Lex Fridman Podcast - #159 – Richard Craib: WallStreetBets, Numerai, and the Future of Stock Trading

Episode Date: February 8, 2021

Richard Craib is the founder of Numerai, a crowd-sourced, AI-run stock trading system. Please support this podcast by checking out our sponsors: - Audible: https://audible.com/lex to get $9.95 a month... for 6 months - Tryolabs: https://tryolabs.com/lex - Blinkist: https://blinkist.com/lex and use code LEX to get 25% off premium - Athletic Greens: https://athleticgreens.com/lex and use code LEX to get 1 month of fish oil EPISODE LINKS: Richard's Twitter: https://twitter.com/richardcraib Numerai's Twitter: https://twitter.com/numerai Numerai's Website: https://numer.ai 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/LexFridmanPage - 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 (08:12) - WallStreetBets and GameStop saga (22:25) - Evil shorting and chill shorting (24:31) - Hedge funds (30:04) - Vlad (37:00) - Numerai (1:04:16) - Futre of AI in stock trading (1:09:55) - Numerai data (1:13:37) - Is stock trading gambling or investing? (1:17:32) - What is money? (1:20:49) - Cryptocurrency (1:24:06) - Dogecoin (1:28:36) - Advice for startups (1:44:27) - Book recommendations (1:46:29) - Advice for young people (1:50:30) - Meaning of life

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Starting point is 00:00:00 The following is a conversation with Richard Crape, founder of Numerai, which is a crowdsourced hedge fund, very much in the spirit of Wall Street bets, but where the trading is done not directly by humans, but by artificial intelligence systems submitted by those humans. It's a fascinating and extremely difficult machine learning competition, where the incentives of everybody is aligned. The code is kept and owned by the people who develop it. The data, anonymous data, is very well organized and made freely available. I think this kind of idea has a chance to change the nature of stock trading and even just
Starting point is 00:00:41 money management in general by empowering people who are interested in trading stocks with the modern and quickly advancing tools of machine learning. Quick mention of our sponsors. Audible audiobooks, child labs, machine learning company, blinkist app that summarizes books, and athletic greens, all in one nutrition drink. Click the sponsor links to get discount and to support this podcast. As a side note, let me say that this whole set of events
Starting point is 00:01:11 around GameStop and Wall Street Bets has been really inspiring to me as a demonstration that a distributed system, a large number of regular people are able to coordinate and collaborate in taking on the elite centralized power structures, especially when those elites are misbehaving. I believe that power in as many cases as possible should be distributed. And in this case, the internet, as it is for many cases is the fundamental enabler of that power and at the core what the internet and its distributed nature
Starting point is 00:01:51 represents is freedom. Of course the thing about freedom is it enables chaos or progress or sometimes both and that's kind of the point of the thing. Freedom is empowering, but ultimately unpredictable. And I think in the end, freedom wins. If you enjoy this podcast, subscribe on YouTube, review it on Apple Podcasts, follow on Spotify, support on Patreon, or connect with me on Twitter, at Lex Friedman. As usual, I'll do a few minutes of ads now and no ads in the middle. I try to make these interesting, but I give you timestamps, so if you skip, please still check out the sponsors by clicking the links in the description. It's the best way to support this podcast.
Starting point is 00:02:37 This episode is brought to you by Audible, an audiobook service that has given me hundreds if not thousands of hours of education through listening to audiobooks. Many of the books I mentioned on this very podcast were ones I've listened to with Audible, which feels like cheating, but it's not. It's the same book. Examples include American Cosmic, which is about UFOs, surely your Joker Mr. Feyn, by the man himself, Richard Feynman, the Ascent of Money by Neil Ferguson, which is a great history about money. You're interfished by Neil Schubert,
Starting point is 00:03:13 which is one of my favorite books on evolution. The news are by Stephen Lee Myers, which I think is the best, most objective work on Vladimir Putin that I've read to date. I've read quite a lot of biographies about him. And of course, the book that I've mentioned way too many times, the rise and fall of the third Reich by William Shire. I think it's over 50 hours long and one hell of a crazy ride through the darkest moments
Starting point is 00:03:41 of human history. Next two weeks, Audible is doing a special offer for listeners of this podcast, only 10 bucks, 995 a month for your first six months. If you visit audible.com slashlex or text lex to 500 500. I don't even know how that works or why you'd want to do that. Just go to audible.com slash likes. That's way better, I think. But I might be coolest. If you like texting, I guess go ahead and text. They have thousands of titles to choose from. So visit audible.com slash likes. Now they're considering supporting this byguest. So you know what to do if you want to help out. It's audible.com slash Lex.
Starting point is 00:04:26 This episode is also brought to you by Trial Labs, a company that helps build AI-based solutions for businesses of all sizes. I love these guys, especially after talking to them on the phone and checking out a bunch of their demos and blog posts. If you're a business or just curious about machine learning, check them out at triallabs.com slash Lex. They're working on price optimization, early detection of machine failures, and all kinds of applications of computer vision. Their price automation and optimization work is probably their most impressive in terms of helping businesses make money. Also, they release open source code on GitHub like a computer vision tracker, for example.
Starting point is 00:05:09 Tracking, to me, is a fascinating problem. It very much remains unsolved, especially in the application of deep learning to this problem, but we've seen a lot of progress in the past five years. Anyway, trial labs is legit. If you own a business and want to see how AI can help you, check them out at triallabs.com slashlex. This episode is also supported by Blinkist, my favorite app for learning new things.
Starting point is 00:05:36 Blinkist takes the key ideas from thousands of not fiction books and condenses them down into just 15 minutes that you can read or listen to. As part of that, I use Blinkist to try out a book that I may otherwise never have a And that's them down into just 15 minutes that you can read or listen to. As part of that, I use Blinkist to try out a book that I may otherwise never have a chance to read. And in general, it's a great way to broaden your view of the idea landscape out there. And find books that you may want to read more deeply. With Blinkist, you get unlimited access to read or listen to a massive library of condensed,
Starting point is 00:06:05 nonfiction books. I also use Blinkist's shortcuts to quickly catch up on podcast episodes I've missed. Right now, Blinkist has a special offer just for the listeners of this podcast. Go to Blinkist.com, you're on your own in this world. This show is also sponsored by Athletic Greens, the all-in-one daily drink to support better health and peak performance. It replaced the multivitamin for me and went far beyond that with 75 vitamins
Starting point is 00:06:52 and minerals. I do intermittent fasting of 16 to 24 hours every day and always break my fast with Athletic Greens. I honestly can't say enough good things about these guys. It's really one of my favorite products in this world. It helps me not worry whether I'm getting all the nutrients I need, especially since they keep iterating on their formula constantly improving it. I love that kind of obsessive pursuit of perfection. Also, I'm a huge fan of fish oil, I've taken it every day for many years now, and Athletic Greens finally is now offering fish oil. And they're going to give listeners of this podcast free one month supply of wild caught omega 3 fish oil when you go to Athletic Greens.com
Starting point is 00:07:38 slash Lex to claim the special offer. That's Athletic Greens.com for the drink and the fish oil. Trust me, it's worth it you will love it. And now here's my conversation with Richard Crabe. From your perspective, can you summarize the important events around this amazing saga that have been living through of Wall Street bets, the subreddit and GameStop and in general, just what are your thoughts about it from a technical to the philosophical level. I think it's amazing. It's like my favorite story ever.
Starting point is 00:08:30 When I was reading about it, I was like, this is the best. And it's also connected with my company, which we can talk about. But what I liked about it is I like decentralized coordination and looking at the mechanisms that these R. Wall Street bets users use to hype each other up to get excited to prove that they bought the stock and they're holding. And then also to see that how big of an impact that that decentralized coordination had, it really was a big deal. Well, you're impressed by the distributed coordination,
Starting point is 00:09:08 the collaboration amongst like, I don't know what the numbers are. I know numerous eyes looking at the data. After all of this is over and done, it would be interesting to see like from a large scale distributed system perspective to see how everything played out, but just from your current perspective, what we know is it obvious to you that such incredible level of coordination could happen where a lot of people come together in
Starting point is 00:09:35 distributed sense. There's an emergent behavior that happens after that. No, it's not at all obvious. And one of the reasons is the lack of kind of like credibility. To coordinate with someone, you need to kind of make credible contracts or credible claims. So if you have a username on our Wall Street bets, like some of them are, like deep fucking value, is one of that. That's an actual username, by the way, we're talking about, there's a website called Reddit,
Starting point is 00:10:03 and there's subreddits on it. And a lot of people, most the anonymous, we're talking about, there's a website called Reddit and there's subreddits on it. And a lot of people, most the anonymous, I think for the most part anonymous, can create user accounts and then can then just talk on form like style boards. You should know what Reddit is. If you don't know what Reddit is, check it out. If you don't know what Reddit is, maybe go to the subreddit first, a-w-, a WWW with Q pictures of cats and dogs. That's my recommendation. Anyway.
Starting point is 00:10:28 Yeah, that would be a good start to read it. When you get into it more, go to our Wall Street Fits. It gets dark quickly. We'll probably talk about that, too. So yeah, so there's these users, and there's no contracts, like you're saying. There's no contracts, the user are anonymous. There's no contracts, the user anonymous. But there are little things that do help.
Starting point is 00:10:47 So for example, if you've posted a really good investment idea in the past, that exists on Reddit as well. And it might have lots of upvotes. And that's also kind of like giving credibility to your next thing. And then they are also putting up screenshots. Like this is the, here's the trades I've made, and here's a screenshot.
