what is the precise computational representation that is good computer speak, so to speak? Whereas it could have been that the very sort of appreciative way that somebody describes some country translated into some other human language, that notion of appreciation would have been the most important part of that sort of thing that one's asking. But, you know, for the computer, it says, I don't care about that. I'm just here to provide a symbolic representation and give the answer, so to speak.

• 29:40Speaker 02

  I think the thing to understand about translation ultimately is the destination mind isn't built the same way the source mind is necessarily built. And so there may just be no way to change that. Now, you know, you can see that if you imagine, imagine you have two machine learning neural net systems and they've both been trained how to tell cats from dogs, for example. The internal methods by which they will do it will typically be quite different. The details of how they will have reacted to that training will be quite different. And so there isn't sort of a direct translation. Okay, you know, system A does it this way inside. Its most important thing is that the tail has this form or something like this.

• 30:25Speaker 02

  So there isn't this kind of direct internal translation, just as for humans, you know, even if we could do, you know, brain to brain transfer of thoughts, it's not really going to work. Just like when you have two machine learning systems, the details of how they learnt things inside will be different. And that sort of thought experiment, so to speak, about thoughts, direct transfer of thoughts, that sort of also applies that the thing that is the the robust transferer of thoughts is basically language. The thoughts themselves are not directly transferable, but we package them into language, which is this kind of formal representation of thoughts that we can transfer from one mind to another, so to speak. That's my way of thinking about that, at least.

• 31:10Tim Ferriss?

  This underscores, I think, part of the appeal for me in learning these languages, even when they really have very little utility. So I was just studying Romanian, which has very limited use. And part of the fascination is, it's your mentioning these concepts or labels that take the form of language. Even if the translations and literal translation can be conveyed to the target mind, the nuance can be much more challenging to convey. And I find exploring the language as a way to better understand the thinking of a target population, whether Japanese or Romanian, to be a lot of fun. Because, for instance, in Japanese, there are at least 40 or 50 ways to say no. But they might take the form of, well, that's very difficult.

• 31:55Tim Ferriss?

  Or maybe that's possible. Let me ask Mr. Takahashi, and those all mean no. But the translation won't necessarily convey that. And also, thinking about, I'll stop my mini TED Talk here in a second, but the structure of the language, let's just say something as simple as subject, verb, object, I eat the apple versus I the apple eat, which you would find in Japanese. And then in German, you would find it, but only in certain cases where it's a relative clause. And all of that often represents fundamental differences in how people process reality. So I really enjoy it. Now, let me ask you a question about the type of scientific forensic analysis that you've done, where you're looking at how someone took a left turn

• 32:41Tim Ferriss?

  in, say, thermodynamics at some point in time. I have not read this book of yours, but Idea Makers, so a compilation of essays. How did you choose the players on the field for this? How did you choose the people you included?

• 32:55Speaker 02

  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.

• 33:04Tim Ferriss?

  Hmm.

• 33:04Speaker 02

  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 rather nice collection of different types of folks from Dick Feynman and Steve Jobs, who are both people I knew to people like Ada Lovelace and Ramen Ujan, who are people who, you know, died long before I was born.

• 33:29Tim Ferriss?

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• 34:14Tim Ferriss?

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• 34:56Tim Ferriss?

  tommyjohn.com/tim. One more time, that's tommyjohn.com/tim. See the website for more details.

• 35:09Tim Ferriss?

  So 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 searching and learning.

• 35:31Speaker 02

  That's cool.

• 35:32Tim Ferriss?

  And I do have a few diagrams of his as well, which I prize. And I wish I knew more physics. I really enjoyed it when I was younger. I did not pursue it to an advanced level at all. So I really wish I could appreciate his genius 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?

• 35:55Speaker 02

  I met him when I was 18 and he was 60. And he would always say, "I was as quick as you were, but now I'm three times older than you." So, no, he was, he could be quite competitive in those kinds of things. But the thing that I liked about him, like whenever I see it, is he just would think about anything. It's like the thinking apparatus is engaged and will stay engaged, whatever the topic, so to speak. And he liked drilling down to really get, what is the real point? What's the essence of what's going on? And, you know, sometimes he would play a little trick on the world,

• 36:37Speaker 02

  which was, one of the things he was really good at was calculating things by hand. He used computers a little bit, but mostly hand calculation, complicated math, these kinds of things. And so he would do, you know, 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 everybody can do the complicated math, but it's really impressive if you can figure this out by intuition. And so he would then figure out this intuitive answer, throw away the math, tell people only the intuition. And so, you know, there's some fields where, where he did that. And people are like, "We don't

• 37:21Speaker 02

  know how on earth he figured this out." And, you know, people have been trying to reverse engineer the math for years. That was one of his little sort of tricks on the world, so to speak.

• 37:34Tim Ferriss?

  Oh, that's a, that's, that's incredible intellectual sleight of hand. Would Ramanujan, this is someone I know even less about, personify the intuition that Feynman was referring to?

