#209 – Luís and João Batalha: Fermat’s Library and the Art of Studying Papers

Luis and Joao Batalha are co-founders of Fermat’s Library. Please support this podcast by checking out our sponsors: – Skiff: https://skiff.org/lex to get early access – SimpliSafe: https://simplisafe.com/lex and use code LEX to get a free security camera – Indeed: https://indeed.com/lex to get $75 credit – NetSuite: http://netsuite.com/lex to get free product tour – Four Sigmatic: https://foursigmatic.com/lex and use code LexPod to get up to 60% off EPISODE LINKS: Fermat’s Library Twitter: https://twitter.com/fermatslibrary Luis’s Twitter: https://twitter.com/luismbat Joao’s Twitter: https://twitter.com/joao_batalha Fermat’s Library Website: https://fermatslibrary.com PODCAST INFO: Podcast website: https://lexfridman.com/podcast Apple Podcasts: https://apple.co/2lwqZIr Spotify: https://spoti.fi/2nEwCF8 RSS: https://lexfridman.com/feed/podcast/ YouTube Full Episodes: https://youtube.com/lexfridman YouTube Clips: https://youtube.com/lexclips SUPPORT & CONNECT: – Check out the sponsors above, it’s the best way to support this podcast – Support on Patreon: https://www.patreon.com/lexfridman – Twitter: https://twitter.com/lexfridman – Instagram: https://www.instagram.com/lexfridman – LinkedIn: https://www.linkedin.com/in/lexfridman – Facebook: https://www.facebook.com/lexfridman – Medium: https://medium.com/@lexfridman OUTLINE: Here’s the timestamps for the episode. On some podcast players you should be able to click the timestamp to jump to that time. (00:00) – Introduction (10:18) – Backstories to research papers (25:09) – Fermat’s Library (45:10) – Scientific publishing (1:08:50) – How to read a paper (1:14:44) – Taking good notes (1:23:23) – Favorite papers on Fermat’s Library (2:04:14) – Fermat’s Library on Twitter (2:13:46) – What it takes to build a successful startup (2:22:43) – Game of Thrones (2:25:30) – Realism in science fiction movies (2:31:29) – Greatest soccer player of all time (2:54:18) – Advice for young people

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

• 0:00Lex Fridman?

  The following is a conversation with Luis and Jawao Batala, brothers and co-founders of Fermat's Library, which is an incredible platform for annotating papers. As they write on the Fermat's Library website, quote, "Justice Pierre de Fermat scribbled his famous last theorem in the margins. Professional scientists, academics, and citizen scientists can annotate equations, figures, ideas, and write in the margins." Fermat's Library is also a really good Twitter account to follow. I highly recommend it. They post little visual factoids and explorations that reveal the beauty of mathematics. I love it.

• 0:40Lex Fridman?

  Quick mention of our sponsors: Skiff, SimpliSafe, Indeed, NetSuite, and Four Sigmatic. Check them out in the description to support this podcast. As a side note, let me say a few words about the dissemination of scientific ideas. I believe that all scientific articles should be freely accessible to the public. They currently are not. In one analysis, I saw more than 70% of published research articles are behind a paywall. In case you don't know, the funders of the research, whether that's government or industry, aren't the ones putting up the paywall. The journals are the ones putting up the paywall,

• 1:20Lex Fridman?

  while using unpaid labor from researchers for the peer review process. Where is all that money from the paywall going? In this digital age, the costs here should be minimal. This cost can easily be covered through donation, advertisement, or public funding of science. The benefit versus the cost of all papers being free to read is obvious. And the fact that they're not free goes against everything science should stand for, which is the free dissemination of ideas that educate and inspire. Science cannot be a gated institution. The more people can freely learn and collaborate on ideas, the more problems we can solve in the world together,

• 2:02Lex Fridman?

  and the faster we can drive old ideas out and bring new, better ideas in. Science is beautiful and powerful, and its dissemination in this digital age should be free.

• 2:16Lex Fridman?

  As usual, I'll do a few minutes of ads now. I try to make these interesting, but I give you timestamps. So if you skip, please still check out the sponsors by clicking the links in the description. It is the best way to support this podcast. I'm very picky with the sponsors we take on. So hopefully, if you buy their stuff, you'll find value in it, just as I have. This show is brought to you by Skiff, a new sponsor, an amazing sponsor. I really love these guys. I love the idea. I love the implementation. What Signal is to messaging, Skiff is to document writing and collaboration. It's like Google Docs, but with a lot more security features. I should confess that I'm very picky about the tools I use for productivity in general,

• 2:59Lex Fridman?

  but for creating documents, for creating notes. I'm a big user of Google Docs. I probably have over 1,000 documents on there. I use also Evernote, Notion, Google Keep. I love that for note taking. Anyway, I bring that up because I'm really picky on the usability front of these tools. And that's the magic of Skiff. Not only is it secure, there's a lot of interesting things I could talk about for a long time, how they implemented, super interesting. But the actual writing and collaboration experience in it is just amazing. In my opinion, these are big words, it is better than Google Docs. But back to the security side of things.

• 3:40Lex Fridman?

  It's an end-to-end encrypted and decentralized collaboration platform built for privacy from the ground up. On Skiff, only you can decrypt the data. No one, not even Skiff, can ever see it. They are offering listeners of this podcast. This is truly special. They're offering you early access to their platform. You get to skip their over 60,000 person waiting list. Sign up for Skiff's beta at skiff.org/lex. By the way, that's spelled S-K-I-F-F. I'm actually thinking of doing a fun collaborative document with a free-for-all to all the listeners of this podcast. So one document that anyone could edit on Skiff. That'd be pretty cool. What could possibly go wrong?

• 4:25Lex Fridman?

  Anyway, go to skiff.org/lex to sign up for the early access. This show is also brought to you by SimpliSafe, a home security company designed by Chad and Eleanor Lawrence to be simple and effective. I think the reason they want me to bring up the founder names is to show that there's actual real people with a real need, a real problem they want to solve and they want to solve it. I love companies like that. See a problem in the world and actually come up with a solution. It's not about making money first. It's about solving the problem. And then you can really feel the sort of love for the design, for the features, for the implementation,

• 5:07Lex Fridman?

  for the whole thing when it's done like that. It takes 30 minutes to set up, super easy. I set it up in two places now. You can customize the system for your needs on simplisafe.com/lex. I think security has two components. One, it should be super easy to use, set up, operate. And two, it should be obviously reliable as the security system itself. Now, obviously, SimpliSafe works as a security system, but the thing that makes it truly special, in my opinion, is just how easy it is to get the whole thing working. Anyway, go to simplisafe.com/lex to customize your system and get a free security camera plus the 60-day risk-free trial. Again, that's simplisafe.com/lex.

• 5:50Lex Fridman?

  This episode is brought to you by Indeed, a hiring website. I've used them as part of many hiring efforts I've done for the teams I've led. They have tools like Indeed Instant Match, giving you quality candidates whose resumes on Indeed fit your job description immediately. On the podcast and the video side of things, I've actually been trying to hire a few different kinds of people to build up a team of people I can sort of work side to side with. Obviously, everyone should be really good at getting the thing they're supposed to do done, but also the personality, the flavor they bring to the team is really important, whether it's the wild, crazy ones or the quiet, hardworking ones. I mean, having the full set of flavors on a team, I think, especially when

• 6:34Lex Fridman?

  you're doing like creative type of things, which is what a podcast or any kind of video on YouTube is, that's essential, that variety. But in order to select that good variety, you have to have a nice pool of candidates. And that's what Indeed is really good at doing. For the basic job that needs to get done, it'll give you a good pool of candidates. Right now, get a free $75 sponsored job credit to upgrade your job post at indeed.com/lex. Get it at indeed.com/lex. Offer is valid through September 30. Terms and conditions apply. Join 3 million businesses that use Indeed by going to indeed.com/lex. This show is also brought to you by NetSuite. They basically do a bunch of stuff that QuickBooks can do and more.

• 7:19Lex Fridman?

  Plus, they do the stuff QuickBooks does and do it better. NetSuite allows you to manage financials, HR, inventory, e-commerce, and many more business-related details, all in one place. I tend to think of a company as a single living organism. And it's fascinating to think of it in that way, like a complex living organism with different parts and what are each of those parts responsible for? And what is the essential parts that make the organism what it is? And what are the sort of administrative parts that do the bulk of the working? It's like the DevOps or the people that run the compute infrastructure for the living organism. It's really important to have that infrastructure in place and work well.

• 8:04Lex Fridman?

  And to do so, I think tools can really help. That's where NetSuite can really help. I should also say that special financing is back. NetSuite is offering a one-of-a-kind financing program only for those ready to sign up today. Head to netsuite.com/lex. That's special financing and netsuite.com/lex. netsuite.com/lex. This show is sponsored by Four Sigmatic, the maker of delicious mushroom coffee and plant-based protein. The coffee, in case you're wondering, does not taste like mushrooms. It is delicious. In fact, earlier today, I had an emergency when I woke up in the morning, all happy with the sunshine shining through the windows, the birds chirping.

• 8:49Lex Fridman?

  Actually, I don't remember if the birds are chirping. It's Texas, so it's super hot. Probably the birds were sweating and exhausted. But the point is, I wanted to make some coffee and I realized I was out of coffee. And that was an emergency. That was a big problem. I didn't have any more Four Sigmatic. That's my failure, so I had to order more. But the level of disappointment I felt was a reflection of how important coffee is in my life, how important that ritual of coffee is. It just starts the day right. It gives you that little warm kick that's a launching pad into the first few hours of deep work that I truly, truly appreciate. I mean, that's when my mind is sharpest, it can go the deepest. I just love it.

• 9:33Lex Fridman?

  And I somehow, I think a lot of us do, connect coffee with that. So if you enjoy coffee like I do, you should definitely try out Four Sigmatic. It's one I really enjoy. Anyway, get up to 40% off and free shipping on mushroom coffee bundles if you go to foursigmatic.com/lex. That's foursigmatic.com/lex. This is the Lex Fridman Podcast, and here is my conversation with Louise and Jawao Batawa.

• 10:18Lex Fridman?

  Louise, you suggested an interesting idea. Imagine if most papers had a backstory section, the same way that they have an abstract. So knowing more about how the authors ended up working on a paper can be extremely insightful. And then you went on to give a backstory for the Feynman QED paper. This is all in a tweet, by the way. We're doing tweet analysis today. How much of the human backstory do you think is important in understanding the idea itself that's presented in the paper or in general?

• 10:50Speaker 01

  I think this gives way more context to the work of scientists. I think people, a lot of people have this almost kind of romantic misconception that the way a lot of scientists work is almost as the sum of eureka moments where all of the sudden they sit down and start writing two papers in a row and the papers are usually isolated. And when you actually look at it, it's the papers are, you know, chapters of a way more complex. Story and the Feynman Q E D paper is a good example. So Feynman was actually going through a pretty dark phase before writing that paper. He was he lost enthusiasm with physics and doing physics problems. And there was one time when he was in the cafeteria of Cornell.

• 11:35Speaker 01

  And he saw a guy that was throwing plates in the air. And he noticed that there was when the plate was in the air, there were two movements there. The plate was wobbling, but he also noticed that the Cornell symbol was rotating. And he was able to figure out the equations of motions, the equations of motions of those plates. And that led him to kind of think a little bit about electron orbits in relativity, which led to the paper of about quantum electrodynamics. So that kind of reignited his interest in physics and ended up publishing the paper that led to the his Nobel Prize, basically. And I think it's it's there are a lot of really interesting backstories about papers

• 12:20Speaker 01

  that readers never get to know. For instance, we did a couple of months ago, an AMA around a paper, a pretty famous paper, the Gans paper with Ian Goodfellow. And so we did an AMA where everyone was could ask questions about the paper. And Ian was responding to those questions. And he was also he was also telling the story of how he got the idea for that paper in a bar. So there was also an interesting backstory. I also read a book by Cedric Vilani. Cedric Vilani is this mathematician, the Fields Medalist. And in his book, he tries to explain how he got from like a PhD student to the Fields Medal.

• 13:02Speaker 01

  And he tries to be as descriptive as possible about every single step how he got to the Fields Medal. And it's interesting also to see just the amount of random interactions and discussions with other researchers, sometimes over coffee and how it led to like fundamental breakthroughs and some of his most important papers. So I think it's super interesting to have that context of the backstory.

• 13:24Lex Fridman?

  Well, the Ian Goodfellow story is kind of interesting. And perhaps that's true for Feynman as well. I don't know if it's romanticizing the thing, but it seems like just a few little insights and a little bit of work does most of the leap required. Do you have a sense that for a lot of the stuff you've looked at, just looking back through history? It wasn't necessarily the grind of like Andrew Wiles with the Fermat's Last Theorem, for example. It was more like a brilliant moment of insight. In fact, Ian Goodfellow has a kind of sadness to him almost in that at that time in machine learning, like at that time, especially in for GANs, you could code something up really

• 14:08Lex Fridman?

  quickly on a single machine and almost do the invention, go from idea to experimental validation in like a single night, a single person could do it. And now there's kind of a sadness that a lot of the breakthroughs you might have in machine learning kind of require large scale experiments. So it was almost like the early days. So I wonder how many low hanging fruit there are in science and mathematics and even engineering where it's like you could do that little experiment quickly, like you have an insight in a bar. Why is it always a bar? But you have an insight at a bar and then just implement and the world changes.

• 14:48Speaker 01

  It's a good point. I think it also depends a lot on the maturity of the field. When you look at a field like mathematics, like it's a pretty mature field. A field like machine learning, it's it's growing pretty fast and it's actually pretty interesting. I looked up like the number of new papers on archive with the keyword machine learning and like 50% of those papers have been published on in the last 12 months. So you can see just the sense.

• 15:19Lex Fridman?

  Five zero?

• 15:20Speaker 01

  Five zero, 50%. So you can see the magnitude of growth in that field. And so I think like as fields mature, like those types of moments, I think naturally are less frequent. It's just a consequence of.

• 15:36Speaker 02

  That. The other point that is interesting about the backstory is that it can really make it more memorable in a way. And by making it more memorable, it's it kind of sediments the knowledge more in your mind. I remember also reading the sort of the backstory to to Dijkstra's shortest path algorithm, right, where he came up with it essentially while he was sitting down at a coffee shop in Amsterdam. And he and he came up with that algorithm over 20 minutes. And one interesting aspect is that he didn't have any pen or paper at the time. And so you had to do it all in his mind. And so there's only so much complexity that he can handle if you're just thinking about it in your mind.

• 16:16Speaker 02

  And that like when you think about the simplicity of Dijkstra's shortest path finding algorithm, it's, you know, knowing that backstory helps sediment that algorithm in your mind so that you don't forget about it as easily.

• 16:29Lex Fridman?

  It might be from you that I saw a meme about Dijkstra. It's like he's trying to solve it and he comes up with some kind of random path. And then it's like, my parents aren't home. And then he does, he figures out the algorithm for the shortest path. It's tried through words to convey memes, but it's hilarious. I don't know if it's in post that we construct stories that romanticize it. Apparently with Newton, there was no apple. Especially when you're working on problems that have a physical manifestation or a visual manifestation, it feels like the world could be an inspiration to you.

• 17:10Lex Fridman?

  So it doesn't have to be completely in on paper. Like you could be sitting at a bar and all of a sudden see something and a pattern will will spark another pattern and you can visualize it and rethink a problem in a particular way. Of course, you can also load the math that you have on paper and always carry that with you. So when you show up to the bar, some little inspiration could be the thing that changes it. Is there any other people? Almost on the human side, whether it's physics with Feynman, Dirac, Einstein, or computer science, Turing, anybody else? Any backstories that you remember that jump out? Because I'm also referring to not necessarily these stories where something magical happens,

• 17:55Lex Fridman?

  but these are personalities. They have big egos. Some of them are super friendly. Some of them are like self-obsessed. Some of them have anger issues. Some of them, how do I describe Feynman? But he appears to have appreciation of the beautiful in all its forms. He has a wit and a cleverness and a humor about him. So does that come into play in terms of the construction of the science?

• 18:21Speaker 02

  I think you brought up Newton. Newton is a good example also to think about his backstory because, you know, there's a certain backstory of Newton that people always talk about. But then there's a whole another aspect of him that is also a big part of the person that he was, but you know, he was really into alchemy, right? And that he spent a lot of time thinking about that and writing about it. And he took it very seriously. He was really into Bible's interpretation, trying to predict things based on the Bible. And so there's also a whole backstory then. And of course, you need to look at it in the context and the time that when Newton lived, but it adds to his personality.

• 19:02Speaker 02

  And it's important to also understand those aspects that maybe, you know, people are not as proud to teach to little kids, but it's important. It was part of who he was and maybe without those, who knows what he would have done otherwise, so.

• 19:17Lex Fridman?

  Well, the cool thing about alchemy, I don't know how it was viewed at the time, but it almost like to me symbolizes dreaming of the impossible. Like, most of the breakthrough ideas kind of seem impossible until they're actually done. It's like achieving human flight. It's not completely obvious to me that alchemy is impossible or like putting myself in the mindset of the time. And perhaps even still, everything that, you know, some of the most incredible breakthroughs would seem impossible. And I wonder the value of believing, almost like focusing and dreaming of the impossible

• 20:01Lex Fridman?

  such that it is actually is possible in your mind and that in itself manifests. Whether the accomplishing that goal or making progress in some unexpected direction. So alchemy almost symbolizes that for me.

• 20:14Speaker 02

  I distinctly remember having the same thought of thinking, you know, when I learned about atoms and that they have protons and electrons, I was like, okay, to make gold, you just take whatever has an atomic weight below it and then shove another proton in there and then you have a bunch of gold. So like, why don't people do that? It seemed like, conceptually, it's like, you know, this sounds feasible. You might be able to do it.

• 20:35Lex Fridman?

  And you can, actually, it's just very, very expensive.

• 20:37Speaker 02

  Yeah, yeah, exactly. Exactly. So in a sense, we do have alchemy and maybe even back then, it wasn't as crazy that he was so into it. But people just don't like to talk about that as much. Yeah. But Newton in general was a very interesting fellow.

• 20:52Lex Fridman?

  Anybody else come to mind? In terms of people that inspire you, in terms of people that you just are happy that they have once or still exist on this earth?

• 21:05Speaker 02

  I think, I mean, Freeman Dyson for me.

• 21:09Speaker 01

  Yeah, Freeman Dyson was, was, I've had a chance to actually exchange a couple of emails with him. He was probably one of the most humble scientists that I've ever met. And that had a big impact on me. We were trying, we're actually trying to convince him to annotate a paper on Fermat's library. And I sent him an email asking him if he could annotate a paper. And his response was something like, I have very limited knowledge. I just know a couple of things about certain fields. I'm not sure if I'm qualified to do that. That was his first response. And this was someone that should have won an Nobel Prize and worked on a bunch of different fields, did some really, really great work.

• 21:52Speaker 01

  And then just the interactions that I had with him, every time I asked him a couple of questions about his papers, and he always responded saying, I'm not here to answer your questions. I just want to open more questions. And so that had a big impact on me. It was like, just an example of an extremely humble, yet accomplished.