Starting point is 00:11:10 Now you could fake the screenshot, but still it seems like if you've got a lot of karma and you've had a good performance on the community, it somehow becomes credible enough for other people to be like, you know what? He actually probably did put a million dollars into this. And you know what, I can follow that trade easily. And there's a bunch of people like that,
Starting point is 00:11:31 so you're kind of integrating all that information together yourself to see like, huh, there's something happening here. And then you jump it onto this little boat of like behavior, like we should buy the stock or sell the stock, and then another person jumps on another person jumps on and all of a sudden you have just a huge number of people behaving in the same direction. It's like flock of whatever birds and the lower what was strange with this one it wasn't just let's all buy Tesla we love Elon we love the Tesla let's let's all buy Tesla because that we've heard before right everybody likes
Starting point is 00:12:06 Tesla Well now they do So What they did with this in this case they're buying a stock that was bad They're buying it because it was bad and that's really weird because that's a little bit um Two galaxy brain for for a decentralized community Um, how did they come up with it? How did they know that was the right one?
Starting point is 00:12:29 And the reason they liked it is because it had really, really high short interest. It had been shorted more than its own float, I believe. And so they figured out that if they all bought this bad stock, they could short squeeze some hedge funds. And those hedge funds would have to capitulate and buy the stock at really, really high prices. And we should say that short, it means that these are a bunch of people. When you short a stock, you're betting on the, on your predicting that the stock is going to go down and then you will make money if it does. And then what's the short
Starting point is 00:13:05 squeeze? It's really that if you if you are a hedge fund and you take a big short position in a company, there's a certain level at which you can't sustain holding that position. There's no limit to how high a stock can go, but there is a limit to how low it can go, right? So if you short something, you have infinite loss potential. And if the stock doubles overnight, like GameStop did, you're putting a lot of stress on that hedge fund. And that hedge fund manager might have to say, you know what, I have to get out of the trade. And the only way to get out is to buy the bad stock that they don't want, like they believe
Starting point is 00:13:45 will go down. So it's an interesting situation, particularly because it's not zero sum. If you say, let's all get together and make a bubble in watermelons, you buy a bunch of watermelons, the price goes up, it comes down again. It's a zero sum gain. If someone's already shorted a stock and you can make them short squeeze, it's actually a positive sum game. So yes, some editors will make a lot of money, some will lose a lot,
Starting point is 00:14:13 but actually the whole group will make money. And that's really why it was such a clever thing for them to do. A couple do the fact that shorting, I mean, maybe you can push back, but to me, always from an outsider's perspective seemed, I hope I'm not using too strong of a word, but it seemed almost unethical, maybe not unethical, maybe it's just the asshole thing to do. It's okay, I'm speaking not from an economics or financial perspective, I'm speaking from just somebody who loves, I'm a fan of a lot of people.
Starting point is 00:14:47 I love celebrating the success of a lot of people. And this is like the stock market equivalent of like haters. I know that's not what it is. I know that there's efficient, you want to have an economy, efficient mechanism for punishing sort of overhyped, overvalued things. That's what Short-Ange is designed for, but it just always felt like these people are just,
Starting point is 00:15:13 because they're not just betting on the loss of the company. It feels like they're also using their leverage and power to manipulate media, or just to write articles, or just to hate I knew on social media and you get to see that with Elon Musk and so on. So, so this is like the man So people like hedge funds that were shorting are like the Sort of embodiment of the evil or just the bad guy, the overpowerful that's misusing their power.
Starting point is 00:15:46 And here's the crowd, the people that are standing up and rising up. So it's not just that they were able to collaborate on Wall Street bets to sort of effectively make money for themselves. It's also that this is like a symbol of the people getting together and fighting the centralized elites, the powerful. And that, you know, I don't know what your thoughts are about that in general. At this stage, it feels like that's really exciting that people have power, just like regular people have power.
Starting point is 00:16:22 At the same time, it's scary a little bit because, you know, just studying history, people could be manipulated by charismatic leaders. And so, like, just like, you know, a lot of right now is like manipulating, encouraging people to buy a dose coin or whatever, the, like, there can be good charismatic leaders and there can be bad charismatic leaders. And so it's nerve-wracking. It's a little bit scary how much power subreddit can have to destroy somebody. Because right now we're celebrating they might be attacking or destroying somebody that
Starting point is 00:16:59 ever be, doesn't like. But what if they attack somebody that is actually good for this world? And that's kind of the awesomeness and the price of freedom. It's like it could destroy the world or it can save the world. But at this stage, it feels like, I don't know, overall, when you sit back, do you think this was just a positive wave of emergent behavior? Is it because there's something negative about what happened? Well, yeah, the cool thing is they weren't doing anything, the reddit people weren't doing anything exotic. It was a creative trade, but it wasn't exotic, it wasn't, it was just buying the stock. Okay, maybe they bought some options too,
Starting point is 00:17:41 It was just buying the stock. Okay, maybe they bought some options too. But it was the hedge fund that was doing the exotic thing. So I like that. It's hard to say, well, we've got together and we've put all pulled all our money together. And now there's a company out there that's worth more. What's wrong with that? Yeah, right.
Starting point is 00:18:02 But it doesn't talk about the motivations, and then we destroyed some hedge funds in the process. Is there something to be said about the humor and I don't know, the edginess, sometimes viciousness of that subreddit? I haven't looked at it too much, but it feels like people can be quite aggressive on there. So is there... but it feels like people can be quite aggressive on there.
Starting point is 00:18:25 So is there, what is that? Is that what freedom looks like? I think it does, yeah. You definitely need to let people, the one of the things that people have compared it to is the Occupy Wall Street, which is let's say, you know, some very sincere liberals,
Starting point is 00:18:45 like 23 years old, whatever, and they go out and with signs and they have some kind of case to make. But this isn't sincere, really. It's like a little bit more nihilistic, a little bit more yolo. And therefore, a little bit more scary, because he's scared of the who's scared of the Wall Street Occupy Wall Street people with the science.
Starting point is 00:19:07 Nobody. But these hedge funds really are scared. I was scared of the of the Wall Street bats people. I'm still scared of them. Yeah, the anonymity is a bit terrifying and exciting. Yeah. I mean, yeah, I don't know what to do with it. You know, I've been following events in Russia, for example
Starting point is 00:19:27 It's like there's a struggle between centralized power and the distributed. I mean, that's the struggle of The history of human civilization, right? But this on the internet Just that you can multiply People like some of them don't have to be real like you can probably create bots like it starts getting me as a programmer I start to think like me is one person how much chaos can I create by writing some bots yeah and I'm sure I'm not the only one thinking that there's I'm sure there's the hundreds thousands of good developers out there listening to this thinking the same thing. And then as that develops further and further in the next decade or
Starting point is 00:20:11 two, what impact does that have on financial markets, on just destruction of reputations, of just or politics, you know, the the bickering of left and right political discourse, the dynamics of that be manipulated by, you know, they people talk about like Russian bots or whatever. I were probably in a very early stage of that, right? Exactly. And this is a good example. So do you have a sense that most of Wall Street Betts folks are actually individual people? Right that that's the feeling I have is there's just individual maybe young investors
Starting point is 00:20:50 Yeah, just doing a little bit of an investment, but just on a large scale. Yeah, exactly the reason I found out I've known about Wall Street Betts for a while But the reason I found about GameStop was this just I met somebody at a party who told me about it And he was like 21 years old and he's like it's gonna go up 100% in the next one day. We're talking about in last year. This was probably, no, this was a few days ago. Oh, yeah, it was like maybe two weeks ago or something. So it was already high, it was game stuff.
Starting point is 00:21:21 But it was just strange to me that there was someone telling me at a party how to trade stocks who was like 21 years old and started to look into it. And yeah, he did make 140% in one day. He was right. And now he's supercharged. He's a little bit wealthier. And now he's going to look, wait for the next thing, and this decentralized entity is just going to get bigger and bigger. And they're going to get a search for the next thing. So there's thousands of folks like him, and they're going to probably search for the next thing to attack. People that have power in this world that sit there with power right now in government,
Starting point is 00:22:01 in finance, in any kind of position are probably a little bit scared right now. And honestly, that's probably a little bit good. It's dangerous, but it's good. Yeah, it certainly makes you think twice about shorting. It certainly makes you think twice about putting a lot of money into your short. These funds put a lot into one or two names, and so it was very, very badly risk-managed. Do you think shorting is, can you speak at a high level, just for your own as a person,
Starting point is 00:22:31 is it good for the world, is it good for markets? I do think that the two kinds of shorting, evil shorting? And chill shorting. Evil shorting is what Melvin Capital was doing. And it's like you put a huge position down. You get all your buddies to also short it, and you start making press and trying to bring this company down. And I don't think in some cases, you go out
Starting point is 00:23:05 to fraudulent companies, say, this company is a fraud, maybe that's okay, but they weren't even saying games up, it's just saying it's a bad company and we're gonna bring it to the ground, bring it to its knees. A quant fund, like Numerai, we always have lots of positions and we never have a position that's like more than 1% of our fund. So we actually have right now 250 shorts. I don't know any of them, except for one,
Starting point is 00:23:35 because it was one of the meme stocks. But we shorting them not to make them go, we don't even want them to go down necessarily. That doesn't sound a bit strange, and I say that, but we just want them to not go up as much as our lungs. So by shorting a little bit, we can actually go long more in the things we do believe in. So when we were going long in Tesla, we could do it with more money than we had because we would borrow from banks who would lend us money because we had longs and shorts,
Starting point is 00:24:16 because we didn't have market exposure, you have market risk. And so I think that's a good thing because that means we can short the oil companies and go along Tesla and make the future come forward faster. And I do think that's not a bad thing. So we talked about this incredible distributed system created by Wall Street Bets. And then there's a platform which is Robinhood, which allows investors to efficiently, as far
Starting point is 00:24:43 you can correct me if I'm wrong, but there's those and there's others and this new Mariah that allow you to make it accessible for people to invest. But that said, Robinhood was in a centralized way, applied its power to restrict trading on the stock that we're referring to. Do you have a thought on actually like all the things that happened? I don't know how much you were paying attention to sort of the shadiness around the whole thing. Do you think it was forced to do it? Was there something shady going on? What are your thoughts in general? Well, I think I want to see the alternate history. Like I want to see the counterfactual history of them not doing that.