• 37:49Speaker 02

  Well, Ramanujan is a different kind of story. So Ramanujan was a kind of slightly, you know, decently educated 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 then when he started corresponding with mathematicians in England in 1913 or whatever, they were like, 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 goddess so and so told it to me in a dream. Okay. But the truth of it was, he was a really good calculator.

• 38:34Speaker 02

  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 going to be correct. It's not just going to be an approximation. It's going to be exactly right. Occasionally, that intuition failed him. He had 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, some huge place, which he couldn't reach with calculation. So in a sense, he was kind of, I think, a great experimental mathematician. Had he used computers, he would have had a

• 39:17Speaker 02

  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. 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 teenager and so on. And for some reason, you know, the tools existed to be able to do some mathematical computations by computer, but people weren't using them.

• 39:57Speaker 02

  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 thirteen, fourteen, fifteen 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 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, I'm actually pretty bad at it.

• 40:40Speaker 02

  But me with a computer, we're pretty good. But they didn't really even understand the fact that that was a thing back in those days. So, yeah, I've seen this kind of interesting phenomenon of the, when you use tools where people don't necessarily even understand that those tools exist, it's kind of has some interesting consequences.

• 40:59Tim Ferriss?

  I was just gonna say, the attribution, I'm gonna skip, but what was it? Any sufficiently advanced form of technologies indistinguishable from magic? Something like that.

• 41:07Speaker 02

  Yeah, maybe an Arthur C. Clarke.

• 41:09Tim Ferriss?

  Yeah, I think that sounds like Arthur C. Clarke.

• 41:11Speaker 02

  Right. Yeah, no, I think that the thing that I've spent a lot of my kind of scientific effort getting intuition from doing computer experiments. In another age, I would have been there with test tubes and other things, doing physical experiments. Thank goodness I can get away with doing computer experiments, because it's a lot better for me, so to speak. But you do the 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, because it's just coming from not the natural world, but kind of the computational world. You're just turning over this rock in the computational world, and suddenly you discover

• 41:56Speaker 02

  that there's this whole, whole crazy thing going on underneath it, so to speak.

• 42:00Tim Ferriss?

  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 I'll unpack what that means. So he asked each of us to present a heresy, and in this context, what that meant was something you believed to be true, or to be the case, that other people in this group would disagree with you about. And these were a lot of technical folks, and 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

• 42:43Tim Ferriss?

  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?

• 43:07Speaker 02

  I mean, there's several, but there's one example of a big one, but this one is kind of, the resistance is crumbling rapidly. So maybe it doesn't quite count as well, but I think it would still be the case that if you poll, let's say physicists, the resistance would not have completely crumbled. So that's the question of what is space? And is space made of anything? So go back, let's say 120 years. 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

• 43:52Speaker 02

  of something. People had guessed it much earlier. It's made of molecules. So the question now is, what is space made of? This thing that we kind of move around in. Is it just a thing where we get to place something wherever we want? Or does it have an inner structure? And I'd been pretty sure for quite a while that space has kind of an inner structure. It's just made of these discrete sort of atoms of existence. 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

• 44:37Speaker 02

  in the underlying structure of space. That's kind of like if you have a fluid, there's a bunch of these molecules bouncing around. But let's say you just look at little vortex, little eddy on the surface of the fluid, little whirlpool type thing. 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 and the underlying thing that space is made of.

• 45:21Tim Ferriss?

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

• 45:26Speaker 02

  It's kind of a detail. The bigger picture is something which is a more embarrassing feature of current physics. So 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 some small scale stuff happens in physics. There is this phenomenon called zero-point fluctuations. And there are an infinite collection of zero-point fluctuations in the universe that essentially produce energy that are associated with energy that has a gravitational effect that will roll the universe up into a tiny ball.

• 46:11Speaker 02

  That is not what we see. We see a universe that's a big universe, not the 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 a hundred orders of magnitude or more. That's a bigger problem, so to speak, than the dark energy problem. But that's a dark matter problem. Dark energy is yet a different 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. We don't know where the energy is coming from and so on. One feature of our sort of model of physics is that the, the very processes that are

• 46:54Speaker 02

  leading to those vacuum fluctuations and so on, those are the processes that knit together the structure of space. 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. 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. That's an example of how something like that works out in, in our kind of model of physics.

• 47:36Tim Ferriss?

  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?

• 47:43Speaker 02

  Here's another one. It's a little bit more detailed. So what's happened is, as a result of the physics project, we have come to understand a kind of different paradigmatic way of thinking about a bunch of things. And so there are a bunch of fields that you can then apply this new paradigmatic way of thinking to, and start to make sort of foundational changes in those fields. I'll mention another thing, which I don't know how much of a heresy this is, but in physics, the two big theories of physics, well, there are really three big theories of 20th century physics. General relativity, Einstein's theory of gravity, quantum mechanics, and statistical mechanics, which is what brings us things like the second law of thermodynamics, the law of entropy increase, and so on.

• 48:28Speaker 02

  And it's the theory of heat, so to speak. Those are the three big theories of 20th century physics. One of the things that I think is just super amazingly cool is it's turned out that all three of those theories are basically come from the same place. They're all in a sense versions of the same statement. They're all in some sense the same theory, which to me is really remarkable. And in fact, one of the things that has just become clear to me now is that, okay, so statistical mechanics is about when you put lots of molecules together, what do they typically do? So for example, you can have molecules that make a gas, and you say there are certain gas laws that determine the pressure and volume of the gas, and so on.