• 22:16Speaker 01

  Scientist and Feynman was also a big, big inspiration in the sense that he was able to be, you know, again, extremely talented and, and scientist, but at the same time, socially, he was able to, to, he was also really smart from a social perspective and he was able to interact with people. He was also a really good teacher and was also to did awesome work in terms of explaining physics to, to the masses and motivating and getting people interested in physics. And that for me was, was also big inspiration.

• 22:51Lex Fridman?

  Yeah, I like the childlike curiosity of some of those folks like you mentioned Freeman. I've Daniel Kahneman, I got a chance to meet and interact with some, some of these truly special scientists. What makes them special is that even in older age, there's still like, there's still that fire of childlike curiosity that burns. And some of that is like not taking yourself so seriously that you think you've figured it all out, but almost like thinking that you don't know much of it. And that's like step one in having a great conversation or collaboration or exploring a scientific question. It's cool

• 23:31Lex Fridman?

  how the very thing that probably earned people the Nobel Prize or, or work that's seminal in some way is, is the very thing that still burns even after they've won the prize. It's cool to see and they're rare humans, it seems.

• 23:48Speaker 01

  And to that point, I remember like the last email that I sent to Freeman Dyson was like in his last birthday. He was really into number theory and primes. So what I did is I took like a photo of him, picture, and then I turned that into like a giant prime number. So I converted the picture into a bunch of one and eights and then I moved some numbers around until it was a prime. And then I sent him that.

• 24:13Lex Fridman?

  Also, the visual, like it still looked like the picture.

• 24:16Speaker 02

  It's.

• 24:16Lex Fridman?

  It was made up of a prime. That's tricky to do.

• 24:18Speaker 02

  It's.

• 24:19Lex Fridman?

  That's hard to do.

• 24:20Speaker 02

  It looks harder than it actually is. So the way you do it is like you convert the darker regions into eights and the lighter regions in ones. And then there's.

• 24:30Lex Fridman?

  And just keep flipping.

• 24:31Speaker 02

  Yeah.

• 24:31Lex Fridman?

  Numbers.

• 24:32Speaker 02

  Until. But there's like some primality tests that are cheaper from a computational standpoint.

• 24:37Lex Fridman?

  Yes.

• 24:38Speaker 02

  But what it tells you is it excludes numbers that are not prime. Then you end up with a set of numbers that you don't know if they are prime or not. And then you run the full primality test on that. So you just have to keep iterating on that. And it was, it was, it's funny because when you got the picture, it was like, how did you do that? It was super curious to, and then we got into the details. And again, this was, it was already 90, I think 92 or something. And that curiosity was still there.

• 25:06Speaker 02

  So you can really see that in some of these scientists.

• 25:10Lex Fridman?

  So could we talk about Fermat's Library?

• 25:13Speaker 02

  Yeah, absolutely.

• 25:14Lex Fridman?

  What is it? What's the main goal? What's the dream?

• 25:18Speaker 02

  It is a platform for annotating papers in its essence, right? And so academic papers can be one of the densest forms of content out there. And generally, pretty hard to understand at times. And the idea is that you can make them more accessible and easier to understand by adding these rich annotations to the side, right? And so we can just imagine a PDF view on your browser and then you have annotations on each side. And then when you click on them, a sidebar expands and then you have annotations that support LaTeX and Markdown. And so the idea is that you can, say, explain a tougher part of a paper where there's a step that is not completely obvious, or you can add more context to it.

• 26:00Speaker 02

  And then over time, papers can become easier and easier to understand and can evolve in a way. But it really came from myself, Luigi, and two other friends. We've been, we've had this, this long running habit of kind of running a journal club amongst us. We come from different backgrounds, right? I studied CS, we studied physics. And so we'd read papers and present them to each other. And then we tried to bring some of that online. And that's, that's, that's when we decided to, to, to build Fermat's Library. Then over time, it kind of grew into, into something with, with a broader goal.

• 26:42Speaker 02

  And really, what we're trying to do is trying to help move science in the right direction. That's really the ultimate goal and where we want to take it now.

• 26:51Lex Fridman?

  So there's a lot to be said. So first of all, for people who haven't seen it, the interface is exceptionally well done. That's like execution is really important here.

• 27:01Speaker 02

  Absolutely.

• 27:02Lex Fridman?

  The other thing is just to mention for a large number of people, apparently, which is new to me, don't know what LaTeX is. So it's spelled like latex, so be careful Googling it if you haven't before. It's a, sorry, I don't even know the correct terminology.

• 27:20Speaker 02

  Typesetting language?

• 27:21Lex Fridman?

  It's a typesetting language where it's you're basically program, writing a program that then generates something that looks, from a typography perspective, beautiful.

• 27:33Speaker 02

  Absolutely.

• 27:34Lex Fridman?

  And so a lot of academics use it to write papers. I think there's like a bunch of communities that use it to write papers. I would say it's mathematics, physics, computer science.

• 27:46Speaker 02

  Yeah, that's, yeah.

• 27:47Lex Fridman?

  That's it. Because I'm collaborating currently on a paper with two neuroscientists from Stanford.

• 27:53Speaker 02

  And they don't know what?

• 27:56Lex Fridman?

  So I'm using Microsoft Word and Mendeley and like all of those kinds of things. And it's, and I'm being very zen like about, about the whole process, but it's fascinating. It's a little heartbreaking, actually, because it actually, it's funny to say, but, and we'll talk about Open Science, actually, the bigger mission behind it from our libraries, like really opening up the world of science to everybody, is these silly two facts of like one community uses LaTeX and another uses Word is actually a barrier between them. That's like, it's like boring and practical in a sense, but it makes it very difficult to collaborate.

• 28:42Speaker 01

  Just on that, I think there are some people that should have received like a Nobel Prize, but will never get it. And I think one of those is like Donald Knuth because of tech and LaTeX. Because it had a huge impact in terms of like just making it easier for researchers to put their content out there, like making it uniform as much as possible.

• 29:03Lex Fridman?

  Oh, you mean like a Nobel Peace Prize?

• 29:06Speaker 01

  Maybe a Nobel Peace Prize. Maybe a Nobel Peace Prize. Yeah, I think so.

• 29:13Lex Fridman?

  I mean, he at a very young age got the Turing Award for his work in algorithms and so on. So like an incredibly, I think it's in, it might be even the 60s, but I think it's the 70s. So when he was really young. And then he went on to do like incredible work with his book. And yeah, with tech that people don't know.

• 29:32Speaker 01

  And going back just on the reason why we ended up, because I think this is interesting. The reason why we ended up using the name Fermat's Library, this was because of Fermat's Last Theorem. And Fermat's Last Theorem is actually a funny story. So Pierre de Fermat, he was like a lawyer. And he wrote like on a book that he had a solution to Fermat's Last Theorem, but that didn't fit the margin of that book. And so Fermat's Last Theorem basically states that there is no solution. If you have integers a, b, and c, there's no solution to a to the power of n plus b to the power of n equals to c to the power of n if n is bigger than 2.

• 30:15Speaker 01

  So there's no solutions. And he said that, and that problem remained open for almost 300 years, I believe. And a lot of the most famous mathematicians tried to tackle that problem. No one was able to figure that out until Andrew Wiles, I think was in the 90s, was able to publish the solution, which was, I believe, almost 300 pages long. And so it's kind of an anecdote that, you know, there's a lot of knowledge and insights that can be trapped in the margins, and there's a lot of potential energy that you can release. If you actually spend some time trying to digest that.

• 30:57Speaker 01

  And that was the the the origin story for for the name.

• 31:01Lex Fridman?

  Yes, you can share the contents of the margins with the world.

• 31:04Speaker 01

  Exactly.

• 31:04Lex Fridman?

  That could inspire a solution or a communication that then leads to a solution.

• 31:09Speaker 01

  But and and if you think about papers, like papers are, as as Jerome was saying, probably one of the densest pieces of of text that any human can read. And you have these researchers, like some of the brightest minds in in these fields, working on like new discoveries and publishing these work on journals that are imposing them restrictions in terms of the number of pages that they can have to explain a new scientific breakthrough. So at the end of the day, papers are not optimized for clarity and for a proper explanation of of that content, because there are so many restrictions. So there's, as as I mentioned, there's a lot of potential energy that can be freed if you actually try to digest a lot of the contents of of papers.

• 31:53Lex Fridman?

  Can you explain some of the other things, so margins, librarian, journal club?

• 31:59Speaker 01

  So Journal Club is what a lot of people know us for, where we, every week, we release an annotated paper and in all sorts of different fields, but physics, CS, math. Margins is kind of the same software that we use to to run the Journal Club and to host the annotations, but we've made that available for free to anybody that wants to use it. And so folks use it at universities and and for running journal clubs. And and so we've just made that freely available. And then librarian is a browser extension that we developed that is sort of an overlay on top of Archive. So it's about bringing some of the same functionality around comments, plus adding some extra niceties to to Archive,

• 32:43Speaker 01

  like being able to very easily extract the references of a paper that you're looking at or being able to extract the BibTech in order to cite that paper yourself. So it's an overlay on top of Archive. Yeah, it is that you can have that commenting interface without having to leave Archive.

• 32:58Lex Fridman?

  It's kind of incredible. I didn't know about it. And once I learned of it, it's like, holy shit.

• 33:06Lex Fridman?

  Why isn't it more popular, given how popular Archive is? Like, everybody should be using it. Archive sucks in terms of its interface. Or, let me rephrase that, it's limited.

• 33:16Speaker 02

  Yeah.

• 33:16Lex Fridman?

  In terms of its interface.

• 33:17Speaker 02

  Archive is a pretty incredible project, right? And it is, in a way, it's, you know, the growth has been completely linear over time. If you look at like, number of papers published on Archive, like, you know, it's just been, it's pretty much a straight line for the past 20 years. Especially for, you know, for like, if you're coming from a startup background and then you're trying to do Archive, you'd probably try to like, all sorts of growth acts and like, try to, to then maybe like, have paid features and things like that, and that would kind of maybe ruin it. And so, there's, there's a subtle balance there, and I don't know what, what aspects you can change about it.

• 33:55Speaker 01

  Yeah, for some tools in science, it just takes time for them to grow. Archive just turned 30, I believe.

• 34:02Lex Fridman?

  Yeah.

• 34:03Speaker 01

  And for, for people that don't know, Archive is this kind of online repository where people put pre-prints, which are versions of the papers, before they actually make it to journals.

• 34:13Lex Fridman?

  A-R-X-I-V.

• 34:16Speaker 01

  Exactly.

• 34:16Lex Fridman?

  For people who don't know, and it's actually a really vibrant place to publish your papers in, in the aforementioned communities of mathematics, physics, and computer science.

• 34:27Speaker 01

  It started with mathematics and physics, and then, over the, the last 30 years, it evolved into now. Actually, computer, computer science now, it's, it's a more popular category than, than physics and math on Archive.

• 34:38Lex Fridman?

  And there's also, which I don't know very much about, like, a biology, medical version of that is.

• 34:43Speaker 01

  BioArchive, yeah, BioArchive.

• 34:45Speaker 02

  More recent.

• 34:46Speaker 01

  It's, it's, it's interesting, because if you look at like, these platforms for pre-prints, they are, they actually play a super important role, because, if you look at a category like math... For some papers in math, it might take close to three years after you click upload paper on the journal website and the paper gets published on the website of the journal. So this is literally the longest upload period on the internet. And during those three years, like it's, it's, you know, that content is just, you know, locked. And so that's why it's so important for people to have websites like Archive so that you

• 35:28Speaker 01

  can share that before it goes to the journal with the rest of the world. There was actually on Archive that Perelman published the three papers that led to the proof of the Poincaré conjecture. And then you have other fields like machine learning, for instance, where the field is evolving at such a high rate that people don't even wait before the papers go to journals, before they start working on top of those papers. So they publish them on Archive, then other people see them, they start working on that. And Archive did a really good job at like building that core platform to host papers. But I, I think there's a really, really big opportunity in building more features on top of that platform apart from just hosting papers.

• 36:09Speaker 01

  So collaboration, annotations, and like having other things apart from, from papers like code and, and other things. Because for instance, in the field like machine learning, there's a really big, you know, as, as I mentioned, people start working on, on, on top of pre-prints and they are assuming that, that, that pre-print is correct. But you really need a way, for instance, to maybe it's not peer review, but distinguish what is good work from bad work on Archive. How do you do that? So like a commenting interface like Librarian, it's useful for that so that you can distinguish that at, at, in a field that is growing so fast as machine learning. And, and then you have platforms that focus on, on just biology.

• 36:54Speaker 01

  BioArchive is a good example. BioArchive is also super interesting because there, there's actually an interesting experiment that was run in the sixties. So in the sixties, the NIH supported this, this, this experiment called the Information Exchange Group. Which at the time was a way for researchers to share biology preprints via mail or using libraries. And that project in the 1960s got cancelled six years after it started. And it was due to intense pressure from the journals to kill that project because they were fearing a competition from the preprints for the journal industry.

• 37:39Speaker 01

  Kriek was also was one of the famous scientists that opposed to the information exchange group. And it's interesting because right now, if you analyze the number of biology papers that appear first as preprints, it's only 2% of the papers. And this was almost 50 years after that first experiment. So you can see like that pressure from the journals to cancel that initial version of a preprint repo had a tremendous impact on the number of papers that are showing up in biology as preprints. So it delayed a lot that revolution. But now platforms like Bio Archive are doing that work. But there's still a lot of room for growth there.

• 38:23Speaker 01

  And I think it's super important because those are the papers that are open, that everyone can read.

• 38:27Lex Fridman?

  Okay, so but if we just look at the entire process of science as a big system, can we just talk about how it can be revolutionized? So you have an idea, depending on the field, you want to make that idea concrete, you want to run a few experiments in computer size, there might be some code, there'd be a data set for, you know, some of the more sort of biology, psychology, you might be collecting the data set that's called, you know, a study, right? So that's part of that, that's part of the methodology. And so you are putting all of that into a paper form.

• 39:08Lex Fridman?

  And then you have some results and then you you submit that to a place for review through the peer review process and there's a process where how would you summarize the peer review process, but it's it's really just like a handful of people look over your paper and comment and based on that decide whether your paper is good or not. So there's a whole broken nature to it. At the same time, I love the peer review process when I buy stuff on Amazon, like for like the commenting system, whatever that is. So, okay, so there's a bunch of possibilities for revolutions there. And then there's the other side, which is the collaborative

• 39:50Lex Fridman?

  aspect of the science, which is people annotating, people commenting, sort of the low effort collaboration, which is a comment. Sometimes, as you've talked about, a comment can change everything, but you know, or a higher effort collaboration, like more like maybe annotations or even like contributing to the paper. You can think of like collaborative updating of the paper over time. So there's all these possibilities for doing things better than they've been done. Can we talk about some ideas in this space, some ideas that you're working on, some ideas that you're not yet working on, but should be revolutionized?

• 40:31Lex Fridman?

  Because it does seem that archive and like open review, for example, are like the Craigslist of science, like, like, yeah, okay, I'm very grateful that we have it, but it just feels like it's like 10 to 20 years, like, it doesn't feel like that's a feature. The simplicity of it is a feature. It feels like it's a it's a bug. But then again, the pushback there is Wikipedia has a same kind of simplicity to it, and it seems to work exceptionally well. In the crowdsourcing aspect of it. So sorry, there's a bunch of stuff going on the table. Let's just pick random things that we can talk about.

• 41:16Speaker 01

  Wikipedia, you know, for me, it's the cosmological constant of the internet. It's, I think we are lucky to live in the parallel universe where Wikipedia exists.

• 41:24Lex Fridman?

  Yes.

• 41:25Speaker 01

  Because if someone had pitched me Wikipedia, like a publicly edited encyclopedia, like a couple of years ago, like it would be, I don't know how many people would have said that that would have survived.

• 41:37Speaker 02

  I mean, it makes almost no sense. It's like having a Google Doc that everybody on the internet can edit and like they'll be like the most reliable source for for knowledge.

• 41:46Lex Fridman?

  And I don't know how many, but hundreds of thousands of topics.

• 41:50Speaker 01

  Yeah.

• 41:52Speaker 02

  It's insane.

• 41:53Speaker 01

  It's insane. And like you have, and then you have users, like there's one, a single user that edited one third of the articles on Wikipedia. So we have these really, really big power users. There are a substantial part of like what makes Wikipedia successful. And so like, no one would have ever imagined that that could happen.

• 42:16Speaker 01

  And so that, that's, that's one thing I completely agree with what you just said. I also.

• 42:20Lex Fridman?

  Sorry to interrupt briefly. Maybe let's inject that into the discussion of everything else. I also believe, I've seen that with Stack Overflow, that one individual or a small collection of individuals contribute or revolutionize most of the community. Like, if you create a really powerful system for archive or like open review and made it really easy and compelling and exciting for one person who's in like a 10x contributor to do their thing, that's going to change everything. It seems like that was the mechanism that changed everything for Wikipedia. And that's the mechanism that changed everything for Stack Overflow is gamifying or making

• 43:02Lex Fridman?

  it exciting or just making it fun or pleasant or fulfilling in some way for those people who are insane enough to like answer thousands of questions or write thousands of factoids and like research them and check them, all those kinds of things, or read thousands of papers.

• 43:21Speaker 02

  Yeah. No, Stack Overflow is another great example of that. And it's just, and those are both two incredibly productive communities that generate a ton of value and, and, and capture almost none of it. Right? And it's. And in a way, it's almost like counter. It's very counterintuitive that people, that these communities would exist and thrive. And it's really hard to, you, there aren't that many communities like that.

• 43:54Lex Fridman?

  So how do we do that for science? Do you have ideas there? Like, what are the biggest problems that you see? You're working on some of them.

• 44:01Speaker 01

  Like, just on that, there are a couple of really interesting experiments that people are running. And an example would be like the polymath projects. So this is a kind of a social experiment that was created by Tim Gowers, Fields medalist. And his idea was to try to prove that, is it possible to do mathematics in a massively collaborative way on the internet? So he decided to pick a couple of problems and test that. And they found out that it actually is possible for specific types of problems, namely problems that you're able to break down in little pieces and go step by step. You might need, as with open source, you might need people that are just kind of reorganizing

• 44:46Speaker 01

  the house every once in a while. And then, you know, people throw a bunch of ideas and then, you know, you make some progress, then you reorganize, you reframe the problem and you go step by step. But they were actually able to prove that it is possible to collaborate online and do progress in terms of mathematics. And so I'm confident that there are other avenues that could be explored here.

• 45:10Lex Fridman?

  Can we talk about peer review, for example?

• 45:12Speaker 01

  Absolutely. I think like, in terms of the peer review, I think we, it's important to look at the bigger picture here of like, of what this scientific, the scientific publishing ecosystem looks like. Because for me, there are a lot of things that are wrong about that entire process. So if you look at what publishing means in like a traditional journal, you have journals that pay authors for their articles, and then they might pay like reviewers to review those articles, and finally they pay people to, or distributors to distribute the content.