Starting point is 00:25:28 Not doing it. How bad would it have gotten for hedge funds? How much more damage could have been done if the momentum of these short squeezes could continue? What happens when there are short squeezes, even if they're in a few stocks, they affect kind of all the other shorts, too. And suddenly brokers are saying things like,
Starting point is 00:25:51 you need to put it more collateral. So we had a short, it wasn't GameStop, luckily, it was Blackberry. And it went up like 100% in a day. It was one of these meme stocks, super bad company. The AI's don't like it, okay? The AI's think it's going down. What's a meme stock?
Starting point is 00:26:08 A meme stock is kind of a new term for these stocks that catch mnemetic momentum on Reddit. And so the meme stocks were GameStop, the biggest one, GameStunk, Elon calls it, AMC. Blackberry was one, Nokia was one. So these are high short interest stocks as well. So these are targeted stocks. Some people say, oh, isn't it adorable that these people are investing money in these companies that are nostalgic? It's like, you're going to the AMC movie theater. It's like nostalgic. It's like, no. It's not why I'm doing it.
Starting point is 00:26:50 It's that they had a lot of short interest. That was the main thing. And so they were high chance of short squeeze. In saying I would love to see an alternate history, do you have a sense that that what does your prediction of what that history would have looked like? Well, you wouldn't have needed very many more days of that kind of chaos to hurt hedge funds. I think it's underrated how damaging it could have been. Because when your shorts go up, your collateral requirements for them go up. Similar to Robinhood, like we have a prime broker
Starting point is 00:27:28 that says, said to us, you need to put up, you know, like $40 per hundred dollars of short exposure. And then the next day, there's actually, you have to put up, you know, all of it, 100%. And we would like what? But if that happens, that, if that happens to all the short, all the commonly held hedge fund shorts because they were all kind of holding the same things.
Starting point is 00:27:52 If that happens, not only do you have to cover the short of which means you're buying the bad companies, you need to sell your good companies in order to cover the short. So suddenly, all the good companies, you need to sell your good companies in order to cover the short. Right. So suddenly, all the good companies, all the ones that the hedge funds like are coming down and all the ones that the hedge funds hate are going up in a cascading way. So I believe that if you could have had a few more days of GameSock doubling, AMC doubling,
Starting point is 00:28:26 you would have had more and more hedge fund deleveraging. But so hedge funds, I mean, they get a lot of shit, but do you have a sense that they do some good for the world? I mean, ultimately, so, okay, first of all, Wall Street bets itself as a kind of distributed hedge fund, numerous eyes, a kind of hedge fund. So, like, hedge funds are a very broad category. I mean, like if some of those were destroyed, would that be good for the world?
Starting point is 00:28:52 Or would there be coupled with the destroying the evil shorting? Would there be just a lot of pain in terms of investment in good companies? Yeah. A thing I like to tell people, if they hate hedge funds is, I don't think you wanna rerun
Starting point is 00:29:09 American economic history without hedge funds. So on mass, they're good. Yeah, they're good. Yeah, you really wouldn't want to. Because hedge funds are kind of like picking up, they're making liquidity in stocks. And so if you love venture capitalists, they're investing in new technology, so good. You have to also like hedge funds because they're the reason venture capitalists exist because their companies can have a liquidity event when they go to the public markets.
Starting point is 00:29:42 So it's kind of essential that we have them. There are many different kinds of them. I believe we could maybe get away with only having an AI hedge fund. But we don't necessarily need these evil billions type hedge funds that make the media and try to kill companies, but we definitely need hedge funds. Maybe from your perspective, because you run such an organization and Vlad, the CEO of Robinhood,
Starting point is 00:30:14 sort of had to make decisions really quickly, probably had to wake up in the middle of the night kind of thing. And he also had a conversation with Elon Musk on Clubhouse, which I just signed up for. It was a fascinating, one of the great journalistic performances of our time with the Elon Musk. The list of prize for Elon. How hilarious would it be if he gets a poll? Surprise. And then his Wikipedia be like, journalist
Starting point is 00:30:42 and part of the entrepreneur. Business, business, and business. I don't know if you can comment on any aspects of that, but if you were of lead, how would you do things differently? What are your thoughts about his interaction with Elon? How he should have played it differently? I guess there's a lot of aspects of this interaction. One is about transparency.
Starting point is 00:31:04 How much do you want to tell people about really what went down? There's NDAs potentially involved. How much in private do you want to push back and say no fuck you to centralize power? Whatever the phone calls you're getting, which I'm sure he's getting some kind of phone calls that might not be contractual, like it's not contracts that are forcing him, but he was being what do you call it, like pressured to behave in certain kinds of ways from all kinds of directions. Like what do you take from this whole situation? I was very excited to see Vlad's response, I mean, it's pretty cool to have him talk to Elon. And one of the things that struck me in the first few seconds
Starting point is 00:31:48 of Vlad's speaking was like, I was like, is Vlad like a boomer? Like, like, the, the, here we go. Like, he seemed like a 55-year-old man talking to a 20-year-old. Yeah. Elon was like the 20-year-old. And he's like the 55 year old man. You can see why Citadel are NMR buddies, right? Like you can. You can see why it's like this is a nice, it's not a bad thing. It's like he's like he's got a respectable professional attitude.
Starting point is 00:32:19 Well, he he also tried to do like a joky thing like, no, we're not being ages here. Boomer, but like, like, like a 60 year old CEO, Bank of America, we try to make a joke for the kids. That's what vats. Exactly. Yeah. I was like, what is this? This guy's like, what is he? 30? Yeah. And I'm like, this is weird. Yeah. But I think, and maybe that's also what I like about Elon's kind of influence on American business. He's super like anti-the professional. Like why say, you know, 100 words about nothing. And so I liked how he was cutting in and saying, Vlad, what do you mean?
Starting point is 00:33:00 Spill the beans, bro. Yeah. So you don't have to be courteous. It's like the first principle is thinking. It's like, what the hell happened? Yes. And let's just talk like normal people. The problem, of course, is, you know, for Elon, it's cost them what is it? 10s of millions of dollars is tweeting like that. But perhaps it's a worthy price to pay because ultimately there's something magical about just being real and honest and just Going off the cuff and making mistakes and paying for them but just being real and then moments like this
Starting point is 00:33:36 That was an opportunity for Vlad to be that and it felt like he wasn't Do you think they're do you think we'll ever find out? What really went down if there was something shady underneath it all? Yeah, I mean, it would be sad if nothing shady happened. But his presence made it shady. Sometimes I feel like that would mark Zuckerberg the CEO Facebook. Sometimes I feel like, yeah, there's a lot of shitty things that Facebook is doing, but sometimes I think
Starting point is 00:34:07 he makes you look worse by the way he presents himself about those things. Like I honestly think that a large amount of people at Facebook just have a huge unstable chaotic system and they're all not all, but a mass are trying to do good with this chaotic system. But the presentation is like, it sounds like there's a lot of back room conversations that are trying to manipulate people.
Starting point is 00:34:34 And there's something about the realness that Elon has that it feels like CEO should have and that had that opportunity. I think Mark Zuckerberg had that too when he was younger. Younger. And somebody said, you got to be more professional man. You can't say, you know, law to an interview. And then suddenly he became like this distance person that was hot. I'd like you'd rather have to make mistakes, but be honest.
Starting point is 00:34:58 Yeah. Than be like professional and never make mistakes. Yeah. One of the difficult tires I think is like marketing people, or like PR people, is you have to hire people that get the fact that you can say, lol on an interview. Or, you know, take risks as opposed to what the PR, I've thought to quite a few big CEOs and But the PR, I've thought to quite a few big CEOs and the people around them are trying to constantly minimize risk of like, what if he says the wrong thing? What if she says the wrong thing?
Starting point is 00:35:33 It's like, what? Be careful. It's constantly like, ooh, like I don't know. And there's this nervous energy that builds up over time with larger, larger teams where the whole thing, like I visited YouTube, for example, everybody I talked to YouTube, incredible engineering, an incredible system, but everybody's scared. Like, let's be honest about this madness that we have going on of huge amounts of video that we can't possibly ever handle. There's a bunch of hate on YouTube. There's this chaos of comments.
Starting point is 00:36:05 Much of conspiracy theories, some of which might be true. And then just like this mess that we're dealing with and it's exciting, it's beautiful. It's a place where like democratizes education, all that kind of stuff. And instead, they're all like sitting in like trying to be very polite and saying like, well, we're just want to improve the health of our platform. Like, yeah, the discussion like, all right, man, let's just be real. Let's, let's, let's, let's both advertise how amazing this freaking thing is, but also to say like, we don't know what we're doing. We have all these Nazis posting videos on YouTube. We don't, we don't know how to like handle it and just being real like that. I suppose that's just the skill. Maybe it can't be taught.
Starting point is 00:36:47 But over time, whatever the dynamics of the company is, it does seem like Zuckerberg and others get worn down. They just get tired. Yeah. They get tired of not being real. Of not being real, which is sad. So let's talk about NumeraI, which is an incredible company, system, idea, I think, but good place to start,
Starting point is 00:37:10 what is NumeraI and how does it work? So NumeraI is the first hedge fund that gives away all of its data. So this is like probably the last thing a hedge fund would do, right? Why would we give away a data? It's like giving away your edge. But the reason we do it is because we're looking
Starting point is 00:37:30 for people to model our data. And the way we do it is by obfuscating the data. So when you look at numerized data that you can download for free, it just looks like a million rows and numbers between zero and one, and you have no idea what the columns mean. But you do know that if you're good at machine learning or have done regressions before, you know that I can still find patents in this data, even though I don't know what the
Starting point is 00:38:00 features mean. And the data itself is a time series data. And even though it's sophisticated, anonymized, what is the source data? Like, approximately, what are we talking about? So we are buying data from lots of different data vendors. And they would also never want us to share that data. So we have strict contracts with them. So we only can, but it's the kind of data you could never buy
Starting point is 00:38:26 yourself unless you had maybe a million dollars a year of budget to buy data. So what's happened with the hedge fund industry is you have a lot of talented people who used to be able to trade and still can trade. But now they have such a data disadvantage. It would never make sense for them to trade themselves, but Numerai by giving away this up-discated data, we can give them a really really high quality data set that would otherwise be very expensive and they can use whatever new machine learning technique they want to find patterns in that data that we can use in our hedge fund. And so how much of a variety is there in underlying data? We're talking about
Starting point is 00:39:13 Apoges from using the wrong terms, but one is just like the stock price. The other, there's like options and all that kind of stuff like the, what are they called? Order books or whatever. Is there maybe other totally unrelated to directly to the stock market data, natural language as well, all that kind of stuff? Yeah, we were really focused on stock data that's specifically to stocks. So things like, you can have like every, every stock has like a PE ratio. For some stocks, it's not as meaningful, but every stock has that.