• 49:09Speaker 02

  These are typical things that happen when you just throw a bunch of molecules all together. That's what statistical mechanics is about. And people have believed that the most significant thing in statistical mechanics, the second law of thermodynamics, which is the law that says things tend to get more random. When you sort of have mechanical work that's doing things, eventually that's dissipated as heat. And once it's heat, that's kind of microscopic motion of molecules, you never get back that large-scale mechanical motion. It's turned into heat, it's random, you don't get anything back from it. So people have believed that it's sort of possible to, quote, derive the second law of thermodynamics in some kind of almost mathematical way.

• 49:51Speaker 02

  You don't really need to know physics to be able to derive that principle that things tend to, for example, go from mechanical work to heat. But people have believed that general relativity and quantum mechanics are both kind of wheel-in features of our universe. They're both things where you could have made a universe that didn't have one of those things. They're just things where it happened to 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 really interesting way. They're all derivable ultimately from this strange thing we call the ruliad, which is this limit of all possible computations.

• 50:35Speaker 02

  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 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 filtered versions of what's going on in the universe. That turns out to be one of the important things.

• 51:18Speaker 02

  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, 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. 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

• 52:02Speaker 02

  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.

• 52:13Tim Ferriss?

  How do you spell ruliad?

• 52:15Speaker 02

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

• 52:18Tim Ferriss?

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

• 52:32Speaker 02

  The first thing to think about is, there's a little bit of a story that gets to it. 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? So in other words, I was talking before about how, you know, simple computational rules, you run them, they do really complicated things. 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 me, let me go actually one other place first, which is how quantum mechanics works.

• 53:15Speaker 02

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

• 53:31Tim Ferriss?

  And by classical, you mean Newtonian in this case?

• 53:34Speaker 02

  Newtonian physics, yes.

• 53:35Tim Ferriss?

  Got it.

• 53:35Speaker 02

  Actually, relativistic physics works the same way. This is a, that's sort of the distinction between classical, as in not quantum and quantum. So this was kind of the, the dividing line is kind of around 1920, it's about 100 years old, the thing that, um. 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, this idea of path integrals and, and following many quantum paths. But 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

• 54:20Speaker 02

  and just get to say, oh, there was a certain probability that this would happen, there's a certain probability that would happen. So that's kind of 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 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 threads of time, so to speak. Different possible things that could happen in the universe. Those threads of history, they sometimes they branch because two different things could happen next.

• 55:03Speaker 02

  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 how one perceives quantum mechanics is, how does a branching mind perceive a branching universe?

• 55:46Speaker 02

  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 believe that our minds are going through a single thread of experience. 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.

• 56:30Speaker 02

  And so that process is kind of what drives the understanding of how quantum mechanics works. And actually, returning to Dick Feynman again, he always used to say, having worked his whole life on quantum mechanics, he always was very fond of saying, nobody understands quantum mechanics. And he was very, and I talked to him for ages and ages about that. And I wish he was still around because I think I can finally say, I think I actually understand quantum mechanics. It's just this idea of the branching mind perceiving the branching universe, I hadn't seen that coming at all. And it's a kind of a bizarre idea that turns out, I think, to sort of unlock how that works. But okay, so in quantum mechanics, we have all these different possible things that could happen in the universe, which

• 57:13Speaker 02

  to us get conflated together into a definite kind of path. Well, let's say we've got this model and we say we find this rule and this rule represents everything the universe does. We might imagine this day, or we've got this rule, comes out of our computer, we've done some search and we have, you know, rule number 713 is our universe. Okay, so for a long time, I was just really uncomfortable with that idea. Because let's say we're universe 713. The next question is, why did we get number 713? Why didn't we get number seven trillion, whatever? Why this one? And, you know, one of the big lessons of science over

• 57:55Speaker 02

  the last 500 years is kind of the Copernicus lesson. We're not very special. You know, we might have thought the earth was the center of the universe. We might have thought these kinds of things, but it isn't true. We're just on a random planet somewhere in this random sort of space of that makes up the universe. So even the idea that our rule is a simple rule as opposed to an incredibly complicated rule seems very anti-Copernican. And so this really bothered me for a long time. And I realized, actually, it's something even more bizarre maybe going on, which is maybe the universe is not picking any particular rule, it's running all possible rules. And so what the ruliad is, is this computational process that runs all possible rules.

• 58:39Speaker 02

  So imagine you had all possible computers and you start them off from all possible starting points and you run them all. So you might say, how could that do anything interesting? The critical point is that sometimes those computers will end up making the same thing. So in other words, two different computers might end up producing something which is the same, has the same structure. And so when you might say, well, they're just all going to do their independent things. Well, they don't do independent things because there are all these equivalences between things that they do. And so you end up building up this rich structure and that structure you build up is what we call the ruliad. It's the entangled limit of all possible computations.