• 45:54Speaker 01

  In the scientific publishing world, you have scientists that are usually backed by government grants. They are giving away their work for free in the form of papers. And then you have other scientists that are reviewing their work. This process is known as the peer review process, again for free. And then finally, we have government-backed universities and libraries that are buying back all that work so that other scientists can read. So this is, for me, it's bizarre. You have the government that is funding the research, is paying the salaries of the scientists, is paying the salaries of the reviewers, and it's buying back all that product of their work, again.

• 46:37Speaker 01

  And I think the problem with this system, and it's why it's so difficult to break this suboptimal equilibrium, is because of the way academia works right now and the way you can progress in your academic life. And so in a lot of fields, the competition in academia is really insane. So you have hundreds of PhD students. They are trying to get to a professor position, and it's hypercompetitive. And the only way for you to get there is if you publish papers, ideally in journals, with a high-impact factor.

• 47:19Lex Fridman?

  In computer science, it's often conferences are also very prestigious, or actually more prestigious than journals now.

• 47:26Speaker 01

  Okay, interesting.

• 47:27Lex Fridman?

  So that's the one discipline where, I mean, that has to do with the thing we've discussed in terms of how quickly the field turns around. But like NURIPS, CVPR, those conferences are more prestigious, or at the very least as prestigious as the journals. But it doesn't matter, the process is what it is.

• 47:46Speaker 01

  And so for people that don't know, the impact factor of a journal is basically the average number of citations that a paper would get if it gets published on that journal. But so you can really think that the problem with the impact factor is that it's a way to turn papers into accounting units. And let me unpack this because it's the impact factor is almost like a nobility title. So because papers are born with impact even before anyone reads them. So the researchers, they don't have the incentive to care about if this paper is going to have a long term impact on the world. What they care, their goal, their end goal is the paper to get published.

• 48:31Speaker 02

  Yes.

• 48:32Speaker 01

  So that they get that value upfront. And so for me, that that is one of the problems of that. And that really creates a tyranny of metrics. Because at the end of the day, if you are a dean, what you want to hire is like people, researchers that publish papers on journals with high impact factors, because that will increase the ranking of your university and will allow you to charge more for tuition, so on and so forth. And and that, that, especially when you are in super competitive areas, you know, that people will try to gamify that system and misconduct starts showing up. And there's a really interesting book on this topic called Gaming the Metrics.

• 49:15Speaker 01

  It's a book by a researcher called Mario Biagiole. It goes a lot into like how this, the impact factor and metrics affect science negatively. And it's interesting to think, especially in terms of citations. If you look at the early work of like, looking at citations, there was a lot of work that was done by a guy called Eugene Garfield. And this guy, the early work in terms of citation, they wanted to use, they wanted to use citations as, from a descriptive point of view. So what they wanted to to create was a map. And and that map would create a visual representation of influence. So citations would be links between papers.

• 49:54Speaker 01

  And ideally, what they would show, they would represent is that you read someone else's paper and it had an impact on your research. They weren't supposed to be counted.

• 50:04Speaker 02

  I think this inspired like Larry and Sergey's.

• 50:06Speaker 01

  Exactly.

• 50:07Speaker 02

  Work, right, for Google.

• 50:08Speaker 01

  Exactly. I think they even mentioned that. But what happens is like, as you start counting citations, you create a market. And the same way, like, and this was the work of Eugene Garfield was a big inspiration for Larry and Sergey and for the PageRank algorithm that, you know, led to the creation of Google. And they even recognized that. And if you think about it, it's like, the same way, there's a gigantic market for search engine optimization, SEO, where people try to optimize, you know, the PageRank and how I, a webpage will rank on Google, the same will happen for papers. People will try to optimize like their, the impact factors and

• 50:49Speaker 01

  the citations that they get. And that creates a really big problem. And it's super interesting to actually analyze the, if you look at the distribution of the high, the impact factors of journals, you have like Nature with, Nature, I believe, is like in the low 40s. And then you have, I believe, Science is high 30s. And then you have a really, a good set of good journals that will fall between 10 and 30. And then you have a gigantic tale of journals that have impact factor below two. And you can really see two economies here. You see the, you know, the universities that are maybe less prestigious, less known, that

• 51:32Speaker 01

  where the faculty are pressured to just publish papers regardless of the journal. What I want to do is increase the ranking of my university. And so they end up publishing as many papers as they can in like journals with low impact factor. And unfortunately, this is, represents a lot of the global south. And then you have the luxury good economy. So, for instance, for, and there are also problems here in the luxury good economy. So if you look at the journal like Nature, so with impact factor of like in the low 40s, there's no way that you're going to be able to sustain that level of impact factor by just grabbing the attention of scientists. What I mean by that is like, for, for the

• 52:17Speaker 01

  journals, the articles that get published in Nature, they need to be

• 52:23Speaker 01

  New York Times, great. So they need to make it to the, you know, to the, to the big media. They need to be captured by the big media. And because that's the only way for you to capture enough attention to sustain that level of citations.

• 52:35Lex Fridman?

  Yes.

• 52:36Speaker 01

  And that, of course, creates problems because people then will try to, again, gamify the system and have like titles or abstracts or that are bigger, make claims that are bigger than what is actually can be, you know, sustained by, by the data or the, the content of the paper. And you'll have clickbait titles or clickbait abstracts. And again, this is all a consequence of metrics and science ometrics. And, and this is a very dangerous cycle that I think it's very hard to break, but it's happening in academia in a lot of fields right now.

• 53:13Lex Fridman?

  Is it fundamentally the existence of metrics or the metrics just need to be significantly improved? Because, uh, like I said, the metrics used for Amazon for purchasing, I don't know, computer parts is pretty damn good in terms of selecting which are the good ones, which are not. In that same way, if, if we had Amazon type of review system in the space of ideas, in the space of science, it feels like that those metrics would be a little bit better. Sort of when it's, um, when it's significantly more open to the crowdsourced nature of the internet, of the, of the scientific internet, meaning as opposed to, like, my biggest problem with peer review

• 53:58Lex Fridman?

  has always been that it's like five, six, seven people, usually even less. And it's often, nobody's incentivized to do a good job in the whole process. Meaning it's anonymous in a way that doesn't incentivize, like doesn't gamify or incentivize great work. And also, it doesn't necessarily have to be anonymous. Like, there, there has to be, um, the entire system is, um, doesn't encourage actual sort of rigorous review. For example, like, open review.

• 54:39Lex Fridman?

  Does kind of incentivize that kind of process of collaborative review, but it's also imperfect. It just feels like the thing that Amazon has, which is like thousands of people contributing their reviews to a product.

• 54:54Lex Fridman?

  It feels like that could be applied to science, where the same kind of thing you're doing with Fermat's Library, but doing at a scale that's much larger. It feels like that should be possible, given the number of grad students, given the number of general public that's getting, for example, I personally, as a person who got an education in mathematics and computer science, like, I can, I can be a quote unquote reviewer on a lot bigger set of things than, than is my exact expertise. If I'm one of thousands of reviewers, if I'm the only reviewer, one of five,

• 55:39Lex Fridman?

  then I better be like an expert in the thing. But if, if I, and I've learned this with COVID, which is like, you can just use your basic skills as a data analyst, as a, and to contribute to the review process on a particular little aspect of a paper, and be able to comment, be able to sort of draw in some references that challenge the ideas presented, or to enrich the ideas that are presented. Where, you know, and it just feels like crowdsourcing the review process would be able to allow you to have metrics in terms of how good a paper is that are much better representative of its actual impact in the world, of its actual value to the world,

• 56:22Lex Fridman?

  as opposed to some kind of arbitrary gamified

• 56:28Lex Fridman?

  version of its impact.

• 56:31Speaker 02

  I agree with that. I think we, there's definitely the possibility, at least for more resilient, a more resilient system than what we have today. And it's, I think that's kind of what you're describing, Alex. And I feel, I mean, to an extent, we kind of have like a little bit of a. Heisenberg uncertainty principle, when you pick a metric, as soon as you do it, then maybe it works as a good heuristic for a short amount of time, but soon enough, people would start gamifying.

• 56:54Lex Fridman?

  Yeah.

• 56:55Speaker 02

  But then you can definitely have metrics that are more resilient to gamification and they'll work as a better heuristic to try to push you in the best direction.

• 57:06Lex Fridman?

  But I guess the underlying problem you're saying is there's a shortage of positions in academia.

• 57:12Speaker 02

  That's a big problem for me.

• 57:13Lex Fridman?

  Yeah, and so they're going to be constantly gamifying the metrics.

• 57:18Speaker 02

  It's a bit of a zero sum.

• 57:19Speaker 01

  It's a very competitive field and that's what usually happens in very competitive fields.

• 57:26Lex Fridman?

  Yeah, yeah.

• 57:27Speaker 01

  But I think some of like the peer review problems, like scale helps, I think, and it's interesting to look at like what you're mentioning, breaking it down, maybe in like smaller parts and having more people jumping in. But this is definitely a problem and the peer review problem, as I mentioned, is correlated with the problem of like academic career progression and it's all intertwined and that's why I think it's so hard to break it. There are like a couple of really interesting things that are being done right now. There are a couple of, for instance, journals that are overlay journals on top of platforms like Archive and Bio Archive that want to remove like the more traditional journals from the equation.

• 58:10Speaker 01

  So essentially a journal is just a collection of links to papers and what they're trying to do is like removing that middleman and trying to make the review process a little bit more transparent and not charging universities. Like there's a couple of, there are a couple of more famous ones. There's one discrete analysis in mathematics. There's one called the Quantum Journal, which we're actually working with them. We have a partnership with them for the papers that get published in Quantum Journal. They also get the annotations on from us and they're doing pretty well. They've been able to grow substantially. The problem there is getting to critical mass. So it's again convincing the researchers and especially the young researchers that

• 58:53Speaker 01

  need that impact factor, need those publications to have citations, to not publish on the traditional journal and go on an open journal and publish their work there. There, I think there are a couple of really high profiled scientists, people like Tim Gowers, that are trying to incentivize like. Famous scientists that already have tenure and that don't need that to publish that to increase the reputation of those journals so that other maybe younger scientists can start publishing on on those as well and so they can try to break that vicious cycle of of the more traditional journals.

• 59:31Lex Fridman?

  I mean, another possible way to break this cycle is to like raise public awareness and just by force like ban paid journals like what exactly are they contributing to the world? Like basically making it illegal to uh forget the fact that it's mostly federally funded. So that's that's a super ugly picture too, but like, why should knowledge be so expensive?

• 1:00:01Lex Fridman?

  Like where everyone is working for the public good and then there's these gatekeepers that, you know, most people can't read most papers without having to pay money and that's

• 1:00:14Lex Fridman?

  that doesn't make any sense. Like that that should be illegal.

• 1:00:18Speaker 01

  I mean, that's what you're saying is exactly right. I mean, for instance, right? I I went to school here in the US. We studied in Europe and you would sit like you'd ask me all the time to download papers and send it to him because he just couldn't get it and like papers that he needed for his research and so.

• 1:00:33Lex Fridman?

  But he's a student like he's.

• 1:00:34Speaker 01

  Yeah, he's a grad student.

• 1:00:36Lex Fridman?

  He was a grad student, but that, you know, I'm even referring to just regular people.

• 1:00:40Speaker 01

  Oh, yeah. Okay, that too.

• 1:00:42Lex Fridman?

  And I I think during 2020, because of COVID, a lot of journals put down the walls for certain kind of coronavirus related papers, but like that just gave me an indication that like this should be done for everything. It's it's absurd. Like people should be outraged that there is these gates because so the moment you dissolve the journals, then there will be an opportunity for startups. To build stuff on top of archive. It'd be an opportunity for like Fermat's Library to step up, to scale up to something much even larger.

• 1:01:21Lex Fridman?

  I mean, that was the original dream of Google, which I've always admired, which is make the world's information accessible. Actually, it's interesting that Google hasn't, maybe you guys can correct me, but they have put together Google Scholar, which is incredible. But they, and they've did the scanning of books, but they haven't really tried to make science accessible in the following way, like besides doing Google Scholar, they haven't like delved into the papers, right?

• 1:01:54Speaker 02

  Which is especially curious, given what Luis was saying, right? That it's kind of in their genesis, there's this, you know, research that was very connected with all papers reference each other and like building a network out of that.

• 1:02:05Speaker 01

  Interesting enough, like Google, I think there was a, there was not intend, Google Plus was like the Google social network that got canceled, was used by a lot of researchers.

• 1:02:14Lex Fridman?

  Yes, it was.

• 1:02:15Speaker 01

  Whether I think was just a, you know, a side, kind of a side effect, but then a lot of people ended up migrating to Twitter, but it was not on purpose. But yeah, I agree with you, like they haven't gone past Google Scholar and I don't know why.

• 1:02:28Lex Fridman?

  That said, Google Scholar is incredible. For people who are not familiar, it's one of the best aggregation of all the scientific work that's out there and especially the network that connects to all of them, what sites, what? And also trying to aggregate all of the versions of the papers that are available there and trying to merge them in a way that one particular work, even though it's available in a bunch of places, counts as, you know, like a central hub of what that work is across the multiple versions. But that almost seems like a fun pet project of a couple of engineers within Google as opposed to a serious effort to make the world's science accessible.

• 1:03:07Speaker 01

  But going back to just the journals, when you're talking about that, Lex, I believe that In that front, I think we might be past the event horizon. So I think the the the model, the business model for the journals doesn't make sense. There are a middle layer that is not adding a lot of value. And you see a lot of motions where it's like in Europe, a lot of the the papers that are get are funded by the European Union. They will have to be open to the public. And I think there's a lot of.

• 1:03:39Speaker 02

  Bill Gates to like the the what the Gates Foundation funds, like the the demand that it then it that it's accessible to everybody.

• 1:03:48Speaker 01

  Oh, interesting. So I think it's it's a question of time before that that wall kind of falls. And and that is going to open a lot of possibilities. Because, you know, imagine if if you had like the layer of that gigantic layer of papers all available online. You know, that unlocks a lot of potential as a platform for people to build things on top of that.

• 1:04:09Speaker 02

  But I it's what you're saying, it is weird. Like, you can literally go and listen to any song that was ever made on your phone, right? You open Spotify and you might not even pay for it. You might be on the free version and you can listen to any song that was ever made, pretty much. But there's like you, you don't have access to a huge percentage of academic papers, which is just like this fundamental knowledge that we're all funding. But you, as an individual, don't have access to it. And and somehow, you know, like, the problem for music got solved, but for papers, it's still like.

• 1:04:45Lex Fridman?

  It's just not yet. It could be ad supported, all those kinds of things. And then hopefully that would change the way we do science. This is the the most exciting thing for me is, especially once I started like making videos and this silly podcast thing. I started to realize like that if you want to do science, one of the most effective ways is to do a like couple the paper with a set of YouTube videos, like explaining it, like.

• 1:05:14Speaker 01

  That also seems like there's a lot of room for disruption there. What is the paper 2.0 gonna look like? I think like LaTeX and the PDF seems like if you, it's interesting. If you look at the first paper that got published in Nature, and if you look at the paper that got published in Nature today, if you look at the two side by side, they are fundamentally the same. And even though like the paper that gets published today, you know, you get, even code, like right now, people put like code like on a PDF. Like, and there are so many things that are related to papers today. You know, you use, you have data, you have code. You might need videos to better explain the concepts.

• 1:05:57Speaker 01

  So it's, I think for me, it's natural that there's gonna be also an evolution there. That papers are not gonna be just the static PDFs or LaTeX. There's gonna be a next, a next interface.

• 1:06:10Lex Fridman?

  So in academia, a lot of things that are judged, you're judged by is often quantity, not quality. I, I wonder if there's a opportunity to have like, I tend to judge people by the best work they've ever done as opposed to. I wonder if there's a possibility for that to encourage sort of focusing on the quality and not necessarily in paper form, but maybe a subset of a paper, a subset of idea, almost even a blog post or an experiment. Like, why does it have to be published in a journal?

• 1:06:40Speaker 01

  Yeah.

• 1:06:41Lex Fridman?

  To be legitimate?

• 1:06:43Speaker 01

  And it's interesting that you mentioned that. I also think like, yeah, it's why, why, why is that the only format? Why can't a blog post or, we were even experimenting, experimenting with these a few months ago. Can you actually like publish something or like a new scientific breakthrough or?

• 1:07:06Speaker 01

  Or something that you've discovered in the form of like a set of tweets.

• 1:07:10Lex Fridman?

  Yeah.

• 1:07:10Speaker 01

  A Twitter thread.

• 1:07:11Lex Fridman?

  Yeah.

• 1:07:11Speaker 01

  Why can't that be possible? And we were experimenting with that idea. We even, yeah, we ran a couple of, like, some people submitted a couple of those. Like, I think the limit was three or four tweets.

• 1:07:25Lex Fridman?

  Yeah.

• 1:07:26Speaker 01

  Uh, maybe it's a new way to look at a, you know, a proof or something. But I think it serves to show that there should be other ways to publish like scientific discoveries that don't fit the paper format.

• 1:07:37Lex Fridman?

  Well, but so even with the Twitter thread, it would be, it would be nice to have some mechanism of formalizing it and making it making it into an NFT.

• 1:07:49Speaker 01

  Maybe.

• 1:07:50Lex Fridman?

  Like a concrete thing that you can reference as a link that's

• 1:07:54Speaker 01

  Yeah.

• 1:07:54Lex Fridman?

  unique. Because, I mean, everything we've been saying, all of that, uh, while being true, it's also true that the constraints and the formalism of a paper works well. It like forces you, constraints forces you to narrow down your thing and literally put it on paper. But, you know.

• 1:08:21Speaker 01

  I agree.

• 1:08:22Lex Fridman?

  Make concrete. And that's why, I mean, it's not broken. It's just could be better.

• 1:08:28Speaker 01

  I agree.

• 1:08:29Lex Fridman?

  And that's the main idea. I think there's something about writing, whether it's a blog post or Twitter thread or a paper, that's really nice to, to concretize a particular little idea that that can then be referenced by other ideas, then it can be built on top of with other ideas. So, uh, let me ask, you've read quite a few papers. You've annotated quite a few papers. Let's talk about the process itself. How do you advise people read papers? Or maybe you want to broaden it beyond just papers, but just read concrete pieces of information to understand the insights that lay within.

• 1:09:14Speaker 02

  I would say for papers specifically, I would bring back kind of what Louise was talking about. It's that it's important to keep in mind that papers are not optimized for ease of understanding. And so, right, there's all sorts of restrictions in size and format and language that they can use. And so it's important to keep that in mind. And so that if you're struggling to read a paper, doesn't that might not mean that the underlying material is actually that hard. And so, so that's definitely something that, especially for us, that we read papers and most of the times we'll read papers that are completely outside of our comfort zone, I guess. And so it would be completely new areas to us.

• 1:09:59Speaker 02

  So I always try to keep that in mind.

• 1:10:01Lex Fridman?

  So there's usually a certain kind of structure, like abstract introductions, methodology, depending on the community and so on. Is there something about the process of like, how to read it, whether you want to skim it, to try to find the parts that are easy to understand or not, reading it multiple times? Is there any kind of hacks that you can comment on?