Starting point is 00:39:49 Every stock has one year momentum, how much they went up in the last year. But those are very common factors. But we try to get lots and lots of those factors that we have for many, many years, like 15, 20 years, like 15, 20 years history. And, and then the setup of the problem is common in in quant code like cross-sectional global equity. You're not really trying to say, I want, I believe, the stock will go up. You're trying to say, the like relative position of this stock in feature space makes it not a bad buy in a portfolio. So it captures some period of time
Starting point is 00:40:28 and you're trying to find the patterns the dynamics captured by the data of that period of time in order to make short term predictions about what's going to happen. Yeah, so our predictions also not that short, we're not really caring about things like order books and tick data, not high frequency at all. We're actually holding things for quite a bit longer.
Starting point is 00:40:49 So our prediction time horizon is about one month. We end up holding stocks for maybe like three or four months. So I kind of believe that's a little bit more like investing than kind of plumbing. Like to go long a stock that's mispriced on one exchange and shorter on another exchange, that's just arbitrage. But what we're trying to do is really know something more about the longer term future of the stock. Yeah, so from the patterns, from these periods of time series data, you're trying to understand
Starting point is 00:41:22 something fundamental about the stock, not about deep value like with the, it's big in the context of the market, it's underpriced overpriced all that kind of stuff. So like this is about investing. It's not about like just like you said, high frequency trading, which I think is a fascinating open question for machine learning perspective, but just to like sort of build on that. asking open question for machine learning perspective, but just to like sort of build on that, so you've anonymized the data, and now you're given away the data, and then now anyone can try to build algorithms
Starting point is 00:41:56 that make investing decisions on top of that data, or predictions on the top of that data. Exactly. And so that's, so what does that look like? What's the goal that what are the underlying principles of that? So the first thing is, you know, we could obviously model that data in house, right? We can make an XG boost model on the data. And that would be quite good too. But what we're trying to do is by opening it up and letting anybody participate, we can do quite a lot better than if we modeled it ourselves.
Starting point is 00:42:31 And a lot better on the stock market doesn't need to be very much. Like it really matters the difference between if you can make 10 and 12% in an equity market neutral hedge fund, because usually you're charging 2% fees. So if you can do 2% better, that's like all your fees, it's worth it. So we're trying to make sure that we always have the best possible model. As new machine learning libraries come out, new techniques come out, they get automatically synthesized. Like if there's a great paper on supervised learning, someone on numera will figure out how to use it on numeraized data.
Starting point is 00:43:07 And is there an ensemble of models going on, or is it more towards kind of like one or two or three, like best performing models? So the way we decide on how to wait all of the predictions together is by how much the users are staking on them, how much of the cryptocurrency that they are putting behind their models. So they're saying, I believe in my model. You can trust me because I'm going to put skin in the game. And so we can take the stake weighted predictions from all our users, add those together, average those together, and that's a much better model than any one model in the sum. Because,
Starting point is 00:43:51 unsombling a lot of models together is kind of the key thing you need to do in investing, too. Yeah, so you're putting, there's the kind of duality from the user from the perspective of a machine learning engineer, where you're, it's both a competition, just a really interesting, difficult machine learning problem, and it's a way to invest algorithmically. So like here, and, but the, the way to invest algorithmically, also is a way to put skin in the game that communicates to you, that your, the quality of the algorithm and also forces you to
Starting point is 00:44:28 really be serious about the models that you build. So it's like everything just works nicely together. Like I guess one way to say that is the interests are aligned. Okay, so it's just like poker is not not fun when it's like for very low stakes. They'll hire the stakes the more the dynamics of the system starts playing out correctly. Like as a small side note, is there something you can say about which kind, looking at the big broad view of machine learning today or AI, what kind of algorithms seem to do good in these kinds of competitions at this time? Is there some universal thing you can say, like neural network suck, recurrent neural network suck, transformer suck, or they're awesome, like old school,
Starting point is 00:45:21 sort of more basic kind of classifiers are better, is there some kind of conclusion so far that you can say? There is, there definitely is something pretty nice about tree models, like XG boost, and they just seem to work pretty nicely on this type of data. So out of the box, if you're trying to come 100th in the competition, or in the tournament, maybe you would try to use that. But what's particularly interesting about the problem that not many people understand,
Starting point is 00:45:55 if you're familiar with machine learning, this typically will surprise you when you model all data. So one of the things that you look at in finance is you don't want to be too exposed to any one risk. Like even if the best sector in the world to invest in over the last 10 years was tech, you would not, does not mean you should put all of your money into tech. Right. So the, if you train a model, it would say put all your money into tech. It's super good. But what you want to do is actually be very careful of how much of this exposure you have to certain features. So on numera, what a lot of people figure out is actually, if you train a model on this kind of data, you want to somehow neutralize
Starting point is 00:46:47 or minimize exposure to these to certain features, which is unusual because if you did train stop light or stop street detection on computer vision, your favorite feature, let's say you have an auto encoder and it's figuring out, okay, it's going to be red and it's going to be white, that's the last thing you want to be, you want to reduce your exposure to. Why would you reduce your exposure to the thing that's helping you model the most? And that's actually this counterintuitive thing you have to do with machine learning on
Starting point is 00:47:21 financial data. So reducing your exposure would help you generalize the things that are... So basically, financial data has a large amount of patterns that appeared in the past, and also a large amount of patterns that have not appeared in the past. And so, like, in that sense, you have to reduce the exposure to red lights to the color red. That's interesting, but how much of this is art and how much of it is science from your perspective so far in terms of as you start to climb from the hundredth position to the 95th in the competition.
Starting point is 00:48:00 Yeah, well, if you do make yourself super exposed to one or two features, you can have a lot of volatility when you're playing Numerai. You could maybe very rapidly rise to be high if you were getting lucky. Yes. And that's a bit like the stock market. Sure, take on massive risk exposure, put all your money into one stock, and you might make 100%. But it doesn't in the long run work out very well. And so the best users are trying to stay high for as long as possible, and not not necessarily try to be first for a little bit. not necessarily try to be first for a little bit. So for me, a developer, machine learning researcher,
Starting point is 00:48:48 how do I legs-freezing participate in this competition and how do others, I'm sure there'll be a lot of others interested in participating in this competition. What are, let's see, there's like a million questions, but like first one is, how do I get started? Well, you can go to numer.ai, sign up, download the data. And on the data is pretty small. In the data pack you download,
Starting point is 00:49:16 there's like an example script, Python scripts, that just builds a XG boost model very quickly from the data. And so in a very short time, you can have an example model. Is that a particular structure? Like what is this model then submitted somewhere? So there needs to be some kind of structure
Starting point is 00:49:36 that communicates with some kind of API. Like how does the whole, how does your model once you build, wants to create a little baby Frankenstein? How does it then live in it's? We want you to keep your baby Frankenstein at home and take care of it. We don't want it.
Starting point is 00:49:51 So you never upload your model to us. You always only giving us predictions. So we never see the code that wrote your model, which is pretty cool. That our whole hedge fund is built from models where we've never ever seen the code. But it's important for the users because it's their IP but they want to give it to us.
Starting point is 00:50:12 That's brilliant. So they've got it themselves, but they can basically almost like license the predictions from that model to us. That's the prediction. Yeah. So they go about it. What some users do is they set up a compute server and we call it newmer.
Starting point is 00:50:28 I compute it's like a little AWS kind of image and you can automate this process. So we can ping you. We can be like, we need more predictions now and then you send it to us. Okay, cool. So that's, is that describes somewhere, like what the preferred is, the AWS or whether another cloud platform, is there, I mean, is there sort of specific technical things you want to say that comes to mind that is a good path for getting started. So download the data, maybe play around, see if you can modify the basic algorithm provided in the example and then you what set up a little server on the AWS that then runs this model and takes things and then makes predictions. And how does your own money actually come into play during the stake of cryptocurrency.
Starting point is 00:51:25 Yeah, so you don't have to stake. You can start without staking. And many users might try for months without staking anything at all to see if their model works on the real life data, right? And is not over-fit. But then you can get new merer, many different ways. You can buy it on, you can buy some on Coinbase,
Starting point is 00:51:48 you can buy some on Uniswap, you can buy some on Binance. So what did you say this is a Hadoi pronounciate? So this is the Numerai cryptocurrency. Yeah, NMR. NMR. What's, you just say NMR? It is technically called Numerai. Numerai, I like it. Yeah, but NMR. What's, you just say NMR? It is technically called Numerair. Numerair?
Starting point is 00:52:06 I like it. Yeah, but NMR is simple. NMR, Numerair. Okay, so, and you could buy it, you know, basically anywhere. Yeah, so it's a bit strange because sometimes people would be like, is this like pay to play? Right. And it's like, soar, it's like, yeah, yeah, you need to put some money down to show us you believe in your model. But weirdly, we're not selling you the, like you can't buy the cryptocurrency
Starting point is 00:52:30 from us. Right. It's like, it's also, we never, if you're, if you do badly, we destroy your cryptocurrency. Okay, that's not good, right? You don't want it to be destroyed. But what's good about it is it's also not coming to us. Right. So it's not like we win when you lose or something, like we're the house. Like we're definitely on the same team. You're helping us make a hedge fund that's never been done before.