• 59:19Speaker 02

  And what's really kind of interesting about it is there's only one of it and it is a necessary object. In other words, as soon as you define that you're talking about the notion of computation, as soon as you kind of define your terms, you have the ruliad. It's not the case that it's like, oh, it so happens that this feature of the world is this way. It is as inevitable as, once you've defined what integers are and what plus signs are and so on, two plus two equals four. There's no way of getting out of that. It's not something that is a random fact about the world that humans happen to have two eyes and a nose type thing, which might be seen to be sort of more coincidental.

• 1:00:03Speaker 02

  It's something that is a necessary feature from the kind of formal structure of what you've set up. So the ruliad is this kind of necessary object. And now the thing which is kind of interesting is, okay, so you have this object that is this limit of all possible computations. So how do we experience that? Well, we are also part of that object. So it's the same kind of a story as the branching mind perceiving the branching universe, except an even more abstracted version of that. It's how do we as pieces of, as elements inside this ruliad perceive the whole ruliad? So one of the things one starts talking about is this notion of what we call rulial space.

• 1:00:45Speaker 02

  Which is the space of kind of possible different views of how the universe works. So we might say, we've got one view of the universe, oh, it works this way. It follows this rule. And then some other person, alien, whatever, says, no, no, no, you're quite wrong. The universe really works according to this other rule instead. What knits all of that together is a kind of a technical fact that's been known for about a hundred years, which is this idea of universal computation. You might have thought that if you wanted to have a computer that was a word processor, you'd buy a word processing computer. You want to have a spreadsheet computer, you buy a spreadsheet computer. But the big fact that emerged in the nineteen twenties and nineteen thirties

• 1:01:25Speaker 02

  is that you can have a single sort of hardware object wasn't put to practice until the nineteen forties and fifties. But it was, you can have the single hardware object that can just be programmed to be a word processor, be a spreadsheet, whatever. And it's kind of the same thing with the universe, that you can attribute different rules to the operation of the universe, but they're interconvertible in the same way as your computer can be made to run a spreadsheet rather than a word processor, so to speak. So one of the things that I kind of like about this is there's this notion of where are you in rulial space? What kind of mode of description of what's going on in the world do you have? And you can imagine that every different mind is at a different place in rulial space.

• 1:02:09Speaker 02

  So the fact that you and I have different internal models of the world is a statement of the fact that we are some distance apart in rulial space. And so what you realize is, as we think about the universe, we have the exploration of the universe by spacecraft or whatever going out in physical space. We also have the exploration of the universe in rulial space. And that's kind of the, the different minds and different ways of describing the universe represent kind of travel through rulial space. You know, when we send out spacecraft in physical space, we're exploring different parts of the physical universe. When we come up with different ways of thinking about things and different ideas, we're kind of traveling in rulial space. And that's kind of a, a way to start representing those kinds of things.

• 1:02:55Tim Ferriss?

  I'm gonna ask a number of questions that will no doubt put me at risk of embarrassing myself, but I knew that one.

• 1:02:59Speaker 02

  I have to say one more thing before.

• 1:03:01Tim Ferriss?

  Oh, yeah.

• 1:03:01Speaker 02

  Because you were asking about languages and you were asking about different human languages. That's an example of being in different places in real space. So you can imagine two languages where the way of thinking about the world is very similar. They are kind of correspond to nearby places in real space where it's pretty easy to translate, to travel from one to the other, whereas things which are very different sort of views of the world are further away in real space. And that is just a way of perhaps conceptualizing what this thing is about.

• 1:03:32Tim Ferriss?

  When you said that, I was just thinking about gendered languages versus ungendered languages, or certain languages that don't conjugate, say, past tense, like Chinese, Mandarin, and how that affects maybe where you stand in real space. So how does a branching mind perceive a branching universe, or the branching mind perceiving the branching universe? I think as many people hear this, they imagine these multiple or infinite possibilities branching out in some form of to conjure the image of the eddy. So these changing atoms, but if you took a snapshot of the eddy, minute after minute, it would have some resemblance.

• 1:04:13Tim Ferriss?

  But there is a branching that I think for many folks listening will take place in linear time. There's some past to future to this branching. I have tried to stretch the boundaries of how I consider or define time by reading and listening to, say, Carlo Rovelli, who I think focuses a fair amount on quantum gravity. I don't know his research very well. How do you think about time? Is how humans experience or think about time just a very convenient collective delusion in terms of its linear past to future nature?

• 1:04:47Speaker 02

  So, I mean, first thing is, what is time?

• 1:04:50Tim Ferriss?

  Exactly.

• 1:04:51Speaker 02

  You know, that's something that I think we really kind of nailed in the way we think about our theory of physics. I mean, time is the inexorable progress of computation. 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. 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.

• 1:05:36Speaker 02

  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. So, for example, one place where that happens, in the simplest kind of black hole. At the center of the simplest kind of black hole is a spacetime 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.

• 1:06:20Speaker 02

  If you're doing a calculation, you do, "Oh, we're calculating these things are happening." And eventually you get to the answer. 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, because time just stopped.