• 1:10:25Speaker 01

  I remember like Feynman had this kind of hack when he was reading papers where he would basically, I think, I believe he would read the conclusion of the paper and we would try to just see if he would be able to figure out how to get to the conclusion in like a couple of minutes by himself. And he would read a lot of papers that way. And I think Fermi also did that almost. And Fermi was known for doing a lot of back of the envelope calculations. So he was a master at doing that. And in terms of like, especially when, when reading a paper, I think a lot of times people might. Feel discouraged about the first time you read it.

• 1:11:10Speaker 01

  You know, it's very hard to grasp or you don't understand a huge fraction of the paper. And I think it's having read a lot of papers in my life. I think I've in peace with like the fact that you might spend hours where you're just reading a paper and jumping from paper to paper, reading citations. And like your level of understanding of sometimes of the paper is very close to zero percent. And all of a sudden, you know, everything kind of makes sense and in your mind. And then, you know, you have this quantum jump where all of a sudden you you you understand the big picture of the paper. And I I and and this is an exercise that I have to when reading papers and especially

• 1:11:54Speaker 01

  like more complex papers like, okay, you don't understand because you're just going through the process and just keep going. And like, and it it's might feel super chaotic, especially if you're jumping from reference to reference. You know, you might end up with like 20 tabs opened and you're reading a ton of other papers, but it's just trusting that process that at the end, like you'll find light. And I think for me, that's a good framework when reading a paper. It's hard because, you know, you might end up spending a lot of time and you it looks like you're lost. But uh, but that's the process to actually, you know, understand what they're talking about in a paper.

• 1:12:32Lex Fridman?

  Yeah, I think that process I enjoy. I've found a lot of value in the process, especially for things outside my field, of reading a lot of related work sections and kind of go going down that path of getting a big context of the field. Because what's especially when they're well written, there's opinions injected into the related work, like what work is important, what is not. And if you read multiple related work sections that cite or don't cite each other, like the papers, you you get a sense of where the field, where the tensions of the field are, where this where the field is striving. And that helps you put into context, like whether the work is radical, whether it's

• 1:13:14Lex Fridman?

  overselling itself, whether it's underselling itself, all those things. And on added on top of that. I find that often the related work section is the most kind of accessible and readable part of a paper because it's kind of, it's brief, to the point, it's trying to like summarize it, it's almost like a Wikipedia style article. The introduction is supposed to be a compelling story or whatever, but it's often like oversell. There's like an agenda in the introduction. The related work usually has the least amount of agenda, except for the few like elements where you're trying to talk shit about previous work, where you're trying to sell that you're doing much better.

• 1:13:57Lex Fridman?

  But other than that, when you're just painting where the field came from or where the field stands, it's really valuable. And also, again, just to agree with Fana in the conclusion, but it's like I get a lot of value from the breadth first search, kind of read the conclusion, then read the related work, and then go through the references in the related work, read the conclusion, read the related work, and just go down the tree until you like hit dead ends or run out of coffee. And then through that process, you go back up the tree and now you can see the results in their proper, in their proper context. Unless, of course, the paper's truly revolutionary, which even that process will help you understand

• 1:14:40Lex Fridman?

  that is in fact truly revolutionary. You've also, you talked about just following your Twitter thread in a depth first search. You talked about that you read the book on Grisha Perlman, Gogor Perlman, and then you had a really nice Twitter thread on it and you were taking notes throughout. So at a high level, is there suggestions you can give on how to take good notes? Whether it's we're talking about annotations or just for yourself to try to? Put on paper ideas as you progress through the work in order to then like understand the work better.

• 1:15:20Speaker 02

  For me, I always try not to underestimate how much you can forget within six months after you've read something.

• 1:15:28Lex Fridman?

  I thought you were gonna say five minutes, but yeah, six months is good.

• 1:15:30Speaker 02

  Yeah, or even shorter. And so that's something that I always try to keep in mind. And it's often, I mean, every once in a while, I'll read back a paper that I annotated on Fermat. And I'll read through my own annotations and I've completely forgotten what I had written. But it also, it's interesting because in a way, after you just understood something, you're kind of the best possible teacher that can teach your future self. You know, after you've forgotten it, you're kind of your own best possible teacher at that moment. And so it can be great to try to capture that.

• 1:16:15Lex Fridman?

  It's brilliant. It just made me kind of realize it's really nice to put yourself in the position of teaching an older version of yourself that returns to this paper, almost like thinking it literally.

• 1:16:29Speaker 02

  That's underexplored, but it's super powerful because you were the person that you can like, if you look at the scale from like one, not knowing anything about the topic and 10, like you are the one that progressed from one to 10 and you know which steps you struggled with. So you're really the best person to help yourself make that transition from one to 10. And a lot of the times, like, and I really believe that the framework that we have to like expose ourselves to like be talking to like us when we were an expert, when we were taking that class and we knew everything about quantum mechanics. And then six months later, you don't remember half of the things. How could we make it easier for like to?

• 1:17:11Speaker 01

  Have those conversations between you and your past expert self. I think there might be, it's an underexplored idea. I think notes on paper are probably not the best way. I'm not sure if it's a combination of like video, audio, where it's like you have a guided framework that you follow to extract information from yourself so that you can later kind of revisit to make it easier to remember. But that's, I think it's an interesting idea worth exploring. That not, I haven't seen a lot of people kind of trying to distill that problem.

• 1:17:50Lex Fridman?

  Yeah, I'm creating the kind of tools. I find if I record, it sounds weird, but I'll take notes. But if I record audio, like little clips of thoughts, like rants,

• 1:18:04Lex Fridman?

  that's really effective at capturing something that notes can't. Because when I replay them, for some reason, it loads my brain back into where I was when I was reading that in a way that notes don't. Like when I read notes, I'll often be like, what? What was I thinking there? But when I listen to the audio, it brings you right back to that place. So there might, and maybe with video, with visual, that might be even more powerful.

• 1:18:33Speaker 01

  I think so. Yeah, and I think just the process of, you know, verbalizing it, that alone kind of makes you have to structure your thought and put it in a way that somebody else could come and understand it. And just the process of that is useful to organize your thoughts. And yeah, just that alone.

• 1:18:54Lex Fridman?

  Does the Fermat's Library Journal Club have like a video component or no?

• 1:18:59Speaker 01

  Not natively. We sometimes will include videos, but it's always embedded.

• 1:19:04Lex Fridman?

  Do people like build videos on top of it to explain the paper? Because you're doing all the hard work of understanding deeply the paper.

• 1:19:12Speaker 01

  Not, we haven't seen that happening too much. But we were, we were actually playing around with the idea of creating some sort of podcast version where we try to distill the paper on an audio format that not maybe you could have access.

• 1:19:27Lex Fridman?

  That might be tricky.

• 1:19:28Speaker 01

  Might be trickier, but you, there are definitely people that could be interested in the paper and that topic, but are not willing to read it. But they might listen to a 30 minute episode on that paper.

• 1:19:36Lex Fridman?

  Yes.

• 1:19:37Speaker 01

  You could reach more people and, and you might even bring the authors to the conversation. But it's tricky, especially for like more technical papers. We've, we've thought about that, doing that, but we haven't like converged. Sure if you have any.

• 1:19:50Lex Fridman?

  Well, I'm, I'm gonna take that as a, a, a small project to take one of your, one of the formats, almost like half advertisement and half as a challenge for myself. Take, take one of the annotated papers and like use it as a basis for creating a, a quick video. Uh, I, I've seen like, um, hopefully I'm saying the name correctly, but machine learning street talk.

• 1:20:13Speaker 01

  Hmm.

• 1:20:14Lex Fridman?

  I think that's the name of the show, the, that I recommend highly. That's the right name. But, uh, they, they do exactly that, which is multiple hour breakdown of a paper with video component. Sometimes with authors, um, people love it. It's very effective.

• 1:20:29Speaker 01

  There's, there's also, I've seen, I haven't seen the entire, in its entirety, but I've seen like the, the founder of comma.ai, George.

• 1:20:37Lex Fridman?

  Yeah, George.

• 1:20:38Speaker 01

  I've seen him like just taking a paper and then, uh, you know, distilling the paper and, and coding it, coding it sometimes during 10 hours.

• 1:20:47Lex Fridman?

  Yeah.

• 1:20:48Speaker 01

  And, uh, he was able to, you know, get a lot of people interested in, in that and viewing him.

• 1:20:52Lex Fridman?

  So I'm a huge fan of that. Like, uh, it's, George is a personality. I think a lot of people like listen to this podcast for the same reason. It's not necessarily the contents. It's they, they, they like to listen to like a, a silly Russian who's, has a childlike brain and mumbles and all those like struggle with ideas, right? And George is a madman who people just enjoy like, how is he going to struggle in implementing this particular paper? How is he going to struggle with this idea? It's fun to watch and that actually pulls you in. The personality is important there.

• 1:21:25Speaker 01

  True, but there's, there's, you know, I agree with you, but there also it's visible, like it's.

• 1:21:31Speaker 02

  There's an extraordinary ability that is there, like he's talented and you need to have, there's a craft and this guy definitely has talent and he's doing something that is not easy. And I think that also draws the attention of people.

• 1:21:44Lex Fridman?

  Oh, yeah.

• 1:21:45Speaker 02

  And, and, and like the, the other day, we were actually, we, we ran into this YouTube channel of this guy that was restoring art, right? Um, and, and, um, it was basically just a, a video of him, like his, the production is really, uh, like really well done and it's just him taking really old, um, pieces of, of art, like, and then paintings and then restoring them, but he's really good at that. And he describes that process and that draws attention, uh, draws the attention of people, regardless of your craft, be it like annotating a paper, like restoring.

• 1:22:19Lex Fridman?

  Craftsmanship, excellence, yeah. Like George is incredibly good at programming, like quick, like, you know, those, uh, competitive programmers, like Topod and all those kinds of stuff? He has the same kind of element where the brain just jumps around really quickly. And that's, uh, yeah, just like with art restoration. It's more, yeah, it's motivating, but, but, and, and you're right, in, in watching people who are good at what they do, it's motivating, even if the thing you're trying to do is not what they're doing. It's just like contagious when they're really good at it. And the same kind of analysis with the paper, I think, so not just like the final result, but the process of struggling with it. That's really interesting.

• 1:22:59Speaker 02

  Yeah. I think, I mean, I think Twitch proved that like, you know, that there's really a market for, for that, for watching people do things that they're really good at. And, uh, and you will just watch it, you will enjoy that, that, that might even, uh, spike your interest in that specific topic. And, yeah, and people, people will enjoy, uh, watching sometimes hours on end of, of, yeah, great craftsmen.

• 1:23:23Lex Fridman?

  Do you mind if we talk about some of the papers? Do any papers come to mind that, uh, have been annotated on Fermat's Library?

• 1:23:30Speaker 02

  The, the papers that we annotated can be about completely random topics, but that's part of what we enjoy as well. It forces you to explore these topics that otherwise maybe you'd never run into. Uh, and so, and so the ones that come to mind are, to me, are, are fairly random, but one that I, I really enjoyed learning more about is, um, a paper, uh, written by a mathematician, actually Tom Apostol, and, uh, about a. A tunnel in a Greek island off the coast of Turkey. I like this already. Random. So this, okay, so what's interesting about this tunnel? So this tunnel was built in the sixth century B.C.

• 1:24:15Speaker 02

  And it was built in this, in the island of Samos, which is, as I said, off the coast of Turkey. And you're right, they had the city on one side and the other mountain. And then they had a bunch of springs on the other side. And they wanted to bring water into the city. Building an aqueduct would be pretty hard because of the way the mountain was shaped. And it would also, you know, if they, if they were under a siege, like they could just easily destroy that aqueduct. And then the water wouldn't have any water supply. The city wouldn't have any water supply. And so they decided to build a tunnel. And they decided to try to do it quickly.

• 1:24:56Speaker 02

  And so they started digging from both ends at the same time, through the mountain, right? And so like, when you start thinking about this, it's, it's a fairly difficult problem. And this is like sixth century B.C. So you had very limited access to, you know, the mathematical tools that you had at the time were very limited. And so what this paper is about is about the story of how they built it and about the fact that for about 2,000 years, kind of the accepted, the accepted explanation of how they built it was actually wrong. And so this tunnel has been famous for a while. There are a number of historians that talked about it since ancient Egypt.

• 1:25:40Speaker 02

  And the method that they described for, for building it is, is was just wrong. And so these, these researchers went there and, and were able to figure, figure that out. And so basically, kind of the way that they thought they had built it was basically, if you can imagine looking at the mountain from the top, and you have the mountain and then you have both entrances. And so what they, what they thought, and what, this is what the ancient historians described, is that they effectively tried to draw a right angle, a right angle triangle with the two entrances at each end of the hypotenuse.

• 1:26:22Speaker 02

  And the way they did is like they would go around the mountain and kind of walking in a grid fashion. And then you can you can figure out the two sides of the triangle. And then after you have that triangle, you can effectively draw two smaller triangles at each entrance that are proportional to that big triangle. And then you kind of have arrows pointing in each way.

• 1:26:45Lex Fridman?

  Got it.

• 1:26:46Speaker 02

  And then you can you you know at least that these that you have a line going through the the mountain that connects both entrances. The issue with that is like, on- once you, once you go to this mountain and you start thinking of doing this, you realize that especially given that the tools that they had at the time, that your error margin would be too small. You wouldn't be able to do it. Uh, you you you the just the fact of of trying to to build this triangle in that fashion, the error would accumulate and you would end up missing. You'd start building these tunnels and they would miss each other.

• 1:27:20Lex Fridman?

  So the task ultimately is to figure out like really perfectly as as close as possible the direction you should be digging. First of all, that it's possible to have a straight line through. And then what that the direction would be. And then you are trying to infer that by constructing a right triangle. By doing, I I'm not exactly sure about how to do that rigorously, like by tracing the mountain, by walking along the mountain, how to, you said grids?

• 1:27:48Speaker 02

  Yeah, you you kind of walk as if you were in a in a grid. And so you you just walk in right angles. And so, right?

• 1:27:54Lex Fridman?

  But then you have to walk really precisely then.

• 1:27:56Speaker 02

  Exactly.

• 1:27:56Lex Fridman?

  You should have to use tools.

• 1:27:58Speaker 02

  To measure this.

• 1:27:59Lex Fridman?

  And the terrain is probably.

• 1:28:01Speaker 02

  Yeah, very.

• 1:28:01Lex Fridman?

  A mess. So this makes more sense in two D and three D gets even weirder. So, okay, gotcha.

• 1:28:07Speaker 02

  But so this method was described by like an ancient Egyptian historian, I think hero of Alexandria. And um, and then for about like, yeah, for about two thousand years, that's that's how like, that's how we thought that they had built this this tunnel.

• 1:28:23Speaker 02

  And then, yeah, and then these researchers went there and, and, and found out that actually they, they must have had to, to use other methods. And, and then in this paper, they described these, these other methods. And of course, they can't know for sure, but there's, uh, they presented a bunch of plausible alternatives. Uh, the one that for me was, is the most plausible is that what they probably must have done is to use something that is similar to an iron sight on a rifle. The way you can line up, uh, your rifle with a target off in the distance by, by having an iron sight. Um, and, uh, and they, they, they must have done something similar to that effectively with three, with three sticks. And that way

• 1:29:08Speaker 02

  they were able to line up sticks, uh, along the side of the mountain that were all on the same height. And so that then you could get to the other side and you could, and then you could draw that line. So this for me is the most plausible, uh, way that they might have done it. And they, but then they, they, they described this in detail and other possible approaches in this paper.

• 1:29:32Lex Fridman?

  So this is a mathematician doing this?

• 1:29:34Speaker 02

  Yeah, this is a mathematician that, that did this.

• 1:29:38Lex Fridman?

  Which I suppose is the right mindset instead of skills required to solve an ancient problem, right?

• 1:29:44Speaker 02

  Yeah.

• 1:29:45Lex Fridman?

  There's mathematicians and engineers, a lot of things. Cause they didn't have, uh, computers or drones or lidar back then, or whatever technology you would use modern day for civil engineering.

• 1:29:56Speaker 02

  Yeah. And, and another fascinating thing is that like, you know, after, effectively after the, the downfall of the Roman civilization, people didn't build tunnels for about a thousand years. We, we go a thousand years without tunnels. And then like only in like in late middle ages that, that we start doing them again. But, uh, but here is the tunnel like sixth century B.C. like incredibly limited mathematics. And they, and they build it in this way. Um, and, and, and for, and it was a mystery for, for a long time exactly how they did it. And then these mathematicians went there and, and, uh, and, and basically with no archaeology kind of background were able to figure it out.

• 1:30:34Lex Fridman?

  How do annotations for this paper look like? What is it? Uh, what's a successful annotation for a paper like this?

• 1:30:40Speaker 02

  Yeah. So sometimes you're, uh, for this paper, um, sometimes adding some more context, uh, on, on a specific, um,

• 1:30:50Speaker 02

  Part like sometimes they they mentioned, for instance, these instruments that were common in ancient Greece and ancient Rome for for building things. And and so in some of those annotations, I described these instruments in more detail and how they worked. Because sometimes it can be hard to to visualize these. Then this paper, I forget exactly when when this was published. I believe maybe maybe the seventies. But then there was further research into this tunnel and more interesting, other interesting aspects about it. I add those to that paper as well. There's historical context that I also go into there.

• 1:31:34Speaker 02

  For instance, the fact that, as I said, that effectively after the downfall of the Roman Empire, no tunnels were built, like that's something that I that I that I that I added to the paper as well. Yeah, so so those are.

• 1:31:45Lex Fridman?

  So when other people look at the paper, how do they usually consume the annotations? So they it's like, is there a commenting feature? Is the I mean, like, this is a really enriching experience, the way you read a paper. What what aspects do you do people usually talk about that they they value from this?

• 1:32:04Speaker 02

  So, yeah, so anybody can just go on there and and either add a new annotation or add a comment to an existing annotation. And so you can start a kind of a thread within an existing annotation. And that's something that happens relative frequency. And then, because I was the original author of the initial annotation, I get pinged. And so oftentimes I'll go back and and and add on to to that thread.

• 1:32:31Lex Fridman?

  How'd you pick the paper? It's really, I mean, first of all, this whole process is really exciting. I'm gonna, especially after this conversation, I'm gonna make sure I participate much more actively on papers that I know a lot about and on papers I know nothing about.

• 1:32:45Speaker 02

  You can get this way to say the paper.

• 1:32:48Lex Fridman?

  I would love to. I also, I mean, I I realized that there's a. Like it's an opportunity for people like me to publicly annotate a paper like.

• 1:33:01Speaker 01

  Or do an AMA around the paper.

• 1:33:04Lex Fridman?

  Yeah, exactly. But yeah, but like be be in the conversation about a paper. It's like a place to have a conversation about an idea. You get the other way to do it that's much more ad hoc is on Twitter, right? But this is more like formal and you could actually probably integrate the two. Have a conversation about the conversation. So the Twitter is the conversation about a conversation and the main conversation is in the space of annotations.