Starting point is 00:52:58 Yeah, so again, interests are aligned. There's no tension there at all, which is really fascinating. Given away everything and then the IP is owned by the code, you never share the code, that's fascinating. So, since I have you here and you said, 100th, I didn't ask out of how many, so we'll just... But if I then, once you get started and you find this interesting, how do you then win or do well, but also how do you potentially try to win if this is something you want to
Starting point is 00:53:32 take on seriously? From the machine learning perspective, not from a financial perspective. Yeah, I think the first of all, you want to talk to the community. People are pretty open. We give out really interesting scripts and ideas for things you might want to talk to the community. People are pretty open. We give out really interesting scripts and ideas for things you might want to try. And, but you're also going to need a lot of compute probably. And so some of the best users are, you know, actually,
Starting point is 00:53:56 the very first time someone won on Numerite, I would, I wrote them a personal email. I was like, you know, you've won some money. We're so excited to give you $300 and then they said, I spend way more on the computer. But this is fundamentally a machine learning problem first, I think, is this is one of the exciting things, I don't know how many ways you can approach this, but really this is less about kind of no offense, but like finance people, finance minded people, they're also I'm sure
Starting point is 00:54:28 great people. But it feels like from the community that I've experienced, these are people who see finances of fascinating problem space, the source of data, but ultimately they're machine learning people or AI people, which is a very different kind of flavor of community. I mean, I should say to that, I'd love to participate in this and I will participate in this, and I'd love to hear from other people if you're listening to this, if you're a machine learning person, you should participate and tell me, give me some hints how I can do well at this thing, because this boomer, I'm not sure I still got it, give me some hints, how I can do well at this thing,
Starting point is 00:55:05 because this boomer, I'm not sure I still got it, but because some of it is, it's like Kaggle competitions, like some of it is certainly set of ideas, like research ideas, like fundamental innovation, but I'm sure some of it is like deeply understanding getting like an intuition about the data. And then like a lot of it will be like figuring out like what
Starting point is 00:55:30 works like tricks. I mean, you could argue most of deep learning research is just tricks on top of tricks, but there's a, the some of it is just the art of getting to know how to work in a really difficult machine learning problem. And I think what's important, the important difference with something like a categor competition where they'll set up this kind of toy problem. And then there will be an out of sample test like, hey, you did well out of sample.
Starting point is 00:55:56 And this is like, okay, cool. But what's cool with Numerized, you're, you're, the out of sample is the real life stock market. We don't even know. Like we don't know the onset of the problem. We don't, like you'll have to find out live. And so we've had users who've submitted every week for like four years because it's kind of,
Starting point is 00:56:20 it's a, we say it's the hardest data science problem on the planet, right? And it sounds, maybe it sounds like maybe a bit too much for like a marketing thing, but it's the hardest because it's the stock market. It's like literally there are like billions of dollars at stake and like no one's like letting it be inefficient on purpose. So if you can find something that works on Numera, you really have something that that is like working on the real stock market.
Starting point is 00:56:47 Yeah, because there's like humans involved in the stock market. I mean, you could argue there might be harder data sets like maybe predicting the weather, all those kinds of things. But, the fundamental statement here is, which I like, I was thinking like, is this really the hardest data size problem? You start thinking about that, but ultimately, it also boils down to a problem where the data is accessible, it's made accessible, made really easy and efficient at submitting algorithms.
Starting point is 00:57:17 So it's not about the data being out there, like the weather. It's about making the data super accessible, making the ability to community around it. Like, this is what ImageNet did. Exactly. Like, it's not just, there's always images. The point is, you aggregate them together, you give it a little title, this is community, and that was one of the hardest, right, for a time. And most important data science problems in the world because it was accessible because it was made sort of like there was mechanisms by which like standards and mechanisms by which to judge your performance all those kinds of things and numerizer actually
Starting point is 00:57:59 just step up from that. Is there something more you can say about why from your perspective, it's the hardest problem in the world. I mean, you said it's connected to the market. So if you can find a pattern in the market, that's a really difficult thing to do because a lot of people are trying to do it. Exactly. But there's also the biggest one is it's non-stationary time series. the one is it's it's non-stationary time series. We've tried to regularize the data so you can find patterns by doing certain things to the features and the target, but ultimately you're in a space where you don't, there's no guarantees that the out of sample distributions will conform to any of the training data. And every single era, which we call on the website, like every single era in the data, which is like sort of showing you the order of the time, it's even the training data has the same dislocations. And so yeah, it's so many things that might want to try.
Starting point is 00:59:10 There's unlimited possible number of models. And so by having it be open, we can at least search that space. It's zooming back onto the philosophical. You said that numerize very much like Wall Street Paths. Is there, I think it'd be interesting to dig in why you think so. I think you're speaking to the distributed nature of the two and the power of the people nature of the two. So maybe can you speak to the similarities and the differences in which way is Numerai more powerful
Starting point is 00:59:50 in which way is Wall Street Betts more powerful? Yeah, this is why the Wall Street Betts story. So interesting to me because it's like feels like we're connected. Yeah. And looking at how, just looking at the form of Wall Street Betts, I was talking earlier about how,
Starting point is 01:00:05 how can you make credible claims? You're anonymous, okay, well maybe you can take a screenshot. How, I will maybe, you can upvote someone. Maybe you can have karma on Reddit. And those kinds of things make this emerging thing possible. Numerous, it didn't work at all when we started. It didn't work at all when we started. It didn't work at all. Why people made multiple accounts, they made really random models and hoped they would
Starting point is 01:00:30 get lucky and some of them did. Staking was our solution to could we make it so that we could trust, we could know which model people believed in the most, and we could wait models that had high stake more and effectively coordinate this group of people to be like, well, actually, there's no incentive to creating bought accounts anymore. Either I stake my accounts, in which case, I should believe in them, because I could lose my stake,
Starting point is 01:01:01 or I don't. And that's a very powerful thing, that having a negative incentive and a positive incentive can make things a lot better. And staking is like this, is this really nice, like key thing about blockchain, it's like something special you can do where they don't even trusting us with their stake
Starting point is 01:01:20 in some ways, they're trusting the blockchain, right? So the incentives, like you say, it's about making these perfect incentives so that you can have coordination to solve one problem. And nowadays I, I sleep easy because I have less money in my own hedge fund than our users are staking on their models. That's powerful. In some sense, from a human psychology perspective, it's fascinating that the Wall Street bets worked at all, right?
Starting point is 01:01:52 That amidst that chaos emerging behavior, that behavior they made sense emerged, it would be fascinating to think if numerous style staking could then be transferred to places like Reddit, you know, and not necessarily for financial investments, but like I wish sometimes people would, you know, would have to stake something in the comments they make on the internet. Yeah. Like that's the problem with anonymity an inimity is freedom and power
Starting point is 01:02:26 that you don't have to you can speak your mind, but it's too easy to just be shitty. Exactly. And so this the I mean, you're making me realize from like a profoundly philosophical aspect, numerized staking is a really clean way to solve this problem. It's a really beautiful way. Of course, it only with numeric currently, it works for a very particular problem, right? Not for human interaction on the internet, but that's fascinating. Yeah, there's nothing for, to stop people. In fact, we've opened source like the code we use for staking in a protocol,
Starting point is 01:03:01 we call a rager. And any, if Reddit wanted to, they could even use that code to do, have enabled staking on our Wall Street pets. And they're actually researching now, they've had some Ethereum grants on how could they have more crypto stuff in their, in Ethereum,
Starting point is 01:03:21 because wouldn't that be interesting? Like imagine you could, instead of seeing a screenshot like guys, I promise, I will not sell my GameStop. We're just going to go huge. We're not going to sell at all. And here is a smart contract which no one in the world, including me, can undo. That says, I have staked millions against this claim. That's powerful. And then what could you do? And of course, there doesn't have to be millions. It could be just very small amount, but then just a huge number of users doing that kind of stake. Exactly.
Starting point is 01:04:03 That could change the internet. It would change the land wall street. It would not, they would never have been able to, they would still be short squeezing one day after the next, every single hedge fund collapsing. If we look into the future, do you think it's possible that numeraly style infrastructure where AI systems back by humans are doing the trading is what the entirety of the stock market is or the entirety of the economy is run by basically this army of AI systems with high level human supervision. Yeah, the thing is that some of them could be, could be bad actors. Some of the humans. No, well, these systems could be tricky. So actually, I once met a hedge fund manager,
Starting point is 01:04:52 this is kind of interesting. He said, very famous one. And he said, we can see, sometimes we can see things in the market where we know we can make money, but it will mess it up. We know we can make money, but it will mess things up. And we choose not to do those things. And on the one hand, maybe this is like, oh, you're being super arrogant. Like, of course, you can't do this, but maybe he can. And maybe he really isn't doing things he knows he could do but would change, you know, be pretty bad. Would the Reddit army have that kind of morality or concern for what they're doing? Probably not based on what we've seen. The madness of crowds.
Starting point is 01:05:41 There would be like one person that says, hey, maybe, and then they'd get trampled over. That's the terrifying thing actually. This, a lot of people have written about this is somehow that like little voice, that's human morality, gets silenced when we get in a group and start chanting. Yeah. And that's terrifying. But like, I think maybe I misunderstood. I thought that you're saying AI systems can be dangerous, but you just describe how you must be dangerous. So which is safer. So I mean, one thing is, um, numera, yeah. So Wall Street bets, these kinds of like, these kinds of attacks, like, it's not possible to model numerized data and then come up with the idea from the model Let Short Screen Game Start.