• 1:06:40Speaker 02

  So, time, as far as I'm concerned, is this inexorable progress of computation. And time is, in the actual way that it manifests in the universe, has many complicated features. So, for example, in relativity and gravitation theory and so on, there are all kinds of ways in which the notion of when's at the same time as somewhere else is complicated. You know, let's say we have a Mars colony one day. And we define, you know, Earth's standard time. Okay, it's 12 noon at this point. Well, it's 20 light minutes away to Mars, for example. Do we say that the 12 noon... Is the time when the light signal from our clock that said it was 12 noon on Earth

• 1:07:25Speaker 02

  reaches Mars? Or do we try and sort of back calculate that and say, well, it's the time when it would have 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 in time? That's kind of the story of relativity theory and gravitation theory and so on. 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 trance that people can go into that's kind of a multi-way trance where they actually have multiple threads of experience that are going on at the same time.

• 1:08:09Speaker 02

  But for most of us, most of the time, it's just there's a definite thread of experience that we have.

• 1:08:15Tim Ferriss?

  What prompted that wonder or question about whether there are people?

• 1:08:20Speaker 02

  Because one of the features 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 want to be saying we've got two different answers in mind. We're going to say, we say a definite thing happened. And so, you know, for example, when people talk about making quantum computers, the

• 1:09:04Speaker 02

  big thing that one hopes for is that one can use these multiple threads of history to each run a different computation. And so then you can do all these things in parallel. Now, the big problem, and again, I seem to be mentioning Dick Feynman too much here, but he and I worked on Doesn't bother me. Back in nineteen eighty-one or so. 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 computations that I did from that just recently. He would do these calculations by hand, and I had no idea why the answers he got were right. Because it's just like you do this calculation, and it's like you could have done this or this or this. You could have made this or this assumption at this point. I don't know why that assumption is right.

• 1:09:47Speaker 02

  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. It was an interesting challenge, so to speak. But actually, even at that time, 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,

• 1:10:32Speaker 02

  then you don't get an advantage in the end. That's a difficult thing to figure out, and you know, it's something we're trying to figure out. I'm not hopeful about the true quantum advantage. I think that the formalism of quantum mechanics is super interesting. And this whole idea 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. 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.

• 1:11:16Speaker 02

  So the two ends are worthwhile. I'm not sure that the thing in the middle is so worthwhile. So that's our notion of time. Now, in terms of people's perception of time. You know, it is this process of we are undergoing these computations, our minds are undergoing these computations, 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 things sort of decaying down to heat, or the time in the expansion of the universe, 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.

• 1:11:58Speaker 02

  They're all just a sort of inexorable process of computation that's happening in the universe.

• 1:12:04Tim Ferriss?

  I'm going to use a term that is, might be frustratingly undefined, overused to the point that it's often undefined at least, but I'm going to 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 subjective experience with certain underpinnings that can be currently explained? How do you think about, if at all? This may be a terrible question.

• 1:12:31Speaker 02

  I've always sort of avoided it because I've, it's always seemed like a deeply slippery thing, but I was recently kind of confronted with, I need to apply the idea of consciousness, and here's how. In the universe, ultimately, there are all these possible computations that can happen, but our minds don't do all possible computations. Our minds are somewhat 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.

• 1:13:14Speaker 02

  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. But actually, what I've come to realize is 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 thing that consciousness, that sort of the application of consciousness to science, is this thing where it's not about everything in the universe.

• 1:13:58Speaker 02

  It's just about the particular things that are our, sort of the way that our minds perceive things. I think an exercise, you know, 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 real space where there is this set of things going on. That is our experience of the universe, and it's completely unique. And there may be some other point in real space, some other mind that is fairly close by, where we can say,

• 1:14:42Speaker 02

  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 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. And, you know, you imagine we humans, we live our lives, we remember a bunch of stuff through our lives. Eventually, it's all lost when we die. And 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 quotes "life experiences" that we humans have?

• 1:15:25Speaker 02

  You know, there is a kind of a whole sort of inner Thinking that's going on with a computer, how does that compare with us humans? There's sort of the communication with other computers, the experience of the outside world and so on. How does that compare? How can we describe that in 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 sort of inside that experiencing things from the point of view of of the machine, so to speak?

• 1:15:56Tim Ferriss?

  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?

• 1:16:37Speaker 02

  I started live streaming a bunch of working meetings that I do. And I started this about, when was it, 2017, so a few years ago. And it's really an interesting process because 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 a, an immediate feedback, you know, we'll get, if we announce some particular topic we're going to work on, we'll get some world experts in that topic often will show up because, gosh, they know they're going

• 1:17:20Speaker 02

  to be stuck using our tools and they might as well contribute 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's a little bit kind of, it helps me feel that the time I'm spending. Doing very detailed grinding away, trying to figure out how software should be designed and so on. It feels like the fact that I'm leaving some record of this feels like it makes it more meaningful. I know people have used some of our live streams for software engineering classes and things like this. And so it's, you know, it helps me make it seem more meaningful, so to speak.