• 1:33:29Speaker 01

  There's an interesting effect that we we see sometimes with the annotations on our papers is that a lot of people, especially if we the annotations are really well done. People sometimes are afraid of adding more annotations because they see that as a kind of a finished work.

• 1:33:45Lex Fridman?

  Yes.

• 1:33:45Speaker 01

  And so they they don't want to pollute that or and especially if it's like a silly question. This is, I don't think that's good. I think, you know, we should as much as possible try to lower the barrier for someone to jump in and ask questions. I think it only like most of the times it adds value, but it's some feedback that we got from users and readers.

• 1:34:08Speaker 01

  I'm not exactly sure how to to kind of fight that, but.

• 1:34:13Lex Fridman?

  Well, I think I I think if I serve as inspiration in any way is by asking a lot of dumb questions and saying a bunch of dumb shit all the time. And hopefully that inspires the rest of other folks to do the same. Because that's the only way to knowledge, I think, is to be willing to ask the dumb questions.

• 1:34:33Speaker 01

  And and there are papers that are like, you know, we have a lot of papers on Fermat's where it's just one page or really short papers. And you we have like the shortest paper ever published in a math journal. Like we like just a couple of words.

• 1:34:47Lex Fridman?

  Yeah.

• 1:34:47Speaker 01

  One of my favorite papers on the platform is actually a paper written by Enrico Fermi.

• 1:34:53Lex Fridman?

  Yeah.

• 1:34:53Speaker 01

  And the the title of the paper is my, I think, is My Observations at Trinity. So basically Fermi was part of the Manhattan Project. So he was in New Mexico when. Um. They exploded the first atomic bomb. And so he was a couple of miles away from the explosion. And he was probably one of the first persons to calculate the energy of the explosion. And so the way he did that was he took a piece of paper and he tore down a piece of paper in in little pieces. And when the bomb exploded, uh, the Trinity bomb was the name of the bomb. Like he waited for the blast to arrive at the where he was. And then he threw those pieces of paper in the air. And he calculated the energy based on the displacement of the paper, the pieces of paper.

• 1:35:38Speaker 01

  And then he wrote a report, which was classified until like a couple of years ago. One page report, like calculating the energy of the explosion. Oh, that's so badass. And I I we actually went there and kind of unpacked and like, uh, I think he just mentions basically the energy. And we we actually went and one of the annotations is like explaining how he did that. I wonder how accurate he was. It was maybe, I think, like twenty twenty or twenty five percent off. Uh, then there was another person that actually calculated the energy based on uh, images after the explosion at the rate. Uh, and the rate at which the the the like the mushroom of the explosion expanded. And it's more accurate to calculate the energy based on that.

• 1:36:20Speaker 01

  Um, and I think it was like twenty twenty percent off, but it's it's really interesting because, you know, Fermi was known for all these being a master at these back of the envelope calculations. Always like the Fermi problems are well known for for that. Um, and it's super interesting to see like that just one page report and it was also actually classified. And it's interesting because a couple of months ago, uh, when the Beirut explosion happened, there was a a video circulating of these, um, a bride that was doing a photo shoot. Uh, when the explosion in Beirut happened. And so you can see a video of her with the wedding dress. And then the explosion happens and the blast arrives at where she was. She was a couple of miles away from the blast. And you can see like, um.

• 1:37:03Speaker 02

  The displacement of the dress as well. And I actually looked and that video went viral on Twitter. And I actually looked at that video and based, I used the same techniques that Fermi used to calculate the energy of the explosion based on the displacement of the dress. And you could actually see where, where she was at the, the distance from the explosion, because there was a store behind her and you could look the name of the store. And, and so I calculated that it was.

• 1:37:26Lex Fridman?

  The distance and then you can.

• 1:37:28Speaker 02

  The, they, the, based on the distance where she was from the, the explosion and also on the, the displacement of the dress. Like, because you can, when the blast happens, like, you can see the dress going back and then going back to the original position. And like, by just looking at like, how much the, the, the dress moved, you can estimate the explo, the energy of the explosion.

• 1:37:48Lex Fridman?

  I assume you published this.

• 1:37:50Speaker 02

  Uh, on Twitter, it was just a, a Twitter thread. Uh, but it, it actually, like, a lot of people share that and it was picked up by a couple of, of, um, news outlets, but.

• 1:37:59Lex Fridman?

  I, I, I was hoping it would be like a formal title and it would be an archive.

• 1:38:03Speaker 02

  No, no, no.

• 1:38:04Lex Fridman?

  And maybe submitted.

• 1:38:04Speaker 02

  Just a Twitter, a Twitter thread. But it was interesting because it was exactly the same method that Fermi used.

• 1:38:11Lex Fridman?

  Is there something else that jumps to mind? Like, what, is there something, um, I know, like, in terms of papers, like, I know the Bitcoin paper is super popular.

• 1:38:19Speaker 02

  Mm-hmm.

• 1:38:19Lex Fridman?

  I, is there something interesting to be said about any of the white papers in the cryptocurrency space?

• 1:38:25Speaker 02

  Yeah, the, the, the Bitcoin paper was the first paper that we put on Fermats. And, uh.

• 1:38:31Lex Fridman?

  Why, why that, why that choice as the first paper?

• 1:38:34Speaker 02

  This was a while ago and it was one of the papers that I read and then, uh, and then kind of explained it to, to Luigi and there are two other friends that do this journal club with us. And, um, I did some research in cryptography, uh, as an undergrad. And so it was a topic that I was interested in. Um, but even for me, the, I, I had that, that background, but reading the Bitcoin paper, it, it took me a few reads to really kind of wrap my head around it. It's, it's right, it's, it uses very Spartan precise language in a way. It's like, you feel like you can't take any word out of it without something falling apart. And, uh, and it's all there.

• 1:39:15Speaker 02

  I think it's a beautiful paper and it's, it's, it's very well-written, of course, but, um, you know, we wanted to try to make it accessible so that anybody that maybe is an undergrad in computer science could go on there and then, and, and know that. You have all the information in that page that you're going to need to understand the mechanics of Bitcoin. And so like I explained, you know, the basic public key cryptography that you need to know in order to understand it, like I can explain, okay, what are the properties of a hash function? And how they are useful in this context? Explain what a Merkle tree is. So a bunch of those basic concepts that maybe if you're reading it for a first time

• 1:39:59Speaker 02

  and you're an undergrad and you know, you don't know those terms, you're going to be, you know, discouraged because maybe, okay, now I have to go and Google around until I understand these before I can make progress in the paper. And this way it's all there, you know? So there's a magic to, also to the fact that over time, more people went on there and added further annotations. So the idea that the paper gets easier and more accessible over time, but that's still, you're still looking at the original content, the way the, the author intended it to be. But there's just more context and the toughest bits have, have more in-depth explanations.

• 1:40:38Speaker 01

  Okay, I think like there's a, there's so many interesting papers there. Like I remember reading the paper that was written by Freeman Dyson on the, like the, the first time that he explained, or he came up with the concept of the Dyson sphere. And he, he put that out, like it's again, it's a one-page paper. And what he explained was that eventually if civilization develops and, and grows, there's going to be a point where, when the resources on the planet are not, are not enough for the energy requirements of that civilization. So if you want to go, the next step is you need to go to the next star and extract energy from that star.

• 1:41:21Speaker 01

  And the way to do it is you need to build some sort of cap around the star that extracts the energy. So he theorized this idea of the, the Dyson sphere. And he went on to kind of analyze how you would build that, the stability of that sphere, like if something happens, like if there's like a small oscillation with that, that sphere collapsed into the, the star. Know what what would happen and even went on to kind of say that a good way for us to look for signs of intelligent life out there is to look for signals of these Dyson spheres. And because, you know, according to the law of second law of thermodynamics, like there's going to be some a lot of infrared radiation that is going to be emitted as a consequence of extracting the energy from the star.

• 1:42:05Speaker 01

  And we should be able to see those signals of like infrared if we look at the sky. But all these like from the introduction of the concept, like the how to build a Dyson sphere, the problems of like having a Dyson sphere, how to detect how that could be used as a signal for intelligence.

• 1:42:21Lex Fridman?

  Wait, really? That's all in the paper?

• 1:42:23Speaker 01

  All in one like one page paper. And it's like it's it's for me, it's beautiful. It's like

• 1:42:27Lex Fridman?

  Where was this published?

• 1:42:28Speaker 01

  I don't remember.

• 1:42:30Lex Fridman?

  It's fascinating that papers like that could be.

• 1:42:33Speaker 01

  Yeah.

• 1:42:33Lex Fridman?

  I mean, the guts it takes to put that all together in a paper form. You know, that that kind of challenges our previous discussion of papers. I mean, papers can be beautiful. You can play with the format, right?

• 1:42:46Speaker 01

  But there's a lot to unpack there. That's like the that's the the starting point. But it's it's it's beautiful that you're able to put that in one page. And then people can build on top of that.

• 1:42:57Lex Fridman?

  But the key ideas are there.

• 1:42:59Speaker 01

  Yeah, exactly.

• 1:43:00Lex Fridman?

  What about have you looked at any of the the big seminal papers throughout the history of science? Like you look at simple like Einstein papers. Are have any of those been annotated?

• 1:43:11Speaker 02

  Yeah, yeah, no, we we have some more seminal papers that that people will have heard about. You know, we have the the DNA double elix paper on there. We have the Higgs boson paper. Yeah, there's papers that that we know that it's they're not going to be finding out about them because of us, but it's papers that we think should be more widely read and that folks would benefit from having some annotations there. And so we also have a number of those.

• 1:43:45Speaker 01

  A lot of like discovery papers for fundamental particles and all that. As we have a lot of those on Fermat's library. And we I would like to end. We haven't annotated that one, but I'd like to on the Riemann hypothesis. That's a really interesting paper as well. And and but we haven't annotated that one, but there's a lot of like more historical landmark papers. On the platform.

• 1:44:08Lex Fridman?

  Have you done a Poncaria conjecture with Perman?

• 1:44:13Speaker 01

  That's too much.

• 1:44:14Lex Fridman?

  Too much?

• 1:44:15Speaker 01

  Too much for me, but it's it's interesting that, you know, and going back to our discussion, like the Poncaria paper was like published on archive and and was not on a journal, like the three papers and.

• 1:44:27Lex Fridman?

  Yeah, what do you make of that? I mean, he's such a fascinating human being. I mentioned to you offline that I'm going to Russia. He's somebody I'm really.

• 1:44:35Speaker 01

  To interview.

• 1:44:36Lex Fridman?

  Yeah, well, so I definitely will interview him and I believe I will. I believe I can. I just don't know how to. I know where he lives, so here. Okay. My my my hope is my conjecture is that if I just show up to the house and look desperate enough that or threatening enough or some combination of both, that like the only way to get rid of me is to just get the thing done. That's the hope.

• 1:45:05Speaker 01

  It's actually interesting that you mentioned that because I after I so a couple of weeks ago, I was searching for like stuff about Paramount Paramount online and ended up on this Twitter account of this guy that claims to be Paramount Paramount's assistant. And he is like he has been posting a bunch of pictures like next to Paramount. You can see like Paramount in a library and he's like next to him like taking a selfie or like Paramount walking on the street and like maybe you could reach out to his assistant. Then I'll send you. I'll send you this Twitter account.

• 1:45:38Lex Fridman?

  Maybe you're on to something.

• 1:45:39Speaker 01

  No, but but going going back to like Paramount is super interesting because the fact that he published the the proofs on archive is what was also like a way for him to because he really didn't like the scientific publishing industry and the fact that you had to pay to get access to to articles. And that was a form of like protest. And that's why he published those papers there. I mean, I think Paramount is just a fascinating like character. And for me, it's this kind of ideal of a platonic ideal of what a mathematician should be, you know, it's someone that is, you know, it's just cares about deeply cares about mathematics, you know, it cares about fair attribution of.

• 1:46:22Speaker 01

  Disregards money and and and like the fact that he published like on archive was is a good example of that.

• 1:46:30Lex Fridman?

  What about the Fields Medal that he turned down the Fields Medal? What's what's?

• 1:46:33Speaker 01

  Yeah.

• 1:46:34Lex Fridman?

  What do you make of that?

• 1:46:35Speaker 01

  Yeah, I mean, if you look at like the reasons why he rejected the Fields Medal. So after so Perelman did a post talk in the US and when he he came back to Russia.

• 1:46:46Lex Fridman?

  Do you know how good his English is?

• 1:46:47Speaker 01

  I think it's fairly good.

• 1:46:49Lex Fridman?

  I think it's pretty good, right?

• 1:46:50Speaker 01

  I think it's really good, especially.

• 1:46:51Speaker 02

  He's given lectures in American.

• 1:46:53Lex Fridman?

  But I haven't been able to.

• 1:46:55Speaker 01

  Listen to anything.

• 1:46:55Lex Fridman?

  Well, certainly not listen, but I haven't been able to get anybody because I know a lot of people have been to those lectures. I'm not able to get a sense of like, yeah, but how strong is the accent? What are we talking about here? Is this gonna have to be in Russian? Is it gonna have to be in English? It's fascinating. But he writes the papers in English, so.

• 1:47:12Speaker 01

  True, like there's there's but there's so much like such a fascinating character. And there are a couple of examples like him like at I think twenty eight or twenty nine, he proved like a really famous conjecture called the Sol conjecture, I believe it was like in a very short four page proof of that was a really big breakthrough. Then he went to Princeton to give a lecture on that. And after the lecture, the the chair of the math department at Princeton, a guy called Peter Sarnock, went up to to Perelman, was trying to recruit him, trying to offer him a position at at Princeton. And he was and at some point he asked for Perelman's resume. Perelman responded saying, just gave a lecture on like this really tough problem. Why do you need my resume?

• 1:47:57Speaker 01

  I'm not gonna send you like I just proved like my value. But but going back to the Fields Medal, like when when Perelman went to back to Russia, he he he arrived at a time where the the salary of post talks were so much off in regards to inflation that they were not making any money like they they people didn't even bother to pick up the checks at the end of the month because they were just like ridiculous. But thankfully, he had some money that he had gained while he was doing his post talks. So he just concentrated on like. The Poincaré conjecture problem, which he, when he took that, he took it after it was reframed by this mathematician called Richard Hamilton,

• 1:48:42Speaker 01

  which posed the problem in a way that it turned into this super like math Olympian problem with like perfect boundaries well defined. And that was perfect for Perriman to attack. And so he spent like seven years working on that. And then in two thousand and two, he started publishing those papers on archive. And people started jumping on that, reading those papers. And there was like a lot of excitement around that. Couple of years later, there were two researchers, I believe it was, they were from Harvard, that took Perriman's work. They sanded some of the edges and they republished that saying that, you know, based on Perriman's work, they were able to figure out the Poincaré conjecture.

• 1:49:25Speaker 01

  And then there was, at the time, at the International Conference of Mathematics in two thousand and six, I believe. That's when they were gonna give out the Fields Medal. There was a lot of debate of like, oh, who's like, who should get the credit for solving this big problem? And for Perriman, it like, it felt really sad that people were even considering that he was not the person that solved that. And the claims that those like researchers, when they published after Perriman, they were false claims that they were the ones. They just sanded a couple of edges, like Perriman did all the really hard work.

• 1:50:05Speaker 01

  And so just, just the fact that they doubted that Perriman had done that, like, was enough for him to say, I'm not, I'm not interested in this prize. And that was one of the reasons why he rejected the Fields Medal. Then he also rejected the Clay Prize. So the Poincaré conjecture was one of the millennium prizes. There was a million dollar prize associated with that problem. And that has to add to do with the fact that for them to attribute that prize, I think it had to be published on a journal.

• 1:50:34Lex Fridman?

  Yes.

• 1:50:34Speaker 01

  To prove. And again, Perriman's principles of like interfered here. And he also just didn't care about the money. He was like, Clay, I think, was a businessman and he's like, doesn't have to do anything with mathematics. I don't care about these. Like, that's one of the reasons why he rejected the.

• 1:50:52Lex Fridman?

  Yeah, there's, it's hard to convert into words, but at MIT.

• 1:50:59Lex Fridman?

  Distinctly aware of the distinction between when I enter a room, there's a certain kind of music to the way people talk when we're talking about ideas versus what that music sounds like when we're talking, when it's like bickering in the space of like, whether it's politics or funding or egos. It's a different sound to it. And I'm distinctly aware of the two. And I kind of sort of, to me personally, happiness was just like swimming around. The one that like is the political stuff or the money stuff and all that. Or egos.

• 1:51:44Lex Fridman?

  And I think that's probably what Promet is as well. Like the moment he senses there's any, as would it feels metal, like the moment you start to have any kind of drama around credit assignment, all those kinds of things. It's almost not that it's important who gets the credit. It's like the drama in itself gets in the way of the exploration of the ideas or the fundamental thing that makes science so damn beautiful.

• 1:52:08Speaker 01

  And you can really see that is also a product of that Russian school of like doing science. And you can see that, that, that people were, you know, during the Cold War, a lot of mathematicians, they were not making any money. They were doing math for the sake of math. Like for the intellectual pleasure of like solving a difficult problem.

• 1:52:29Lex Fridman?

  Yeah.

• 1:52:30Speaker 01

  And, you know, even, even if it was a flawed system and there were a lot of problems with, with that, there's these, they were able to, to actually achieve these. And there were a lot of, and Perlmutter for me is the perfect product of that. He just cared about like working on tough problems. He didn't care about anything else. It was just math. You know, pure math.

• 1:52:50Lex Fridman?

  Yeah, there's a like for the broader audience, I think another example of that is like professional sports versus Olympics. Especially in Russia, I've seen that clear distinction where because the state manages so much of the Olympic process in Russia, as people know with the steroids, yes, yes, yes. But outside of steroids thing is like the athlete can focus on the pure artistry of the sport, like, like not worry about the money, not just in the way they talk about it, the way they think about it, the way they define excellence versus like in the

• 1:53:32Lex Fridman?

  perhaps a bit of a capitalist system in United States with American football, with baseball, with basketball. So much of the discussion is about money. Now, of course, at the end of the day, it's about excellence and artistry and all of that. But when the culture is so richly grounded in discussions of money and

• 1:53:56Lex Fridman?

  sort of this capitalistic like merch and businesses and all those kinds of things, it changes the nature of the activity. And it's in a way that's hard again to describe in words, but when it's purely about the activity itself, it's almost like you quiet down all the noise enough to hear the signal, enough to hear the beauty. Like whenever you're talking about the money, that's when the marketing people come and the business people, the non creators come and they fill the room and there's and they create drama and they know how to create the drama, the noise, as opposed to the people who are truly excellent at what they do, the, the person in their arena, right?

• 1:54:38Lex Fridman?

  Like when you remove all the money and you just let that thing shine, that's when true excellence can, can come out. And that was of the few things that worked with the communist system in the Soviet Union, to me at least, as somebody who loves sport and loves mathematics and science, that worked well, removing the money from the picture.

• 1:55:04Lex Fridman?

  Yeah, not that I'm, not that I'm saying poverty is good for science. There's some level in which not worrying about money is good for science. It's a weird, I'm not exactly sure what to make of that because capitalism works really damn well. But it's, it's tricky how to find that balance.