Starting point is 01:06:31 It's not even framed in that way. It's not like possible to have that idea. So, but it is possible for like kind of a bunch of humans. So I think there's, it's, numer I could get very powerful without it being dangerous. But Wall Street bets needs to get a little bit more powerful and it'll be pretty dangerous. Yeah, well, I mean, this is a good place to kind of think
Starting point is 01:06:56 about Numerai data today and Numerai signals and what that looks like in 10, 20, 30, 50, 100 years. Right now, I guess maybe you can correct me, but the data that we're working with is like a window. It's an anonymized, obfuscated window into a particular aspect, a time period of the market. You can expand that more and more and more and more potentially. You can imagine in different dimensions to where it encapsulates all the things that
Starting point is 01:07:31 where you could include kind of human-to-human communication that was available for like to buy a GameStop, for example, on Wall Street. So maybe the step back, can you speak to what is Numerai signals and what are the different data sets that are involved? So with Numerai signals, you're still providing predictions to us. But you can do that from your own data sets. So Numerai is all, you have to model our data to come up with predictions.
Starting point is 01:08:06 Numerite signals is, whatever data you can find out there, you can turn it into a signal and give it to us. So, it's a way for us to import signals on data we don't yet have. And that's why it's particularly valuable because it's gonna be signals, you're only rewarded for signals that are orthogonal to our core signal. So you have to be doing something uncarrelated. And so, strange alternative data tends to have that property.
Starting point is 01:08:39 There isn't too many other signals that are correlated with what's happening on Wall Street bets That's not going to be like correlated with the price to earnings ratio, right? And we have some users as of recently as of like a week ago There was a user that created I think he's in India he created a Signal that is scraped from Wall Street bets And now we have that signal as one of our a signal that is scraped from Wall Street Bets. And now we have that signal as one of our signals
Starting point is 01:09:10 in thousands that we use at Numerai. And the structure of the signal is similar, so it's just numbers and time series data. It's exactly, and it's just like, it's kind of a, you're providing a ranking of stocks. So you just say, give a one means you like the stock zero means you don't like the stock and you provide that for five thousand stocks in the world. And they somehow converted the the natural language that's in the washroom. But they've come exactly. So
Starting point is 01:09:36 there's they made they open source the scolab notebook. You can go and see it and look at it. And so yeah, it's taking that making a sentiment score and then turning it into a rank of stocks. A testament score. Yeah. Like this stock sucks or this stock is awesome. And then converting that's fast. Just looking at that data will be a fast thing.
Starting point is 01:09:55 So on the signal side, what's the vision? This long term, what do you see that becoming? So we want to manage all the money in the world. That's Numerized Mission. And to get that, we need to have all the data and have all of the talent. Like there's no way for the first principles, if you had really good modeling and really good data that you would lose. It's just a question of how much do you need to get to get really good. So Numerite already has some really nice data that we give out. This year we are 10Xing that, and I actually think we'll 10X the amount of data we have on Numerite every year for
Starting point is 01:10:37 at least the next 10 years. Wow. So it's going to get very big the data we give out. And signals is more data. People with any other random data set can turn that into a signal and give it to us. And in some sense, that kind of data is the edge case of the weirdness is the, so you're focused on like the bulk, like the main data. And then there's just like weirdness from all over the place that just can enter through this back door of Christ. Exactly. And it's also a little bit shorter term. So the signals are set about a seven-day time horizon and on numerates like a 30-day. So it's often for faster situations. You've written about a master plan and you've mentioned, which I
Starting point is 01:11:25 love, in a similar sort of style of big style thinking, you would like numeri to manage all of the world's money. So how do we get there from from yesterday to several years from now? Like what is the plan? So do you have already started to allure to get all the data and get all the talent, humans, models? Exactly. I mean, the important thing to note there is what would that mean, right? And I think the biggest thing it means is like, if there was one hedge fund, you would have not so much talent wasted on all the other hedge funds. Like it's super weird how the industry works. It's like one hedge fund gets a data source and hires a PhD.
Starting point is 01:12:17 And another hedge fund has to buy the same data source and hire a PhD. And suddenly a third of American PhDs are working at hedge funds, and we're not even on Mars. And like, so in some ways, Numerai, it's all about freeing up people who work at hedge funds to go work for Elon. Yeah, and also the people who are working on Numerai problem,
Starting point is 01:12:42 it feels like a lot of the knowledge there is also transferable to other domains. Exactly. Our top one of our top users is he works at NASA Jet Propulsion Lab. And he's like amazing. I went to go visit him there. And it's like, he's got like Numerai posters. And it's like, it looks like, you know, the movies,
Starting point is 01:13:00 like it looks like Apollo 11 or whatever. Yeah, the point is he didn't quit his job to join full time. He's working on getting us to Jupiter's Moon. That's his mission, the Euro-Rope Clipper mission. Actually, literally what you're saying. Literally. We, he's smart enough that we really want his intelligence
Starting point is 01:13:21 to reach the stock market. Because the stock market's a good thing, hedge funds are a good thing. Our kinds of hedge funds, especially. But we don't want him to quit his job. So he can just do a new man right in the weekend and that's what he does. He just made a model and it just automatically submits to us and he's like one of our best users. You mentioned briefly that stock market's a good, for my sort of outside perspective, good. For my sort of outside perspective, is there a sense, do you think trading stocks
Starting point is 01:13:56 is closer to gambling or is it closer to investing? Sometimes it feels like it's gambling as opposed to betting on companies to succeed. And this is maybe connected to our discussion of shorting in general, but from your sense, do you think about it? Is it fundamentally still investing? I do think, I mean, it's a good question. I've also seen lately, like people say, this is like speculation. Is there too much speculation in the market? And it's like, but all the trades are speculative. Like all the trades have a horizon. Like people want them to work. So I would say that there's certainly a lot of aspects of gambling math that proplies to investing. Like one thing you don't do in gambling is put all your money
Starting point is 01:14:42 in one bet. You have bank role management and it's a key part of it. And small alterations to your bankroll management might be better than improvements to your skill. And then there are things we care about in our fund. We want to make a lot of independent bets. We talk about it. We want to make a lot of independent bets because We talk about it, like we want to make a lot of independent bets because that's going to be a higher sharp than if you have a lot
Starting point is 01:15:09 of bets that depend on each other, like all in one sector. But yeah, I mean, the point is that you want the prices of the stocks to be reflective of how of their value. Of the underlying value company. Yeah, you shouldn't have there be like a hedge fund that's able to say, well, I've looked at it some data and all of the stuff supermiss priced. Okay. That's super bad for society if it looks like that to someone. I guess the underlying question then is, do you see that the market often like drifts away from the underlying value of companies and it becomes a game in itself like with these
Starting point is 01:15:54 whatever they're called like derivatives like the option like you know options and shorting you know that kind of stuff. It's like and shorting and all that kind of stuff. It's like layers of game on top of the actual, like what you said was just like the basic thing that the Wall Street Bets was doing, which is just buying stocks. Yeah, there are a lot of games that people play
Starting point is 01:16:17 that are in the derivatives market. And I think a lot of the stuff people dislike when they look at the history of what's happened, they hate like credit default swaps or it's collateralized debt obligations. Like these are the, these are like kind of like enemies of 2008. And then the long-term capital management thing,
Starting point is 01:16:38 it was like, it was like that 30 times leverage or something, just that no one, like you could just go to a gas station and ask anybody at the gas station, is it a good idea to have 30 times leverage? And they just say no. It's a common sense just like went out the window.
Starting point is 01:16:56 So, yeah, I don't respect long-term capital management. Okay, but Numerine doesn't actually use any derivatives unless you call shorting the derivative. We do put money into companies. That does help the companies we're investing in. It's just in little ways. We really did buy Tesla. We played some role and in that's it's success Super small make no mistake, but still I think that's important can I ask you a
Starting point is 01:17:33 pot head question, which is What is money man? So if we just kind of zoom out and look at Because I'd let's talk to you about cryptocurrency, which perhaps could be the future of money. In general, how do you think about money? You said, you said, you're the vision, the goal is to run, to manage the world's money. What is money in your view?
Starting point is 01:18:03 I don't have a good answer to that, but it's definitely in my personal life, it's become more and more warped. And you start to care about the real thing, like what's really going on here? Elon has talks about things like this, like what is the company? Really? It's like so a bunch of people who like kind of show up
Starting point is 01:18:26 to work together and like they solve a problem. And they might not be a stock out there that's trading that represents what they're doing, but it's not the real thing. And being involved in crypto, I put in crowd sale of Ethereum and all these other things and different crypto hedge funds and things that I've invested in. And it's like, it's just kind of like, it feels like how I used to think about money stuff is just like totally warped. because you stop caring about the price and you can care about the product.
Starting point is 01:19:10 So, but the product, you mean the different mechanisms that money has exchanged. I mean, money is ultimately a kind of a little, you know, on one is the store of wealth, but it's also a mechanism of exchanging wealth. But what wealth means becomes a totally different thing, especially with the cryptocurrency, where it's almost like these little contracts, these little agreements, these transactions between human beings that represent something that's bigger and just like cash being exchanged to 7.11, it feels like. Yeah, maybe I'll answer what is finance. Like, it's what are you doing when you have the ability
Starting point is 01:19:50 to take out a loan? You can bring a whole new future into being with finance. If you couldn't get a student loan to get a college degree, you couldn't get a college degree. get a college degree, you couldn't get a college degree. I give you didn't have the money. But now, weirdly, you can get it with, and all you have is this loan, which is like, so now you can bring a different future into the world.
Starting point is 01:20:18 That's how, when I was saying earlier, about if you rerun American history, economic history without these things, like, you know, a lot these things. Like, you know, a lot of takeout loans, you know, a lot to have derivatives, you know, a lot to have money. It would just, it just doesn't really work. And it's a really magic thing. How, how, how much you can do with finance, but kind of bringing the future forward. Finance is empowering. It's, we sometimes forget this, but yeah, it enables innovation. It enables big risk takers and bold builders that ultimately make this world better.
Starting point is 01:20:50 You said you were early in on cryptocurrency. Can you give your high level overview of just your thoughts about the past, present, and future of cryptocurrency? Yeah, so my friends told me about Bitcoin and I was interested in equities a lot and I was like, well, it has no net present value. It has no future cash flows. Bitcoin pays no dividends. So I really couldn't get my head around it and like that this could be valuable. And then I but I did so I didn't feel like I was early in cryptocurrency.