• 1:18:03Speaker 02

  I think I've been doing the even more extreme version of that is that I've been doing video worklogs, which means I'm just sitting by myself and I'm working on something and I'm writing some document or something like that. And I just record it. And, you know, like last night, I probably recorded five hours of video worklogs. Yeah, 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 the thing that, and somehow it makes it feel a little bit more meaningful to me. It sort of makes me think, oh, I'm not going to goof off in that way because I'm screen recording everything here.

• 1:18:45Speaker 02

  And, okay, I admit I have a secondary screen, so I can goof off on the secondary screen. 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 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 unwind it. Same thing, by the way, for our software design meetings. The people who do project management routinely go back and look at all kinds of pieces of the meetings. What actually happened? How did we decide this?

• 1:19:29Speaker 02

  Oh, you know, a bug showed up there. Let's go carve that piece of the video out and send it to people and so on. You know, I think this thing about doing sort of 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 part of why we can do it is that we have a pretty unique, we're in a unique place and sort of technology space where it's not like, I know people who wanted to compete with us have watched live streams. It's like, good luck, you know, you just spent 35 years building all this stuff. This is not, one live stream is not going to 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,

• 1:20:12Speaker 02

  say really stupid things on these live streams, I don't care. I'm more interested in, these are 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. I don't have an internal sort of ego issue with either that process happening, or that being something that people can go back and find. And I'm sure it's possible to find all kinds of terrible, stupid things that I said in these live streams and so on. 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, all these kids are gonna be out of school. I know a bunch of stuff about science.

• 1:20:55Speaker 02

  Every so often, I'll do a Q and A, you know, once a week, I'll do a Q and 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 a hundred episodes or more now, of this hour, hour and a half on Fridays of science and technology Q and 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? And from a couple of days ago, there was a question somebody asked

• 1:21:39Speaker 02

  that made me realize some piece of physics that is relevant to our physics project that I'd never realized before. And the process of explaining it, particularly with the forced feature that 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 and As, one about history of science and technology, and the other about business, innovation, and managing life, more your kind of territory. There, again, I just find it really helpful in crystallizing my own thinking that I'm

• 1:22:20Speaker 02

  Trying to answer these questions, particularly in this real time format where I don't get to kind of say, oh, let me think about that and let me think some more about it and so on. And then I never get around to answering it. I'm kind of on the spot, having to answer something. And that's been a very useful process. I know that in terms of explaining things like science kinds of things, I'm pretty sure I can feel that I've gotten better through, you know, hundreds of hours of people ask random questions and I try and answer them. The one thing that always trips me up is when somebody asks a question and I think to myself, that's really easy. I have that one absolutely nailed. Those are the ones that I trip up on. And actually, there's a, there's a curious reason which I did realize about that, which is

• 1:23:01Speaker 02

  a lot of these things where it's like, I've understood that since I was 12 years old. So it's easy. And I realize, oh my gosh, it relies on this thing and that thing and the other thing, which yeah, I learnt when I was 12, 13 years old or something, but not everybody knows that. And I have to go explain that. And then I have to go explain this other thing that I thought was obvious. And pretty soon once one's sort of descending into this swamp of complicated stuff.

• 1:23:25Tim Ferriss?

  Let's look at maybe some of the, if there is a there, there, we'll find out. So the physiological underpinnings of productivity. So we have these physical bodies and you seem to, 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 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?

• 1:24:05Speaker 02

  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 I can sort of out energize lots of young folk who are working with me and so on. And that always, actually I get a kick out of being able to do that. So.

• 1:24:19Tim Ferriss?

  Yeah, why not?

• 1:24:20Speaker 02

  That helps add energy to the whole, to the whole picture. But no, I, I think for me, one thing is that I do things that I like to do. And for me, 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, I'm jumping into things where I really want to do this. Another strange thing I just did, I I seem to have been reliving my life fifty years ago. And the last few weeks, I decided to organize, a couple of months ago, I initiated this. A reunion for my elementary school graduating class, which was nineteen seventy two. So it's small sort of subgroup of people. And so it was kind of the fifty year follow up.

• 1:25:02Speaker 02

  It was, actually, it was, you know, I liked these people fifty years ago. I liked them fifty years later. That was nice. But I realized, you know, one of the things that's a little disappointing is some fraction of these people were like writing little blurbs about what we've been doing. And they're like, I retired, I retired, et cetera, et cetera, et cetera. They're British folk, so they had lots of witty things to say about what they were doing in their retirement. But so I was realizing, well, I'm not retired and I'm not even, I realized I'd been working more than twelve hours a day, every day, for basically all of the last fifty years. And I'm having a good time.

• 1:25:40Speaker 02

  I've been lucky enough to be able to mostly do things that sort of add energy to me rather than taking it away. 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. Back in the day before, before we realized this just didn't work, I would occasionally go shopping with my wife. Okay, long, long, right? And I would try and take my wife to science museums. My wife is a mathematician, so the science museums are 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 Shopping. Walking around shops.