• 1:55:25Speaker 02

  One Fields Medalist that is interesting to look at, and I think you mentioned it earlier, but it's Cedric Vilani, which is, might be the only Fields Medalist that is also a politician now. But so it's this, it's this brilliant French mathematician that won the Fields Medal. And, and after that, he decided that one of the ways that he could have, could have, you know, the biggest leverage kind of is in pushing science in the direction that he thinks science should go would be to, to try to go into politics. And so that's what he did and, and he has ran, I'm not sure if he has won any election.

• 1:56:07Speaker 01

  I think he's running for mayor.

• 1:56:08Speaker 02

  For mayor of Paris or something like that. But it's this brilliant mathematician that, that before winning the Fields Medal had only been just a brilliant mathematician. But, but after that, he decided to go into politics to, to try to, to have an impact and try to change some of the things that he, he would complain about before. So, so there's that component as well.

• 1:56:32Lex Fridman?

  Yeah, and I've always thought mathematics and science should be like, like James Bond would, in my eyes, I think be sexier if he did math. Like, we should, as a society, put excellence in mathematics at the same level as being able to kill a man with your bare hands. Like, those are both useful features, like, that's admirable. It's like, oh, like, that makes you like, that makes the person interesting. Like, being extremely well-read about history or philosophy, being good in mathematics, being able to kill a man with bare hands, those are all the same in my book. So, I think all are useful for action stars. And I think the society will benefit for, for giving more value to that. Like, one of the things that bothers me about American culture.

• 1:57:18Lex Fridman?

  Is the, I don't know the right words to use, but like the nerdiness associated with science. Like, like, and I don't think nerd is a good word in, in American culture, because it's seen as like weakness. There's like images that come with that. And it's fine, you could, you could be all kinds of shapes and colors and personalities, but like, to me, having sophisticated knowledge in science, being good at math, doesn't mean you're weak. In fact, it could be the very opposite. And so it's, it's an interesting thing, because it was very much differently viewed in the, in the Soviet Union.

• 1:58:03Lex Fridman?

  So I know for sure, as an existence proof, that it doesn't have to be that way, but it, um.

• 1:58:11Speaker 01

  I also feel like we lack a lot of role models. If you ask people to mention, to mention one mathematician that they know that is alive today, I think a lot of people would struggle to answer that question.

• 1:58:24Lex Fridman?

  And I also think, I love Neil Gras Tyson. Okay. But there is, uh, having more role models is good, like different kinds of personalities. He, he has kind of fun and, and it's very, it's like Bill Nye, the Science Guy, I don't know if you guys know him, so like that.

• 1:58:46Speaker 01

  That spectrum.

• 1:58:47Lex Fridman?

  That, yeah, but there, there's not, like Feynman is no longer there. Those kinds of personalities. Even Carl Sagan, yeah. Like a seriousness, that's like not playful, like.

• 1:59:01Speaker 01

  Not apologetic.

• 1:59:02Lex Fridman?

  Yeah, exactly. Not apologetic about being knowledgeable, like, like, in fact, like, the kind of energy where you feel, uh,

• 1:59:15Lex Fridman?

  Self-conscious about not having thought about some of these questions. Right? Just like when I see James Bond, I feel bad about that I don't have never killed a man. Like, I need to make sure I fix that. That's the way I feel. So the same way, I want to feel like that way. Well, Carl Sagan talks. I feel like I need to have that same kind of seriousness about science. Like, if I don't know something, I want to, I want to know it well. What about Terrence Tao? He's kind of a superstar. What are your thoughts about him?

• 1:59:44Speaker 01

  Drew is probably one of the most famous mathematicians alive today. And probably, I mean, regardless of like, is of course, he won a Fields Medal. He's a really smart and talented mathematician. It's also like a big inspiration for us, at least for some of the work that we do with Fermat's Library. So Terrence Tao is known for having, you know, a big blog and is pretty open about like his research. And he also, he tries to make his work as public as possible through his blog posts. In fact, there's a really interesting problem that got solved a couple of years ago.

• 2:00:27Speaker 01

  So Tao was working with, on a problem, on an Erdosz problem, actually. So Paul Erdosz was this mathematician from Hungary. And he was known for like, the Erdosz, for a lot of things. But one of the things that he was also known was for the Erdosz problem. So he was always like, creating these problems and usually associating prizes with those problems. And a lot of those problems are still open, like, and, and there will be, some of them will be open for like, maybe a couple of hundred years. And I think that's actually an interesting hack for him to collaborate with future mathematicians. You know, his, his name will, will keep coming up in, you know, for future generations. But so Tao was working on one of these problems called the Erdosz discrepancy.

• 2:01:11Speaker 01

  And he published a blog post on like, about that prob, about that problem. And he, he reached like a dead end. And then all of a sudden, there was this guy from, from Germany that wrote like a comment on his blog post saying, Okay, like some of the, so this problem is like a Sudoku like flavor and some of the machinery that we're using to solve Sudoku could be used here. And that was actually the key to solve the discrepancy problem. So there was a comment on his blog and I think that for me is an example of like how to do, again, going back to collaborative science online and the power that it has.

• 2:01:50Speaker 01

  But Tao is also like pretty public about like some of the struggles and of being a mathematician. Like and even he wrote about some of the unintended consequences of having extraordinary ability in a field. And he used himself as an example. When he was growing up, he was extremely talented in mathematics from a young age. Like Tao was a person, he won a medal in like one of the I M O's at the age, I think, was a gold medal at the age of 10 or something like that. And so he mentioned that when he was growing up, like and especially in college, when he was in a class that he enjoyed, it didn't, it just came very natural for him and he didn't have to work hard to just ace the class.

• 2:02:34Speaker 01

  And when he found that the class was boring, like it didn't work and he barely passed, barely passed, I think in college he almost failed two classes. And, and he was talking about that and how he brought those studying habits or like in existence of studying habits when he went to Princeton for his PhD. And in Princeton, when he, you know, started kind of delving into more complex problems and classes, he struggled a lot because he didn't have that, those habits, like he wasn't taking notes and he was, he wasn't studying hard when he, when he faced problems. And he almost failed out of his PhD, he almost failed his PhD exam.

• 2:03:16Speaker 01

  And it talks about like having this conversation with his advisor and the advisor pointing out like you're not, this is not working, you might have to get out of the program. And like how that was a kind of a turning point for him and, and like it was super important in his career. So I think Tao is also like this figure that apart from being just an exceptional mathematician, he's also pretty open about, you know, what, what it takes to, to, to be a mathematician and some of the struggles of these type of careers. And, and I think it's, that's super important.

• 2:03:48Lex Fridman?

  In many ways, he's contributed to open science and open humanity. He's being an open human.

• 2:03:55Speaker 01

  True.

• 2:03:56Lex Fridman?

  By communicating, Scott Aaronson is another in computer science world who's a very different style, very different style, but there's something about a blog that is authentic and real and just gives us a window into the mind and soul of these brilliant folks. So it's definitely a gift. Let me ask you about Fermat's Library on Twitter.

• 2:04:18Lex Fridman?

  Which, I mean, I don't know how to describe it. People should definitely just follow Fermat's Library on Twitter. I keep following and unfollowing Fermat's Library because it's so, it gives, when I follow, it leads me down rabbit holes often that are very fruitful, but anyway, so the posts you do on Twitter are just these beautiful, are things that reveal some beautiful aspects of mathematics. Is there, is there something you could say about the approach there?

• 2:04:59Speaker 01

  Yeah.

• 2:05:00Lex Fridman?

  And maybe broadly what you find beautiful about mathematics and then more specifically how you convert that into a rigorous process of revealing that in tweet form?

• 2:05:15Speaker 01

  That's a good point. I think there's something about math that, you know, a lot of the mathematical content and, you know, big papers or like little proofs, you know, has in a way sort of an infinite life. What I mean by that is that if you look at like Euclid's Elements, it's as valid today as it was when it was created like 2,000 years ago. And that's not true for a lot of other scientific fields.

• 2:05:42Speaker 01

  And so in regards to Twitter, I think there's also a very, it's a very underexplored platform from a learning perspective. I think if you look at content on Twitter, it's very easy to consume. It's very easy to read.

• 2:06:01Speaker 01

  And especially when you're trying to explain something, you know, we humans get a dopamine hit if we learn something new. And that's a very, very powerful feeling. And that's why, you know, people go to classes when you have a really good professor. You know, it's looking for those dopamine hits. And, and, and, and that's something that we try to explore when we're producing content on Twitter. Imagine if we, we could, if you would on a line to a restaurant, you could go, go to your phone to learn something new instead of social, uh, uh, going to a, um, you know, social network. And to just, and so, and I think it's very hard to, to sometimes to

• 2:06:43Speaker 01

  kind of provide that feeling because you need to sometimes digest content and, and put it, um, in a way, you know, that it feeds 280 characters. Um, and, and it requires a lot of sometimes time to do that, uh, even though it's easy to consume, it's hard to make. But once you are able to, to provide that Eureka moment to people, like, that's very powerful. They get that whole dopamine hit and like you create these feedback cycle and people come back for, for more. And in Twitter, compared to like, uh, you know, an online course or a book, you have a 0% dropout. So people will, will read the content, the content. So that it's, it's like, it's part of the creators, like the person that is creating the content.

• 2:07:25Speaker 01

  If you're able to actually get that feedback cycle, it's super, super powerful.

• 2:07:30Lex Fridman?

  Yeah, but some of this stuff is like, like, how the heck do you find that? And, and I don't know why it's so appealing. It, uh, like, uh, this is from a, what is it? A couple of days ago, I'll just read out the number. Two, three, four, five, six, seven, eight, nine is the largest prime number with consecutive increasing digits.

• 2:07:52Lex Fridman?

  I mean, that is so cool. That's like some weird like glimpse into some deep universal truth, even though it's just a number. I mean, that's like so arbitrary. Like, why, why is it so pleasant that that's a thing? But it is in some way, it's almost like it is a little glimpse at some much bigger like, um.

• 2:08:14Speaker 01

  And, and I think like especially if, if we're talking about science, there's something unique about you go. And with a lot of the tweets, you go sometimes from a state of not knowing something to knowing something. And that is very particular to science, science, math, physics. And that again is extremely addictive. And that's, that's how I, I, I, I feel about that. And, um.

• 2:08:37Speaker 01

  That's why I think people engage so much with our tweets and go into rabbit holes. And then they, you know, we start with prime numbers and all of a sudden you are spending hours reading number theory things and you go into Wikipedia and you lose a lot of time there.

• 2:08:52Lex Fridman?

  Well, the variety is really interesting, too. There's human things, there's physics things, there's like numeric things, like I just mentioned, but there's also more rigorous mathematical things. There's stuff that's tied to the history of math and the proofs and this visual, there's animations, there are looping animations that are incredible that reveal something. There's Andrew Wiles on being smart. This is just me now, like ignoring you guys and just going through your Twitter.

• 2:09:23Speaker 02

  Yeah, we're a bit like math drug dealers. We're just trying to get you hooked. We're trying to give you the hit and trying to get you hooked.

• 2:09:30Lex Fridman?

  Yes, some people are brighter than others, but I really believe that most people can really get to quite a good level of mathematics if they're prepared to deal with these psychological issues of how to handle the situation of being stuck.

• 2:09:43Speaker 01

  Yeah.

• 2:09:44Lex Fridman?

  Yeah, there's some truth to that.

• 2:09:45Speaker 01

  That's truth. I feel that's like really, it's some truth in terms of research and also about startups. You're stuck a lot of the time before you get to a breakthrough and it's difficult to endure that process of like being stuck because you're not trained to be in that position. I feel, yeah, that's.

• 2:10:05Lex Fridman?

  Yeah, most people are broken by the stuckness or like they're distraught. Like I've been very cognizant of the fact that more and more social media becomes a thing, like distractions become a thing, that that moment of being stuck is your mind wants to go do stuff that's unrelated to being stuck and you should be stuck. I'm referring to small stucknesses, like you're like trying to design something and it's a dead end, basically little dead ends, dead ends of programming, dead ends in trying to think through something and then your mind wants to like. Like, like, uh, this is the problem with this, like,

• 2:10:49Lex Fridman?

  work-life balance culture is like, take a break, like, as if taking a break will solve everything. Sometimes it solves quite a bit, but like, sometimes you need to sit in the stuckness and suffer a little bit. And then take a break. But you, you definitely need to be, and like, most people quit from that psychological battle of being stuck. And so, success is people who, who, who, uh, persevere through that.

• 2:11:16Speaker 02

  Yeah.

• 2:11:17Speaker 01

  Yeah. And, and in the creative process, that's also true. I was, the other day, I was, I think I was reading about, was this, um, what is his name? Ed Sheeran, like the musician.

• 2:11:25Lex Fridman?

  Yeah.

• 2:11:26Speaker 01

  Was talking a little bit about the creative process and using, was using this analogy of a faucet, like, where you, when you turn on a faucet, it's as like the dirty water coming out in the beginning. And you just have to, you know, keep trusting that at some point, your clean, clean, clear water will come out. But you have to endure that process, like, in the beginning, it's gonna be dirty water. And, and, and, and just, you know, embrace that.

• 2:11:50Lex Fridman?

  Yeah, actually, this, uh, the entirety of my YouTube channel and this podcast have been following that philosophy of dirty water. Like, I've been, you know, I do believe that. Like, you have to get all the crap out of your system first. And, uh, sometimes it's, it's all, sometimes it's all crappy work. I mean, I tend to be very self-critical, but I do think that quantity leads to quality for some people. It does for my, the way my mind works is like, just keep putting stuff out there, keep creating. And, uh, the quality will come as opposed to sitting there waiting, not doing anything until the thing seems perfect, because the perfect may never come.

• 2:12:32Speaker 01

  But just, just on like, on, on, on our Twitter, uh, like, profile, I really, and sometimes when you look on, on some of those tweets, they might seem like pretty, kind of, um, you know, why is this interesting? It's like so raw, uh, like, it's just a number. But I really believe that, especially with math or physics, it is possible to get everyone to love math or physics, even if you think you hate it. It's, it's not a function of the student or the person that is on the other side. I think it's just purely a function of like, how you explain, uh, hidden beauty that they hadn't realized before.

• 2:13:07Speaker 02

  It's not easy, but I think it's like a lot of the times is on like on the creator's side to to be able to like show that beauty to the other person. I think some of that is native to to humans. We just have that curiosity and you look at small toddlers and babies and like them trying to figure things out and there's just something that is born with us that we we want for that understanding. We want to figure out the world around us and and so, yeah, it shouldn't be like whether or not people are going are going to to enjoy it like I I I also really believe that everybody has that capacity to to fall in love with with math and physics.

• 2:13:47Lex Fridman?

  You mentioned startup. What do you think it takes to build a successful startup?

• 2:13:51Speaker 02

  Yeah, that it's what what Louise was saying that you need to to be able to endure being stuck and and I think the best way to put it is that startups don't have a linear reward function, right? You you oftentimes don't get rewarded for effort and and and most of our lives we go through these processes that do give you those small rewards for effort, right? In school, you study hard, generally you'll get a good grade and then you good you get like good grades ever or you get grades every semester and so you're you're slowly getting rewarded and pushed in the right direction.

• 2:14:33Speaker 02

  For for startups and startups are are not the only thing that is like this, but for startups, it's, you know, you can put in a ton of effort into something that and then get no reward for it, right? It's it's like like Sisyphus boulder where you're pushing that boulder up the mountain and and and you get to the top and then it just rolls all the way back down. And and so that's something that I think a lot of people are not equipped to deal with and can be incredibly demoralizing.

• 2:15:02Speaker 02

  Especially if that happens more than than a few times. And so, but I think it's absolutely essential to to power through it. Because by the nature of startups, it's oftentimes, you know, you're dealing with with with non-obvious ideas and things that that might be contrarian. And so you're gonna you're gonna run into into that a lot. You're gonna do things that are not gonna work out. And you need to be prepared to deal with that. But but if we're not coming out of college, you're you're just not equipped.

• 2:15:34Speaker 01

  Not sure if there is a way to train people to deal with those nonlinear reward functions. But it's definitely, I think, one of the most difficult things to, you know, about doing a startup. And also happens in research sometimes, you know, we're talking about the default state is being stuck. You just, you know, you don't like you try things, you get zero results, you close doors, you're constantly closing doors until you, you know, find something. And yeah, that is a big thing.

• 2:16:02Lex Fridman?

  What about sort of this point when you're stuck? There's a kind of decision whether you if you have a vision to persist through with this direction that you've been going along? Or what a lot of startups do or businesses is pivot. How do you decide whether like to give up on a particular flavor of the way you've imagined the design and to like adjust it or completely like alter it?

• 2:16:32Speaker 02

  I think that's a core question for startups that I've asked myself exactly. And like, I've never been able to come up with a great framework to make those decisions. I think that's really at the core of, yeah, out of a lot of the toughest questions that that people that's that started a company have to deal with.

• 2:16:53Speaker 01

  I think maybe the best framework that I I was able to figure out is like when you run out of ideas. You just, you know, you're exploring something, it's not working. You try it in a different angle, you know, you try a different business model. When you run out of ideas, like you don't have any more cards, just.

• 2:17:12Lex Fridman?

  Switch and yeah.

• 2:17:14Speaker 02

  It's not perfect. And because you also it's you have a lot of stories of startups is like. People kept pushing and then, you know, that paid off. And then you have philosophies is like fail fast and pivot fast. So it's, you know, it's hard to, you know, balance these two worlds and understand what is the best framework.

• 2:17:36Lex Fridman?

  And I mean, if you look at Fermat's library, you're maybe you can correct me, but it feels like you're in operating in a space. Where there's a lot of things that are broken and or could be significantly improved. So it feels like there's a lot of possibilities for pivoting. Or like, how do you revolutionize science? How do you revolutionize the aggregation, the the annotation, the commenting, the community around information of knowledge, structured knowledge? I mean, that's kind of what like Stack Overflow and Stack Exchange has struggled with. To come up with a solution and they've come up, I think, with an interesting set of solutions.

• 2:18:18Lex Fridman?

  That are also, I think, flawed in some ways, but they're much, much better than the alternatives. But there's a lot of other possibilities. If we just look at papers, as we talked about, there's so many possible revolutions and there are a lot of money to be potentially made in those revolutions. Plus, coupled with that, the benefit to humanity. And so like, you're sitting there. Like, I don't know how many people are legitimately from a business perspective, playing with these ideas. It feels like there's a lot of ideas here.

• 2:18:46Speaker 02

  True, there is.

• 2:18:48Lex Fridman?

  Are you right now grinding in a particular direction? Like, is there a like a five year vision that you're thinking in your mind?

• 2:18:55Speaker 02

  For us, it's more like a 20 year vision in the sense that we we've consciously tried to make the decision of. So we so we run Fermats as it's a side project and it's a separate in the sense like it's not what we're working on full time. And but our thesis there is that. We actually think that it's that's a good thing, at least for for this stage of Fermat's library. And also because some of these projects, you just, if you're coming from a start from a startup framework, you probably try to.