Starting point is 01:21:28 In fact, because I was like, it was like 2014, it felt like a long time after Bitcoin. And then, but then I really liked some of the things that's, Ethereum was doing. It seemed like a super visionary thing. Like I was reading something that was, that was just going to change the world when I was reading the white paper. And I liked the different constructs you could have inside of a theory and that you couldn't have on Bitcoin. Like smart contracts and all that kind of stuff. Exactly. Yeah. And even the, they were, yeah, even spoke about different, yeah, different constructions you could have.
Starting point is 01:22:02 Yeah, that's a cool dance between Bitcoin and Ethereum. It's in the space of ideas. It feels so young. I got wonder what cryptocurrencies will look like in the future. If Bitcoin or Ethereum 2.0 or some version will stick around or any of those like who's going to win out or if there's even a concept of winning out at all. Is there going to win out or if there's even a concept of winning out at all, is there a cryptocurrency that you're especially find interesting that technically financially, philosophically, think is something to keep in your eye on? Well, I don't really, I'm not looking to invest in cryptocurrencies anymore, but I, they are, I mean, the, they're, and many are almost identical. I mean, there's not, there wasn't too much difference between even Ethereum and Bitcoin in some ways, right? But they are some that I like the privacy
Starting point is 01:22:59 ones. I mean, I was like, I like Zcash for it's like cool It's a different kind of invention compared to some of the other things. Can you speak to it just briefly to privacy? Is there some mechanism of preserving some privacy of the inverse? I guess everything is public. Yeah. Is that the problem? Yeah, none of the transactions are private. Yeah. And so, you know, even like, I have some of my, I have some numerator and you can just see it.
Starting point is 01:23:32 In fact, you can go to a website and say, like, you can go to like, ethoscan and it'll say like, numerator I found a, and I'm like, how the hell you guys know it? So they can reverse and then you're whatever that's called. Yeah, and so they can see me move it too. They can see me. Oh, why is he moving it? Yeah. So, but yeah, ZCash, then they also, when you can make private transactions, you can also play different games. Yes.
Starting point is 01:23:59 And it's unclear. It's like what's quite cool about Zcash's I wonder what games are being played there. I wonder No, so from a from a deeply analytical perspective Can you describe why Dosh Cohen is going to win? Which it surely will like it very likely will take over the world and once we expand out into the universe will take over the universe and out into the universe will take over the universe. Or in a more serious note, like what are your thoughts on the recent success of Dorsch going where you're spoken to sort of the meme stocks, the memetics of the whole thing,
Starting point is 01:24:35 that it feels like the joke can become the reality. Like the meme, the joke has power in this world. Yes. It's fassay. Exactly. It's like, why is it correlated with Elon tweeting about it? It's not just Elon alone tweeting, right? It's like Elon tweeting and that becomes a catalyst for everybody on the internet kind
Starting point is 01:25:04 of like spreading the joke right. Exactly. The joke of it. So it's the initial spark of the fire for Wall Street bets type of situation. Yeah. And that's fascinating because jokes seem to spread faster than other mechanisms. Yeah.
Starting point is 01:25:22 Like funny shit is very effective at captivating the discourse on the internet. Yeah, and I think you can have, like though I like the one meme, like Doge, I haven't heard that name in a long time. Ah! Ah! Yeah.
Starting point is 01:25:41 Like, I think back to that meme often. That's like funny. And every time I think back to that mean often. That's like funny. Yeah, and every time I think back to it There's a little probability That I might buy some touch kind right and so I might just have millions of people who have had all these great jokes told them And every now and then they reminisce. Oh, that wasn't that was really funny. And then they're like Let me buy some And then they saw that wasn't really funny. And then they're like, ah, let me buy some.
Starting point is 01:26:04 Yeah. Wouldn't that be interesting if the entire, if we travel in time, like multiple centuries, where the entirety of the communication of the human species is like humor. Like it's all just jokes. Like we're high on probably some really advanced drugs and we're all just laughing on stop.
Starting point is 01:26:26 It's a weird like dystopian future of just humor. Elon has made me realize how like good it feels to just not take shit seriously every once in a while and just relieve like the pressure of the world. At the same time, the reason I don't always like when people finish their sentences with law is like that you don't, when you don't take anything seriously. When everything becomes a joke, then it feels like that way of thinking feels like it will destroy the world. It's like, I often think it will, like, will memes save the world or destroy it?
Starting point is 01:27:10 Because I think both are possible directions. Yeah, I think this is a big problem. I mean, America, I always felt that about America, a lot of people are telling jokes kind of all the time. And they're kind of good at it. And you take someone inside an American, you're like, I really want to have a sincere conversation. It's like hard to even keep this rate phase.
Starting point is 01:27:30 Yeah. Because everything is so, there's so much levity. So it's complicated. I like how sincere, actually, like your Twitter can be. You're like, I'm in love with the world. Yeah. I get so much shit for it. But I'm never going to stop because I realize, like, do you have to be able to sometimes just be real and be positive and just be, uh, say the cliche things, which ultimately those
Starting point is 01:27:55 things actually capture some fundamental truths about life. Yeah. But it's a dance. And I think Elon does a good job of that from an engineering perspective of being able to joke, but everyone's mostly to pull back and be like, here's real problems, let's solve them, and so on, and then be able to jump back to a joke. So it's ultimately, I think, I guess, a skill that we have to learn. But I guess your advice is to invest everything anyone listening owns into Dogecoin.
Starting point is 01:28:28 That's what I heard from this stretch. Yeah, exactly. Yeah. Our hedge fund is unavailable. I just go straight to Dogecoin. You're running a successful company. It's just interesting because my mind has been in that space of potentially being one of the
Starting point is 01:28:45 millions other entrepreneurs. What's your advice on how to build a successful startup, how to build a successful company? I think that one thing I do like and it might be a particular thing about America, but like there is something about like playing, tell people what you really want to happen in the world. Like, don't stop. It's not, it's not going to make it, like if you're asking someone to invest in your company, don't say, I think maybe one day we might make a million dollars, when you actually believe
Starting point is 01:29:21 something else, you actually believe believe you're actually more optimistic, but you're toning down your optimism because you wanna appear like low risk, but actually it's super high risk if your company becomes mediocre because no one wants to work in a mediocre company, no one wants to invest in the other company. So you should play the real game.
Starting point is 01:29:46 And obviously this doesn't apply to all businesses, but if you play a venture backed startup kind of game, like play for keeps, play to win, go big. And it's very hard to do that. I always feel like, yeah, I start narrowing your focus because 10 people are telling you, you know, you got to care about this boring thing that won't matter five years from now.
Starting point is 01:30:12 Right. And you should push back and do the real, play the real game. So, it would be bold. So both, I mean, this is, there's an interesting duality there. So there's, well, the way you speak to other people about your plans and what you are like privately, just in your own mind. And maybe it's connected with what you're saying about, yes, sincerity as well. Like if you appear to be sincerely optimistic about something that's bagel crazy, it's
Starting point is 01:30:44 putting yourself up to be kind of like ridiculed or something. And so if you say, my mission is to, yeah, go to Mars. It's just so bonkers that it's hard to say. It is, but one powerful thing, just like you said, is if you say it and you believe it, said is if you say it and you believe it, then actually amazing people come and work with you. Exactly. It's not just skill, but the dreams. There's something about optimism that like that fire that you have when you're optimistic of actually having the hope of building something totally cool, something totally new, that
Starting point is 01:31:23 when those people get in a room together, like they can actually do it. Yeah. Yeah, there's, yeah, there's, that's, uh, and also makes life really fun when you're in that room. So I'll, I'll let it together, uh, ultimately, I don't know, that's what makes this crazy ride of a startup really, uh, And Elon's an example of a person who succeeded at that. There's not many other inspiring figures, which is sad. I used to be a Google. And there's something that happens
Starting point is 01:31:55 that sometimes when the company grows bigger and bigger and bigger, where that kind of ambition kind of quides down a little bit. Google had this ambition still does of making the world's information accessible to everyone. And I remember, I don't know, that's beautiful. I still love that dream of these to scan books, but just in every way possible, make the world's information accessible. Same with Wikipedia. Every time I open up Wikipedia, and accessible, same with Wikipedia. Every time I open up Wikipedia,
Starting point is 01:32:26 I'm just awe inspired by how awesome humans are, man. At creating this together, I don't know what the meetings are over there, but it's just beautiful. Like what they've created is incredible. And I'd love to be able to be part of something like that. And you're right for that, you have to be bold. And there's strange to me also, I think you're right that there's how many boring companies they are.
Starting point is 01:32:50 Something I just talk about, especially in FinTech, it's like, why am I excited about this? It's so lame. Like what is, this isn't even like important, even if you succeed, this is gonna be like terrible. Like this is not good. And it's just strange how people can kind of get fake enthusiastic about like boring ideas. When there's so many bigger ideas that,
Starting point is 01:33:15 yeah, I mean, you read these things like this company raises money and it's just like that's a lot of money for the worst idea I've ever heard. Some ideas are really big. So I worked on autonomous vehicles quite a bit. And there's so many ways in which you can present that idea to yourself, to the team you work with, to just, yeah, like to yourself when you're quietly looking in the mirror in the morning, that's really boring or really exciting.
Starting point is 01:33:42 Like if you're really ambitious with autonomous vehicles, it changes the nature of like human robot interaction, it's changes the nature of how we move, forget money, forget all that stuff. It changes like everything about robotics and AI, machine learning, it changes everything about manufacturing. I mean, the transportation is so fundamentally connected to cars and if that changes, it changes the fabric of society, of movies, of everything.