• 1:26:25Speaker 02

  You know, I'm like, I feel really tired, you know, I have to, I have to kind of, you know, Getting so sleepy. Et cetera, et cetera. I think the effect that I'm doing things I really want to be doing is an important effect. Now, having said that, I did discover when I was kind of like forty years old, hey, you should do some exercise. And that helped for me, I think, add a bunch of energy. I mean, I've walked more than ten thousand steps every single day for the last three years. And that's kind of just one of my constraints, even if I'm traveling or this or that or the other. The people who schedule stuff for me, I gotta walk ten thousand steps. If that's around an airport on phone calls and things, so be it. But I'm just gonna, that's a constraint on my life, so to speak.

• 1:27:08Speaker 02

  And I think that has had a positive effect. For me, it's kind of been bizarre because, you know, when I was younger, I wasn't in terribly good shape. I'm in better shape now. And so for me, I don't yet notice that I'm aging because I'm actually better off in many ways than I was when I was younger.

• 1:27:26Tim Ferriss?

  Yeah, your mitochondria are getting younger, rejuvenating.

• 1:27:31Speaker 02

  No, I mean, you know, another thing about that and about sort of the, the, the management of one's life and so on. I mean, I've been fortunate enough that often you'll do something and maybe you do something really cool when you're twenty five years old. And then kind of it's all downhill from there. It's hard to get motivated. And I've been lucky enough that, well, for example, this physics project that just sort of arrived three years ago. That was something I didn't really expect. It's a rejuvenating kind of thing. And it's just added a lot of energy, you know, it's just so many things to think about and so on. That's one thing. I think that I sleep as close to eight hours as I can. I don't try and game it of saying I'm going to try and shave off extra time and so on. I'm very habitual in terms of when I, when I go to sleep, when I wake up.

• 1:28:16Speaker 02

  Things I eat tend to be habitual, they may not be optimal, but they're habitual at least. You know, I've found that for me, I try and sort of optimize away all those aspects of my life that I really don't care about, so to speak. That I don't keep those as sort of simple and not having to think about them as possible. So that I can spend my thinking.

• 1:28:38Speaker 02

  Effort on things where I really want to think about these things and really want to spend my time on them. I've been fortunate enough that I've, for whatever reason, the mitochondria are still alive and kicking and providing good energy. I think it's mostly just doing things that I want to do. And also, you know, I tend to organize it so that, okay, there are things that I save up for. I'm gonna do this if I'm feeling tired. And sometimes I have another set of things, I'm gonna do this if I get sick. And I've had a whole bunch of those, and I've only been sick once in the last three years. So I've got this big pent-up supply of things to do when I'm sick.

• 1:29:15Tim Ferriss?

  Now, are those just low-energy, low-interest tasks that nonetheless kind of have to get done, like, talk to my accountant about XYZ, whatever?

• 1:29:25Speaker 02

  Well, I'm usually talking to other people. They're usually organizing information, all kinds of things.

• 1:29:30Tim Ferriss?

  I see, I see.

• 1:29:31Speaker 02

  Or sometimes they're, watch this video that I've been meaning to watch and have never had time to do. But I did learn, okay, so this is one not-yet-very-scientific hack fact, 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, I think, all the times I've gotten sick. It's always upper respiratory, you know, things. 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, oh, I went out and I met a bunch of people, or was it whatever? And the one correlation, and I haven't been completely scientific about this, the one

• 1:30:15Speaker 02

  correlation was, it was often two days after I was on a flight, on a plane. Okay? And in a few cases, that was not a commercial plane, that was a private plane. Without a lot of other people on it. And so it's kind of interesting. And so then I asked my medical research friends and so on. Hey, what's going on here? And here's the theory. The theory would be a big part of upper respiratory defense, so to speak, is the innate immune system operating like in one's nose and so on. And if you get your nose dried out and so on, from being in the dry air and on planes and things like that, your little innate immune system doesn't stand a chance.

• 1:30:59Speaker 02

  So my hack has been take things like wheat germ and so on. 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 of trips I've done. So far, I haven't gotten sick.

• 1:31:15Tim Ferriss?

  So far, so good. Well, it also makes me think of ways that you could not necessarily humidify, but maintain the moisture integrity of the sinus lining as well with a spray or something like that.

• 1:31:30Speaker 02

  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.

• 1:31:38Tim Ferriss?

  Try to keep the nose well hydrated.

• 1:31:41Speaker 02

  Right. It's kind of a strange thing, you know, you're on some flight going somewhere and you're like continually tipping things into your nose or whatever. You know, one of the things I found 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. 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 that I knew I had to do. I do the same thing when I'm driving places. I always maintain a call while driving list. You know, phone calls that are slightly more, you know, I've got to do this sometime. I don't need to be in front of a computer. You know, this is something I can do then.

• 1:32:23Speaker 02

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

• 1:32:46Tim Ferriss?

  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.

• 1:32:57Tim Ferriss?

  Data. I think that I take a lot of notes, but you mentioned at the top of this conversation, a quarter million pages, something along those lines. It's just incredible.

• 1:33:08Speaker 02

  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.

• 1:33:15Tim Ferriss?

  See, a lot of stuff over a long period of time. And I would love to, at some point, do a round two. I'm sure 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? Anything at all in terms of closing remarks, comments, any grievances you'd like to air publicly? Anything at all?