• 2:19:35Speaker 02

  Try to fit every single idea into something that can change the world within three to five years. And there's just some problems that take longer than that. Right. And so, you know, we're talking about Archive and I'm very doubtful that you could grow like Archive into what it is today, like within two or three years. No matter how much money you throw at it, there's just some things that can take longer. But you need to be able to power through the time that it takes. But if you look at it as, okay, this is a company, this is a startup, we have to grow fast, we have to raise money, then, then sometimes you might forego those ideas because of that, because they don't very well fit into the typical startup framework.

• 2:20:19Speaker 02

  And so for us, for Motts, it's something that we're okay with growing, with having it grow slowly and maybe taking many years. And, and, and that's why we think it's, it's not a bad thing that it is a side project, because it makes it much more acceptable in a way and that to, to, to be able to be okay with that.

• 2:20:40Lex Fridman?

  That said, I think what happens is if you keep pushing new little features, new little ideas, I feel like there's like, certain ideas will just become viral.

• 2:20:51Lex Fridman?

  Like, and then you just won't be able to help yourself, but it'll revolutionize things. It feels like there needs to be, not needs to be, but there's opportunity for viral ideas to change science.

• 2:21:04Speaker 02

  Absolutely.

• 2:21:05Lex Fridman?

  And maybe we don't know what those are yet. It might be a very small kind of thing.

• 2:21:09Speaker 02

  Maybe you don't even know if, should this be a for-profit company doing these?

• 2:21:13Lex Fridman?

  That's the Wikipedia question.

• 2:21:15Speaker 02

  Yeah. There's a, there are a lot of questions, like really fundamental questions about this space that we've, we've talked about. I mean, you take Wikipedia and you try to run it as a startup and by now we'd have a paywall, you'd be paying 9.99 a month to, to read more than 20 articles.

• 2:21:30Lex Fridman?

  I mean, that's, that's one view.

• 2:21:32Speaker 02

  Yeah.

• 2:21:32Lex Fridman?

  The other, the ad-driven model, so they rejected the ad-driven model.

• 2:21:38Lex Fridman?

  I don't know if we could, I mean, this is a difficult question. You know, if Archive was supported by ads. I don't know if that's bad for Archive. If Fermat's Library was supported by ads. I don't know, I don't. I'm not, it's not trivial to me. I'm, unlike, I think, a lot of people. I'm not against advertisements. I think ads, when done well, are really good. I think the problem with Facebook and all the social networks are the way, the lack of transparency around the way they use data and the lack of control the users have over their data. Not the fact that data is being collected and used to sell advertisements. It's a lack of transparency, lack of control. If you, if you do a good job of that, I feel like it's really a nice way to make stuff free.

• 2:22:23Speaker 01

  Yeah, it's like Stack Overflow, right? I think they've done a good job with that. Even though, as we said, like, they're capturing very little of the value that they're putting out there. Right? But, but it makes it a sustainable company and, and they're providing a lot of, it's a fantastic and very productive community.

• 2:22:43Lex Fridman?

  Let me ask a ridiculous tangent of a question. Luis, you wrote a paper on Game of Thrones, Battle of Winterfell. Just as a side, I'm sorry, I noticed. I'm sure you've done a lot of ridiculous stuff like this. I just noticed that particular one. By ridiculous, I mean ridiculously awesome. Can you describe the, the approach in this work, which I believe is a legitimate publication?

• 2:23:07Speaker 01

  So going back to the original, like, when we were talking about the backstory of, of papers and the importance of that. So this is actually, you know, this is when the last season of the, the show was airing. This was during a company lunch. We, there was, in, in the last season, there's the, there's a really big battle against the, the forces of evil and the, you know, the forces of good. And it's called the Battle of Winterfell. And in this battle, there are like these two armies. And there's a very particular thing that they have to take into account is that in the army of dead, like, if someone dies in the army of the living.

• 2:23:48Speaker 01

  Uh like that person is gonna, you know, be a reborn as a soldier in the army of the dead.

• 2:23:55Lex Fridman?

  Yes.

• 2:23:55Speaker 01

  And so that was an important thing to take into account.

• 2:23:58Lex Fridman?

  And the initial conditions, as you specified, it's about a hundred thousand on each side.

• 2:24:02Speaker 01

  Exactly. So I was able, I was able to like, based on some images or like on previous episodes, to figure out what was the size of the armies. And so what I want, what we wanted to, what we were theorizing was like, how many soldiers does like a soldier on the army of the living has to kill in order for them to be able to destroy the army of the dead without like losing? Because every time one of the good soldiers dies, gonna turn into like the other side. And so it's, so we were theorizing that and I wrote a couple of differential equations. And I was able to figure out that based on the size of the armies, I think, I think was the ratio had to be like 1.7.

• 2:24:42Speaker 01

  So it had to kill like 1.7 soldiers of like the army of the dead in order for them to win the battle.

• 2:24:48Lex Fridman?

  Well, yeah, that's, that's science. It is, it's, it's most powerful. And this is also somehow a pitch for like a hiring pitch in a sense like this is the kind of important science you do at once.

• 2:25:03Speaker 01

  Exactly. Well, it turned out to be, you know, as, as, as for people that have watched these shows is like, they know that every time you try to predict something that is gonna happen, it's gonna, you're gonna fail miserably. And that's what happened. So it was not, not at all important for, for the show. But yeah, we ended up like putting that out and there was a lot of people that shared that. And I think with some like elements of the, of the show, the cast of the show, that actually retweeted that and shared that at first. So it was fun.

• 2:25:30Lex Fridman?

  I would love if this kind of calculation happened like during the making of the show or, or, you know, I love it like in, for example, I now know Alex Garland, the director of Ex Machina. And I love it. He doesn't seem to be some, not many people seem to do this, but I love it when directors and people who wrote the story really think through the technical details. Like whether it's knowing like how things, even if it's science fiction, if you were to try to do this, how would you do this? Like Stephen Wolf from his son were. We're collaborating with the movie Arrival in designing the alien language,

• 2:26:14Lex Fridman?

  how you communicate with the aliens. Like, how would you really have a math-based language that could span the alien and being and the human being? So I love it when they have that kind of rigor.

• 2:26:29Speaker 01

  The Martian was also big on that. Like, the book and the movie was all about, like, can we actually... Is this plausible? Can this happen? It was all about that.

• 2:26:38Speaker 02

  And that can really bring you in. Like, sometimes the small details. I mean, the guy that wrote the Martian book is another book that is also filled with those, like, things that, when you realize that, okay, these are grounded in science, can just really bring you in.

• 2:26:55Speaker 01

  Yeah.

• 2:26:55Speaker 02

  Like, he has a book about a colony on...

• 2:26:59Speaker 01

  The colony on the moon. And he goes about, like, all the details that would, you know, be required about setting up a colony in the moon and, like, things that he wouldn't think about, like, the fact that they would, you know, it's hard to bring, like, air to the moon, so they wouldn't, like, how do you make that breathable, that environment breathable? You need to bring oxygen. But, like, you probably wouldn't bring nitrogen. So what you do is, like, instead of having an atmosphere that is 100% oxygen, you, like, decrease the pressure so that you have the same ratio of oxygen on Earth, but, like, lowering the pressure here. And so, like, things like water boils at a lower temperature. So people would have coffee, and the coffee would be colder.

• 2:27:44Speaker 01

  Like, there was a problem in this environment in the moon. So, like, and these are, like, small things in the book. But I studied physics, so, like, when I read these, that throws me into, like, tangents, and I start researching that. And it's like, I really like to read books and watch movies when they go to that level of detail about science.

• 2:28:08Speaker 02

  Yeah. I think Interstellar was one where they also consulted heavily with a number of...

• 2:28:11Speaker 01

  Yeah, yeah, yeah.

• 2:28:12Speaker 02

  I think even resulted in...

• 2:28:13Speaker 01

  In a couple of papers.

• 2:28:14Speaker 02

  A couple of papers about, like, the black hole visualizations and...

• 2:28:20Speaker 02

  Yeah, but there is even more examples of interesting science around like these fantasy. We were reading at some point like these guys that were trying to figure out if the Tolkien's Middle Earth, if it was round, if it was like a sphere.

• 2:28:37Speaker 01

  Yeah.

• 2:28:38Speaker 02

  Like a flat.

• 2:28:39Speaker 01

  Based on the map.

• 2:28:40Speaker 02

  Based on the map and some of the references in the in the books and so.

• 2:28:46Speaker 01

  Yeah, we actually, I think we tweeted about that.

• 2:28:48Speaker 02

  Yeah, we did.

• 2:28:49Speaker 01

  Based on the distance between the cities, you can actually prove that that could be like a map of a sphere or like a spheroid and you can actually calculate the radius of that planet.

• 2:29:03Lex Fridman?

  That's fascinating. I mean, yeah, that's fascinating, but there's something about like calculating the number like exactly the calculation you did for the Battle of Winterfell is something fascinating about that because that's not like being, that's very mathematical versus like grounded in physics. And that's really interesting. I mean, that's like injecting mathematics into fantasy. There's something magical about that.

• 2:29:35Speaker 01

  And that for me, that's why I think it's also when you look at things like Fermat's Last Theorem, like problems that are very kind of self-contained and simple to state. I think like that's the same with that paper. It's very easy to understand the boundaries of the problem, you know? And that for me, that's why those, that's why math is so appealing. And those like problems are also so appealing to the general public. It's not that they look simple or that people think that they're easy to like solve, but I feel that a lot of the times they are almost intellectually democratic because everyone understands the starting point. You know, you look at Fermat's Last Theorem, everyone understands like this is the universe of the problem.

• 2:30:20Speaker 01

  And the same maybe with that paper, everyone understands, okay, these are the starting conditions. And, and yeah, that the fact that it becomes intellectually. Actually Democrat and I think that's a huge motivation for people. And that's why so, so many people gravitate towards these like Rema hypotheses or Fermat's last theorem. Or that simple paper, which is like just one page, it was very simple.

• 2:30:42Lex Fridman?

  And I just talked to somebody, I don't know if you know who he is, Jaco Willink, who is this person who among many things loves military tactics. So he would probably either publish a follow on paper, maybe you guys should collaborate. But he would see the fundamental, the basic assumptions that you started that paper with as flawed. Because you know, there's like dragons too, right? There's like, like you have to integrate tactics because not, it's not, it's not a homogeneous system. It's not.

• 2:31:13Speaker 01

  I don't take into account the dragons and like.

• 2:31:15Lex Fridman?

  And he would say tactics fundamentally change the dynamics of the system. And so like.

• 2:31:20Speaker 01

  That's what happened.

• 2:31:23Lex Fridman?

  So, uh, yeah, so at least from a scientific perspective, he was right, but he never published. So there you go. Uh, let me ask the most important question. You guys are from Portugal, both.

• 2:31:34Speaker 01

  Yeah.

• 2:31:34Lex Fridman?

  Portugal. Uh, so who is the greatest soccer player, footballer of all time?

• 2:31:41Speaker 01

  Yeah, I think we're a little bit biased on this topic, but I, I mean.

• 2:31:45Lex Fridman?

  Maradona?

• 2:31:47Speaker 01

  I, I have, I have a huge, I have a tremendous respect for, for what.

• 2:31:52Lex Fridman?

  Here we go. This is the political.

• 2:31:56Speaker 01

  We can convince you. I, I, I, I mean, I have tremendous respect for what Ronaldo has achieved in, in his career. And, and I think soccer is one of those sports where I think you can get to maybe be one of the best players in the world. We, if you just have like natural talent and even if you don't put a lot of hard work and discipline into soccer, you can be one of the best players in the world. And I think Ronaldo is kind of like, of course, he's naturally talented, but he also.

• 2:32:22Lex Fridman?

  Cristiano Ronaldo should say the, the football from.

• 2:32:25Speaker 01

  Exactly, from Portugal and, and not, uh, not the Brazilian in this case. And so, um, and Ronaldo put like came from nothing. He is known from being probably one of the hardest working athletes in the game. And, and I see that sometimes a lot of these discussions about the best player, a, a lot of people trend, tend to gravitate towards like, um, you know, this person is naturally talented and the other person has to work hard. And so, and so as if it was bad if he had to work hard to, to be good at something. And I think that, you know, the, the. I think so many people fall into that trap. And the reason why so many people fall into that trap is because if you're saying that someone

• 2:33:07Speaker 01

  is good and achieved a lot of success by working hard as opposed to achieving success because he has some sort of God given natural talent, then you can't explain why the person was born with that. What does it tell you about you? It tells you that maybe if you work hard on a lot of fields, you could have, could accomplish a lot of great things. And I think that's hard to digest for a lot of people.

• 2:33:30Lex Fridman?

  And in that way Ronaldo is inspiring that.

• 2:33:33Speaker 01

  I think so.

• 2:33:33Lex Fridman?

  So you find hard work inspiring, but he's, he's way too good looking. That's the, I don't like him probably.

• 2:33:41Speaker 01

  No, I like the part of the hard work and like of him being like one of the hardest working athletes in soccer.

• 2:33:47Lex Fridman?

  So he is to you the greatest of all time? Is he up there? Is he, would be number, okay.

• 2:33:52Speaker 01

  I agree. Or harder.

• 2:33:55Lex Fridman?

  Well, I definitely disagree. I mean, I, I like him very much. He works hard. I admire, I admire, you know, um, would like, he's incredible, uh, a goal scorer, right? Um, but I, so, so first of all, Leo Messi, and there was some confusion because I've kept saying Maradona is my favorite player, but I, I think, I think Leo has surpassed them. So, uh, um, it's Messi, then Maradona, then Pelé for me. But the, the reason is, is, um, there's certain aesthetic definitions of beauty that

• 2:34:35Lex Fridman?

  I admire, whether it came by hard work or through God given talent or through anything. And it doesn't, it doesn't really matter to me. There's certain aesthetic, like genius, when I, when I see it to me, and especially, it doesn't have to be consistent. It is in the case of Messi, in case of Ronaldo, but just even moments of genius, which is where Maradona really shines. It's a.

• 2:35:00Speaker 01

  Even if that doesn't translate into like results and goals being scored.

• 2:35:04Lex Fridman?

  Right, right. And that's the challenge. I'm like, I did that.

• 2:35:09Lex Fridman?

  Because that's where people that tell me that Leo Messi is never, even on strong teams have led his, the national team, people as part of the World Cup, right? That's really important. And to me, no, it's the moment, like, winning to me was never important. What's more important is the moments of genius. And, but you're talking to the human story. And yeah, Cristiano Ronaldo definitely has a beautiful human story.

• 2:35:38Speaker 01

  Yeah. And I think you can't, for me, it's hard to decouple those two. I don't just look at, you know, the list of achievements, but I like how he got there and how he keeps pushing the boundaries at like almost forty.

• 2:35:52Lex Fridman?

  Yeah.

• 2:35:52Speaker 01

  And how that sets up an example. Like, maybe ten years ago, I wouldn't have ever imagined that like, one of the top players in the world could be a top player at like thirty-seven or.

• 2:36:01Lex Fridman?

  But so, and there's an interesting, the human story is really important, but like, if you look at Ronaldo, he's like, he's somebody like kids could aspire to be. But at the same time, I also like Maradona, who like is a tragic figure in many ways. Like, the, you know, the drugs, the temper, all of those things. That's beautiful, too. Like, I don't necessarily think, to me, firstly, the flaws are beautiful, too, in athletes. I don't think you need to be perfect.

• 2:36:34Speaker 01

  I agree.

• 2:36:34Lex Fridman?

  From a personality perspective, those flaws are also beautiful. So, but yeah, there is something about hard work, and there's also something about the being an underdog and being able to carry a team.

• 2:36:50Lex Fridman?

  That's an argument for Maradona. I don't know if you can make that argument for Messi and Ronaldo either, because they've all played on superstar teams for most of their lives. So I don't know how.

• 2:37:03Lex Fridman?

  You know, it's difficult to know how they would do when they had to work like did what Maradona had to do to carry a team on his shoulders.

• 2:37:14Speaker 01

  True.

• 2:37:15Lex Fridman?

  And Pele did as well, depending on the context.

• 2:37:19Speaker 01

  Maybe you could argue that with the Portuguese national team, but we have a good team. Yeah, but maybe what Maradona did with Naples and a couple other teams, it's incredible.

• 2:37:30Speaker 02

  It speaks to the beauty of the game that, you know, we're talking about all these different players that have, or especially, you know, if you're comparing Messi and Ronaldo that have such different, you know, styles of play and also even their bodies are so different. And but these two very different players can be at the top of the game. And that's not, that's the, there are not a lot of other sports where you where you have that, you know, like you have kind of a mental image of a basketball player and like the the top basketball players kind of fit that mental image and they look a certain way. And but for soccer, there's some, there's, it's not so much like that.

• 2:38:11Speaker 02

  And that's, I think that's, that's beautiful, but that really adds something to the sport.

• 2:38:17Lex Fridman?

  Well, do you play soccer yourself? Have you played that in your life? What do you find beautiful about the game?

• 2:38:23Speaker 01

  Yeah, I mean, it's one of the, I'd say it's the biggest sport in Portugal. And so growing up, we played a lot.

• 2:38:28Lex Fridman?

  Did you see the paper from DeepMind? I didn't look at it, where they're like doing some analysis on soccer strategy.

• 2:38:36Speaker 02

  Interesting.

• 2:38:37Speaker 01

  I saved that paper. I haven't read it yet. It's actually, I, when I was in college, I actually did some research on on applying

• 2:38:49Speaker 01

  machine learning and statistics in sports. And in our, in our case, we're doing it for basketball. But

• 2:38:57Speaker 02

  What they're effectively trying to do was, have you ever watched Moneyball? So they're trying to do something similar, right? Taking that, in this case, basketball, taking a statistical approach to basketball. The interesting thing there is that baseball is much more about having these discreet events that happen kind of in similar conditions, and so it's easier to take a statistical approach to it, whereas basketball, it's a much more dynamic game. It's harder to measure, it's hard to replicate these conditions, and so you have to think about it in a slightly different way. And so we were doing work on that and working like with the Celtics to analyze the data that they had.

• 2:39:40Speaker 02

  Like they had these cameras in the arena, they were tracking the players, and so they had a ton of data, but they didn't really know what to do with it. And so we were doing work on that. And soccer is maybe even a step further. It's right, it's a game where you don't have as many. In basketball, you have a lot of field goals, and so you can measure success. Soccer, it's right, it's more of a process almost, where it's like you have a goal like or two in a game.

• 2:40:07Lex Fridman?

  In terms of metrics, I wonder if there's a way, and I've actually have thought about this in the past, never coming up with any good solution, if there's a way to definitively say whether it's Messi or not, they're the greatest of all time, like honestly, sort of measure.

• 2:40:20Speaker 02

  Interesting.

• 2:40:21Lex Fridman?

  Like convert the game of soccer into metrics, like you said, baseball, but like those moments are genius, like, you know, if it's just about goals or passes that led to goals, that feels like it doesn't capture the genius of the play.

• 2:40:36Speaker 02

  There'll be like, you know, like, like you kind of do, you have more metrics, for instance, in chess, right? And you can try to understand how hard of a move that was, you know, there's like Bobby Fischer has this move that like, that it's, I think it's called the move of the century, where you have to go so deep into the tree to understand that that was the right move, and you can quantify how hard it was. So it'd be interesting to try to think of those type of metrics, but say, yeah, for soccer.