• 1:33:41Speaker 02

  Makes me want to ask you for a bunch of personal productivity hacks and so on. And the what am I missing type thing? Because that's

• 1:33:48Tim Ferriss?

  Oh, boy.

• 1:33:49Speaker 02

  One slowly accumulates these things. And I find I'll try things and probably two thirds of the things I try work and one third don't. And it's kind of like, keep trying them. I think, no, that's, we've covered all kinds of things.

• 1:34:04Tim Ferriss?

  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 gross omission, I will be sure to send it to you. People can find you on Twitter, Steven, that's a P H, Steven underscore Wolfram, then Facebook slash Steven Wolfram, LinkedIn.com, also your name, and then the website, stevenwolfram.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?

• 1:34:49Speaker 02

  The stuff I write ends up in writings.stevenholfman.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 as we just launched our Wolfram Institute, which is an attempted productivity hack. My company, which I started now 36 years ago, is kind of my machine for turning ideas that I have into real things. 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,

• 1:35:34Speaker 02

  what's the machine that does that? I've sort of carved off a bit of resources from the company and so on to do it. But we 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 there'll be more live streaming of science in action and so on there. So those are a few things. You know, I have to plug my life work. My life work is building Wolfram Language and Wolfram Alpha and Mathematica and so on, which are all part of the same idea of make the world computational. And I suppose the one pitch I would make is what we've built,

• 1:36:18Speaker 02

  I can inexorably see is an artifact from the future. You know, 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 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 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'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 learning computational language is a superpower. You get to do that and then you can do all kinds of, all kinds of magic things with it.

• 1:37:03Speaker 02

  Learn that superpower. More people should do it. And it's one of these things where you can kind of see in the world. When things involve big ideas, there's a certain inexorable slowness to the way that they get adopted. And there are always some number of early adopters who are the ones that run out in front. So my parting pitch would be, if you don't understand computational language and Wolfram language and so on, try to understand it. Because it is for me, 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

• 1:37:45Speaker 02

  of tower of technology that we built around that. That's my kind of parting sort of ultimate productivity hack.

• 1:37:52Tim Ferriss?

  Wonderful. And for everybody listening, Mathematica, Wolfram Alpha, Wolfram Language, we will link to all of these things in the show notes at tim.blog/podcast. You can just search Wolfram, W O L F R A M, and that will pop right up. Stephen, I really enjoy learning from you because you're not only an incredible thinker, technologist, I'm sure there are many multi hyphenate labels I could apply, but you're a very gifted communicator and teacher. So the practical impact of what you do is not just manifested through the products used by millions of people and that will be used in some form or another

• 1:38:31Tim Ferriss?

  by many, many millions more, but also in the principled and systematic thinking that you can share and do share with people, including kids, including with non-technical muggles who are nonetheless very curious, like myself, and no doubt with many, many millions of listeners on this podcast. So thank you. I really, really appreciate the time you you take to do what you do and the time you've also taken to have this conversation. So

• 1:38:59Speaker 02

  Thank you.

• 1:39:00Tim Ferriss?

  Thank you very much. And to everybody listening, I'll plug it one more time. You can go to tim.blog/podcast for the show notes for all things we've mentioned in this episode and in all episodes. And until next time, be a little bit kinder than is necessary. Be very curious. Definitely paddle early for the superpowers that you can get ahead of in terms of early adoption, like those that Stephen was mentioning. And thank you for tuning in. Hey guys, this is Tim again. Just one more thing before you take off, and that is Five Bullet Friday. Would you enjoy getting a short email from me every Friday that provides a little fun before the weekend? Between 1.5 and 2 million people subscribe to my free newsletter,

• 1:39:43Tim Ferriss?

  my super short newsletter called Five Bullet Friday. Easy to sign up, easy to cancel. It is basically a half-page that I send out every Friday to share the coolest things I've found or discovered, or have started exploring over that week. It's kind of like my diary of cool things. It often includes articles I'm reading, books I'm reading, albums perhaps, gadgets, gizmos, all sorts of tech tricks and so on that get sent to me by my friends, including a lot of podcast guests. And these strange esoteric things end up in my field, and then I test them, and then I share them with you. So if that sounds fun, again, it's very short, a little tiny bite of goodness before you head off for the weekend, something to think about.

• 1:40:26Tim Ferriss?

  If you'd like to try it out, just go to tim.blog/friday. Type that into your browser, tim.blog/friday. Drop in your email and you'll get the very next one. Thanks for listening. This episode is brought to you by Eight Sleep. My god, am I in love with Eight Sleep. Good sleep is the ultimate game changer. More than 30% of Americans struggle with sleep, and I'm a member of that sad group. Temperature is one of the main causes of poor sleep, and heat has always been my nemesis. I've suffered for decades tossing and turning, throwing blankets off, putting them back on, and repeating ad nauseam. But now, I am falling asleep in record time, faster than ever. Why? Because I'm using a simple device called the Pod Pro Cover by Eight Sleep.

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• 1:43:03Tim Ferriss?

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• 1:43:48Tim Ferriss?

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