• 2:41:05Lex Fridman?

  And computer vision unlocks some of them. That for us, that's that's one possibility.

• 2:41:08Speaker 01

  I have a cool idea, a computer vision product like that you could build for soccer.

• 2:41:13Lex Fridman?

  Let's go. I'm taking notes.

• 2:41:15Speaker 01

  If you could detect the ball and like imagine that it seems like totally doable right now, but like if you could detect when the ball enters one of the goals and like just had like, you know, a crowd cheering for you when you're playing soccer with your friends every time you score a goal. You had like the the Champions League song going on.

• 2:41:36Lex Fridman?

  Yeah.

• 2:41:36Speaker 01

  And like having that, like you go play soccer with your friends, you just turn that on and there's like a computer vision like program analyzing.

• 2:41:42Lex Fridman?

  The ball.

• 2:41:43Speaker 01

  Detects the ball every time there's a goal, like if you miss, like there's a, you know, the fans are reacting to that.

• 2:41:48Lex Fridman?

  And then.

• 2:41:49Speaker 01

  Should be pretty simple by now. It's like, I think there's an opportunity there. Just throwing that.

• 2:41:54Lex Fridman?

  I'm gonna go all out. But by the way, I did, I've never released, I was thinking of just putting on GitHub, but I did write exactly that, which is the trackers for the players. For the for the bodies of the player. This is the hard part, actually. The detection of player bodies and the ball is not hard. What's hard is very like robust tracking through time of each of those. So like, so I wrote a tracker that's pretty damn good. This is.

• 2:42:21Speaker 01

  Is that is that open source? You open?

• 2:42:23Lex Fridman?

  I know, I've never released it.

• 2:42:25Speaker 01

  Interesting.

• 2:42:25Lex Fridman?

  Cause I thought like, I need to, I would. This is the perfection thing, cause I knew it was going to be like, it's gonna pull me in and and it wasn't really that done. And so I've never actually been a part of a GitHub project where it's like really active development. And I didn't want to make it, I knew there's a non-zero probability that will become my life for like a half a year. That could just how much I love soccer and all those kinds of things. And and ultimately, it will be all for just the the joy of analyzing the game, which I'm all for.

• 2:43:00Speaker 01

  I remember you also, like, in one of the episodes, you mentioned that you did also a lot of eye tracking analysis on like Joe Rogan's.

• 2:43:06Lex Fridman?

  That was the that was the research out of my life.

• 2:43:08Speaker 01

  Interesting.

• 2:43:09Lex Fridman?

  Yeah.

• 2:43:09Speaker 01

  And you have that library, right? You you kind of downloaded all the episodes.

• 2:43:12Lex Fridman?

  Yep. Allegedly, and of course I didn't, if you're a lawyer and listening to this.

• 2:43:17Speaker 01

  No, it is. I was listening to the episode where you mentioned that and I was actually, there was something that I might ask you for access to that, to allegedly that library. But I was doing some, not regarding eye tracking, but I was playing around with analyzing the distribution of silences on one of the Joe Rogan episodes. So like, I did that for the Elon conversation, where it's like, you just take all the silences, like after Joe asked the question and Elon responded, and you plot that distribution and like, and see how that looks like.

• 2:43:53Lex Fridman?

  Yeah, I think there's a huge opportunity, especially with long form podcasts, to do that kind of analysis, bigger than Joe.

• 2:44:00Speaker 01

  Exactly. It has to be a fairly unedited podcast, so that you don't cut the silences.

• 2:44:05Lex Fridman?

  So one of the benefits I have, like, doing this podcast is like, what we're recording today is there's individual audio being recorded. So like, I have the raw information. When it's published, it's all combined together, and individual video feeds. So even when you're listening, which I usually do, I only show one video stream, I'll know, I can track your blinks and so on. But ultimately, the hope is you don't need that raw data, because if you don't need the raw data for whatever analysis you're doing, you can then do a huge number of podcasts, because it's quickly growing now, the number, especially comedians. There's quite a few comedians with long form podcasts, and they have a

• 2:44:50Lex Fridman?

  lot of facial expressions, they have a lot of fun and all those kinds of things, and it's prone for analysis.

• 2:44:55Speaker 01

  Yeah, there's so many interesting things that you... That idea actually sparked because I was watching a Q and A by Steve Jobs, and I think it was at MIT, and then like, people did a talk there, and then the Q and A started, and people started asking questions that, I was working while listening to it, and like, someone asked a question, and he goes like, on a 20 second silence before answering the question. Like, I had to check if the video hadn't paused or something. And I was thinking about like,

• 2:45:27Speaker 01

  If that is a feature of a person, like how long on average you take to respond to a question? And if it's like

• 2:45:33Lex Fridman?

  Oh, that's fascinating.

• 2:45:34Speaker 01

  As to do with like how thoughtful you are and if that changes over time.

• 2:45:38Lex Fridman?

  Oh, but it also could be this really fascinating metric because it also could be. It's certainly a feature of a person, but it's also a function of the question. Like if you normalize to the person, you can probably infer a bunch of stuff about the question. So it's a nice flag, like it's a really strong signal, the length of that silence relative to the usual silence they have. So one, the silence is a measure of how thoughtful they are. And two, the particular silence is a measure how

• 2:46:06Speaker 01

  Thoughtful the question was.

• 2:46:07Lex Fridman?

  Thoughtful the question was. It's really interesting. I mean, yeah.

• 2:46:09Speaker 01

  Yeah, I just analyzed Elon's episode, but I think there's like room for exploration there.

• 2:46:17Speaker 02

  I feel like the average for comedians would be like, I mean, the time would be so small because you're trained to like, I would, I would think you're reacting to hecklers, you're reacting to all sorts of things. You have to be like so quick.

• 2:46:28Lex Fridman?

  Maybe, maybe. Yeah, but some of the greatest comedians are very good at sitting in the silence. I mean, there, there's Louis CK. They play with that. Cause you have a rhythm and like Dave Chappelle, a comedian who did Joe's show recently. He has a, especially when he's just having a conversation, he does long pauses. It's kind of cool. Is it, it's one of the ways to have people hanging in your word is to play with the pauses. To play with the silences and the emphasis and like mid-sentence, there's a bunch of different things that

• 2:47:08Lex Fridman?

  it'd be interesting to really, really analyze, but still soccer to me is that, that, that one was fascinating. Just, I just want a conclusive definitive statement about, it's like, there are so many

• 2:47:21Lex Fridman?

  soccer highlights of both Messi and Ronaldo. I just feel like the raw data is there.

• 2:47:27Speaker 02

  Definitive state.

• 2:47:31Lex Fridman?

  Cause you don't have that with Pelé and Maradona.

• 2:47:33Speaker 02

  Just, yeah, true.

• 2:47:35Lex Fridman?

  But here's a huge amount of high dev data, then the annoying, the difficult thing. And then this is really hard for tracking. And this is actually where I kind of gave up. Well, I didn't really give much effort, but I gave up.

• 2:47:49Lex Fridman?

  The way that highlights or usually football matches are filmed is they switch the camera. So they'll they'll do a different switch of perspective. So you have to. It's a really interesting computer vision problem. When the perspective is switched, you still have a lot of overlap about the players. But the perspective is sufficiently different that you have to like recompute everything. So I there there's two ways to solve this. So one is doing it the full way where you're constantly doing the slam problem. You you're doing a 3D reconstruction the whole time and projecting into that 3D world. But you could also there could be some hacks. Then I wonder like some trick where you can hop like when the perspective shifts.

• 2:48:32Lex Fridman?

  Do a high probability tracking hops from one object to another. But I I thought especially in exciting moments when when uh when you're passing players. Like you're doing a single ball dribble across players and you switch perspective, which is when they often do when you're making a run on goal. If you switch a perspective, it's it feels like that's going to be really tricky to get right automatically.

• 2:48:59Speaker 02

  But in that case, for instance, I feel like if somebody released that data set where it's like you just have all like these this data set. A massive data set of all these games from from say Ronaldo and Messi like and just you just add that in like whatever CSV format. And some some publicly available data set like that. I feel like people would just there there would be so many cool things that you could do with it. And you just set it free and then like the world would like do its thing. And then like interesting things would come out of it.

• 2:49:28Lex Fridman?

  By the way, I have this data set. So the two the two things I I've did of this scale is soccer. So it's body pose and ball tracking for soccer. And then I try it's pupil tracking and blink tracking for it was Joe Rogan and a few other podcasts that I did. So those are the two data sets I have.

• 2:49:48Speaker 02

  Did you analyze any of your podcasts?

• 2:49:52Lex Fridman?

  No, I I think I really started doing this podcast after after doing that work. And it's difficult to.

• 2:50:02Lex Fridman?

  Maybe I'd be afraid of what I find. I'm already annoyed with my own voice and video, like editing it. But perhaps that's the honest thing to do. Because one useful thing about doing computer vision about myself is like, I know what I was thinking at the time. So you can start to like, connect the particular, the behavioral peculiarities of like, the way you blink, the way you squint, the way you close your eyes. Like, talking about details, there's, it's like, for example, I just closed my eyes. Is that a blink or no?

• 2:50:38Speaker 02

  Mm hmm.

• 2:50:39Lex Fridman?

  Like, figuring that out in terms of timing, in terms of the blink dynamics, is tricky. It's very doable. I think there's universal laws about what is a blink and what is a closed eye and all those things. Plus makeup and eyelashes. I actually have annoyingly long eyelashes. So I remember when I was doing a lot of this work, I would cut off my eyelashes. Which, when like, especially, it was funny, like, female colleagues were like, what the fuck are you doing? Like, no, keep the eyelashes. But, because it got in the way, made the computer vision a lot more difficult, but.

• 2:51:15Speaker 02

  Super interesting topics. Yeah, but speaking about the, one, still on the topic of data sets for sports, there's one, one paper, and I actually annotated it on Fermat, and it was published in 90s? 90s, I believe, 90s or 80s, I forget. But the researcher was effectively looking at the hot end phenomena in basketball, right? So whether like, the fact that you just made a field goal, if, you know, if on your next attempt, if you're more likely to make it or not. And it was super interesting because, I mean, he polled like, I think 100 undergrads,

• 2:51:57Speaker 02

  and I think from Stanford and Cornell, and asking people like, do you, you think that's, that you have a higher likelihood of making your free throw if you just, just made one? And I think it was like 68, 68% said yes, they believed that. And then he looked at the data. And this was back in, as I said, like a few decades ago. And so I think he had a data set of about, he looked at it specifically for free throws and he had a data set of about 5,000 free throws. And effectively, what he found was that specifically in the case of free throws, he didn't, for the aggregate data, he didn't find that, he couldn't really

• 2:52:39Speaker 02

  spot that correlation, that hot end correlation. So if you made the first one, you weren't more likely to make the second one. What he did find was that they were just better at the second one. Because you just got like maybe a tiny practice and you just, you attempted once and then, and then you're going to be better at the next one. And then I, then I went, and there's a data set on Kaggle that has like 600,000 free throws. And I reran the same computations and confirmed, like you can see a very clear pattern, that they're just better at their second free throw.

• 2:53:14Lex Fridman?

  That's interesting. Because I think there's similar, that kind of analysis is so awesome. Because I think with tennis, they have like, like a fault, like when you serve, they have analysis of like, are you most likely to miss the second serve if you missed the first, obviously. Yeah, I think that's the case. So that integrates, that's so cool when psychology is converted into metrics in that way. And in sports, it's especially cool because it's such a constrained system that you can really study human psychology because it's repeated, it's constrained, so many things are controlled, which is something you rarely have in, in the wild psychological experiments. So it's cool. Plus, everyone loves it. Like, sports is really cool to analyze.

• 2:53:58Speaker 02

  People actually care about the results.

• 2:54:01Lex Fridman?

  Yeah. I still think, well, like, I, I will definitely publish this work on Messi versus Ronaldo and

• 2:54:09Speaker 02

  I'd love to read it.

• 2:54:09Lex Fridman?

  Objective, fully objective.

• 2:54:11Speaker 02

  I'd love to peer review.

• 2:54:15Lex Fridman?

  Yeah, this is very true. This is not past peer review. Let me ask sort of an advice question to, to young folks. You've explored a lot of fascinating ideas in your life. You built a startup, worked on physics, worked in computer science. What advice would you give to young people today in high school, maybe early college, about life, about career, about science and mathematics?

• 2:54:44Speaker 01

  I remember like I read, like I remember reading that

• 2:54:50Speaker 01

  Poncaria was once asked by a French journal about his advice for young people and what was his teaching philosophy. And he said that like, one of the most important things that parents should teach their kids is how to be enthusiastic in regards to like the mysteries of the world. And that he said like, striking that balance was actually one of the most important things between like in education, you know, you want to have your kids be enthusiastic about the mysteries of the world, but you also don't want to traumatize them. Like if you really force them into something. And I think like especially if you're young, I think you should be curious.

• 2:55:28Speaker 01

  And I think you should explore that curiosity to the fullest, to the point where you even become almost as an expert on that topic. And now, and you might start with something that is small, like you might start with, you know, you're interested in numbers and how to factor numbers into primes. And then all of a sudden you go and you're like lost in number theory and you discover cryptography. And then all of a sudden you're buying Bitcoin. And I, and I think you should do this. You should really try to fulfill this curiosity and you should live in a society that allows you to fulfill this curiosity, which is also important. And I think you should do this, not to get to some sort of status or fame or money.

• 2:56:11Speaker 01

  But I think this is the way, this iterative process, I think this is the way to find happiness. And, and I think this is also allows you to find the meaning for your life. I think it's all about like being curious and being able to fulfill that curiosity and that path to fulfilling that, your curiosity.

• 2:56:30Lex Fridman?

  Yeah, the, the start small, let the fire build is kind of interesting way to think about it.

• 2:56:35Speaker 01

  And you never know where you're going to end up. It's, it's like, for us, it's just a really good example. We started like by doing this as an internal like thing that we did in the company. And then we started putting out there and now a lot of people follow it and know about it. And so.

• 2:56:52Lex Fridman?

  And you still don't know where from our library is going to end up, actually.

• 2:56:55Speaker 01

  True, exactly. So, um, yeah, I think that would be my piece of advice with very limited experience, of course, but.

• 2:57:03Lex Fridman?

  Yeah, I agree. I agree.

• 2:57:06Lex Fridman?

  I mean, is there something in from particular, Joel, from the computer science versus physics perspective? Do you regret not doing physics? Do you regret not doing computer science? Which one is the the wiser, the better human beings? This is Messi versus Ronaldo. Those are very, I don't know if you would agree, but they're kind of different disciplines.

• 2:57:28Speaker 02

  True. Yeah, very much so. I actually, I actually, I was, I had that question in my mind. I took physics classes as an undergrad or like besides what I had to take. And it's definitely something that I considered at some point. And, and that I, I do feel like later in life, that might be something that, I'm not sure if regret is, is the right word, but it's, it's kind of something that I can imagine in an alternative universe, what would have happened if I, if I had gone into physics.

• 2:58:12Speaker 02

  I try to think that like, well, it depends on what your path ends up being, but that it's, it's not super important, right? Like exactly what you decide to major on. Like, I think there's, there's, I think Tim Urban, like the blogger, had a good visualization of this, where it's like, you know, like he, he has a picture where you have all sorts of paths that you could pursue in your life, and then maybe you're in the middle of it. And so there's maybe some paths that are not accessible to you, but like the, the tree that is still in front of you gives you a lot of optionality. And so.

• 2:58:45Lex Fridman?

  There's two lessons to learn from that. Like, we have a huge number of options now, and probably you're just one to reflect, like to try to derive wisdom from the one little path you've taken so far may be flawed because there's all these other paths you could have taken.

• 2:59:03Speaker 02

  Yeah.

• 2:59:04Lex Fridman?

  So it's like, so one, it's inspiring that you can take any path now. And two, it's like you, the path you've taken so far is just one of many possible ones. But it does seem that like. Physics and computer science both open a lot of doors and a lot of different doors.

• 2:59:21Speaker 01

  True.

• 2:59:21Lex Fridman?

  It's very interesting.

• 2:59:22Speaker 01

  It is. I like in this case, like, and especially in our case, because I could see the difference. I studied, I went to college in Europe and Joanne went to college here in the US. So I could see the differences, like, the European system is more rigid in the sense that when you decide to study physics, you don't have a lot, especially in the early years, you don't have a lot of, you can't choose to take like a class from like computer science course or something like that. You don't have a lot of freedom to explore in that sense in university, as opposed to here in the US where you have more freedom. And I think, I think that's important. I think that's what constitutes, you know, a good kind of educational system, is one that gravitates towards the interests of a student as you progress.

• 3:00:07Speaker 01

  But I think in order for you to do that, you need to explore different areas. And I felt like if I had a chance to take, say, more computer science class when I was in college, I would have probably have taken those classes. But, yeah, but I ended up like focusing maybe too, too much in physics. And I think here at least my perception is that you can explore more, more fields.

• 3:00:29Lex Fridman?

  But there is a kind of, it's funny, but physics can be difficult. So I don't see too many computer science people then exploring into physics. It's all like the one, not the one, but one of the beneficial things of physics, it feels like it, what was it, Rutherford that said like, like basically that physics is the hard thing and everything is easy. So like, there's a certain sense, once you've figured out some basic like physics, that it's not that you need the tools of physics to understand the other disciplines. It's that you're empowered by having done difficult shit. I mean, the ultimate, I think, is probably mathematics there.

• 3:01:10Speaker 01

  Yeah, true.

• 3:01:11Lex Fridman?

  So maybe just doing difficult things and proving to yourself that you can do difficult things, whatever those are.

• 3:01:18Speaker 01

  That's net positive, I believe.

• 3:01:19Lex Fridman?

  Net positive.

• 3:01:20Speaker 01

  Yeah, and I think like I, I, before I started a company, I had like, I, I worked in the financial sector for a bit. And like, I think having a physics background, I was, I felt I was not afraid of like, learning like finance things. And I think like, when you come from those backgrounds, you are generally not afraid of stepping into other fields and learning about those because, um, yeah, I feel they've learned a lot of difficult things. And, um, yeah, that's an added benefit, I believe.

• 3:01:50Lex Fridman?

  This was an incredible conversation, Luis, Joao. We started with, uh, who do we start with? Feynman ended up with Messi and Ronaldo. So this is like the perfect conversation. It's really an honor that you guys would waste all this time with me today. It was really fun. Thanks for talking.

• 3:02:06Speaker 01

  Thank you so much for having us.

• 3:02:07Speaker 02

  Yeah, thank you so much.

• 3:02:09Lex Fridman?

  Thanks for listening to this conversation with Luis and Joao Batalha. And thank you to Skiff, Simply Safe, Indeed, NetSuite, and For Sigmatic. Check them out in the description to support this podcast. And now let me leave you with some words from Richard Feynman. "Nobody ever figures out what life is all about, and it doesn't matter. Explore the world. Nearly everything is really interesting if you go into it deeply enough." Thank you for listening. I hope to see you next time.