Starting point is 01:34:10 And if you go bold and take risks and go be willing to go bankrupt with your company, as opposed to cautiously, you can really change the world. And so sad for me to see all these autonomous companies, autonomous vehicle companies, they're like really more focused about fundraising and kind of like smoke and mirrors. They're really afraid. The entirety of their marketing is grounded in fear and presenting enough smoke to where they keep raising funds
Starting point is 01:34:39 so they can cautiously use technology of previous decade or previous to decades to kind of test vehicles here and there as opposed to do crazy things in bold and go huge at scale to huge data collection. So that's just an example. The idea can be big, but if you don't allow yourself to take that idea and think really big with it, then you're not going to make anything happen. Yeah, you're absolutely right in that. So you've been connected in your work with a bunch of amazing people. How much do you interact with investors? That whole process is an entire mystery to
Starting point is 01:35:20 me. Is there some people that just have influence on the trajectory of your thinking completely? Or is it just this collective energy that they behind the company? Yeah, I mean, I came here and I was amazed how, yeah, people would, I was only here for a few months and I met some incredible investors and I almost run out of money. And once they invested, I was like, I am not gonna let you down. And I was like, okay, I'm gonna send them like an email update every like three minutes. And then they don't care at all.
Starting point is 01:35:58 So they kind of wanna, I don't know. Like so I like it when it's just like, they're always available to talk. But a lot of building a business, especially a high tech business. There's a little for them to add, right? There's a little for them to add on product. There's a lot for them to add on business development.
Starting point is 01:36:18 And if we are doing product research, which is for us research into the market, research into how to make a great hedge fund. And we do that for years. There's not much to tell the investors. So they're basically like, I believe in you, there's something I like to cut of your jib. There's something in your idea, in your ambition, in your plans that I like. And it's almost like a pat on the back. I was like, go get them, kid. Yeah, it is a bit like that. And that's cool.
Starting point is 01:36:48 That's a good way to do it. I'm glad they do it that way. Like the one in meeting I had, which was like really good with this was meeting Howard Morgan, who's actually a co-founder of Renaissance technologies in the like 1980s and worked with Jim Simons and he he he was in the room and I was meeting some other guy and he was in the room and I was explaining how quantitative finance works. I was like so you know that you they use mathematical models and then he was like, yeah, I started Renaissance. I know I've been about this.
Starting point is 01:37:26 And then I was like, oh my God. So yeah, but then I think he kind of said, well, yeah, he said, well, because I was talking, he was working at first round capital as a partner. And they kind of said they didn't want to invest. And then I wrote a blog post describing the idea and I was like, I really think you guys should invest. And then they end up.
Starting point is 01:37:48 Oh, interesting. You convinced them all that. That must be good. Yeah, because they're like, we don't really invest in hedge funds. And I was like, you don't see like what I'm doing. This is something different. So a tech company, not a hedge fund, right? Yeah, and you're more as brilliant.
Starting point is 01:38:00 It's when it caught my eye, there's something special there. So I really do hope you succeed. And obviously it's a risky thing you're taking on, the ambition of it, the size of it. But I do hope you succeed. You mentioned Jim Simon's, he comes up in another world of mine really often on the, he's just a brilliant guy,
Starting point is 01:38:19 on the mathematics side, as a mathematician, but he's also brilliant finance hedge fund manager guy. Have you gotten a chance to interact with him at all? Have you learned anything from him on the math, on the finance, on the philosophy life side? Things. I've played poker with him. It was pretty cool. It was like actually in the show of billions, they kind of do a little thing about this Poke tournament thing with all the hedge fund managers and that's a real life thing and And they have a lot of like world series of bracelet
Starting point is 01:38:53 What's there is poke up the bracelets holders, but it's kind of Jim's thing and I met him there and Yeah, it was kind of brief, but I was just like, he's like, oh, how do you have? Why are you here? And I was like, oh, how had sent me, you know, he's like, go, go play this tournament, meet some of the other players. And then, um, was it Texas Holden? Yeah, that Texas Holden tournament. Yeah, like, do you play poker yourself? Or was it? Yeah, I do. I mean, it was crazy. And the on my right was the CEO, who's the current CEO of Renaissance, Peter Brown, and Peter
Starting point is 01:39:28 Mueller, who's a Pedge Fund Manager at PDT. And yeah, I mean, it was just like, and then, you know, just everyone, and then all these brace, World Series, like people that I know from like TV. And Robert Mercer, who's fucking crazy, he's the guy who donated the most money to Trump. And he's just like... A lot of personality. Character, yeah. Jeez, that's crazy.
Starting point is 01:39:58 So it's quite cool how, yeah, like the... It was really fun. And then I managed to knock out Peter Mellor. I got a little trophy for knocking him out because he was a previous champion. In fact, I think he's won the most. I think he's won three times. Super smart guy.
Starting point is 01:40:15 But I will say Jim outlasted me in the tournament. And they're all extremely good at poker. But they're also, so it was a $10,000 buy-in. And I was like, this is kind of expensive. But it all goes to charity, Jim's math charity. But then the way they play, they have like rebise. And like, they all do a shit ton of rebice. This is for charity. Yeah.
Starting point is 01:40:46 So immediately they're like going all in and I'm like, man, like, so I end up, you know, adding more as well. So the state, like you couldn't play at all without doing math. Yeah, the stakes are high. So, but you're connected to a lot of these folks. They're kind of titans of just economics and tech in general. Do you feel burden from this? You're a young guy. I did feel a bit out of a place there like the company was quite new and they also don't speak about things, right? It's not like going to meet a famous rocket engineer
Starting point is 01:41:28 who will tell you how to make a rocket. They do not want to tell you anything about how to make a hedge fund. It's like all secretive. And that part I didn't like. And they were also kind of making fun of me a little bit. Like they would say, like they'd call me like, I don't know, the Bitcoin kid.
Starting point is 01:41:45 Oh, yeah. And then they would say, even things like, member Peter, yeah, said to me something like, I don't think AI is gonna have a big role in finance. And I was like, hearing this from the CEO of Renaissance was like, weird to hear because I was like, of course it will. And he's like, but he can see, I can see it having a really big impact on things like self-driving
Starting point is 01:42:08 cars. But finance, it's too noisy and whatever. And so I don't think it's like the perfect application. And I was like, that was interesting to hear because it's like, and I think it was that same day that Libra, I think it is. The poker playing AI started to beat like the human. Yeah. So it was kind of funny hearing them like say, Oh, I'm not sure AI could ever get
Starting point is 01:42:30 attack that problem. Yes. And then that very day is attacking the problem of the game we're playing. Well, there's a kind of a magic magic to, um, somebody who's exceptionally successful, looking at you, giving your respect, but also saying that what you're doing is not going to succeed in a sense, like they're not really saying it, but I tend to believe, for my interactions with people, that it's a kind of prod to say,
Starting point is 01:42:57 like, prove me wrong. Yeah. That's ultimately, that's how those guys talk. They see good talent and they're like, I'm, yeah. And I think they also saying it's not gonna succeed quickly in some way. They're like, this is gonna take a long time and maybe that's good to know.
Starting point is 01:43:16 And certainly AI in trading, that's one of the most, so philosophically interesting questions about artificial intelligence and the nature of money because it's like how much Can you extract in terms of patterns from all of these millions of humans interacting using this methodology of money? It's like one of the open questions in the artificial intelligence in that that sense, you converting into a data set is one of the biggest gifts to the research community, to the whole, anyone who loves data science and AI. This is, this is kind of fascinating. I'd love to see where this goes actually. I think I say sometimes long before AGI destroys
Starting point is 01:44:02 the world, a narrow intelligence will win all the money in the stock market. Like, wait, just a narrow AI. Yeah. And I don't know if I'm going to be the one who invents that. So I'm building NumeraI to make sure that that narrow AI uses our data. So you're giving a platform to where millions of people can participate and do build that narrow eye themselves.
Starting point is 01:44:27 People love it when I ask this kind of question about books, about ideas and philosophers and so on. I was wondering if you had books or ideas, philosophers, thinkers that had an influence on your life when you were growing up, or just today that you would recommend that people check out blog posts, podcast, videos, all that kind of stuff. Is there something that just kind of had an impact on you that you can't recommend? A super kind of obvious one that I really was reading Zero to One while coming up with Numerai. I was like halfway through the book.
Starting point is 01:45:08 And I really do like a lot of the ideas there. And it's also about kind of thinking big. And also it's like peculiar little book. It's like why there's a little picture of the hipster versus Uniboma. And it's a weird little book. So there's kind of a weird little book. So I like this kind of like some depth that turns a book on a if you're thinking of doing a startup. Yeah, that's a good book. A book I like a lot is maybe my favorite book is David Deutsche's beginning of infinity.
Starting point is 01:45:40 I just found that so optimistic. It puts you, everything you read in science, it makes the world feel like kind of colder. Because it's like, we're just coming from evolution and coming from nothing should be this way or whatever. And humans are not very powerful. We're just scum on the earth. And the way David Deutsch sees things and argues, he argues them with the same rigor
Starting point is 01:46:07 that the cynics often use and then has a much better conclusion that's, you know, some of the statements of things like, you know, anything that doesn't violate the laws of physics can be solved. Like, so ultimately arriving in a hopeful, like a hopeful before. Yeah, without being like a hippie. You mentioned kind of advice for startups. Is there in general whether you do a startup or not,
Starting point is 01:46:34 do you have advice for young people today? You're like an example of somebody who's paved their own path and where I would say exceptionally successful. Is there advice somebody who's like 20 to day 18 on a grad or thinking about going to college or in college and so on that you would give them? I think I often tell young people don't start companies. Is it not, don't start a company
Starting point is 01:47:00 unless you're prepared to make it your life's work. That's a really good way of putting it. And a lot of people think, well, you know, this semester, I'm gonna take a semester off and in that one semester, I'm gonna start a company and sell it or whatever. And it's just like, what are you talking about? It doesn't really work that way.
Starting point is 01:47:18 You should be like super into the idea, so into it that you wanna spend a really long time on it. Is that more about psychology or actually time allocation? Like, is it literally the fact that you need to give 100% for potentially years for it to succeed? Or is it more about just the mindset that's required? Yeah, I mean, I think, well, I think, yeah, you don't want to have, certainly don't want to have a plan to sell the company, like quickly or something, or it's like a company that has a big fashion component, like it'll only work now.
Starting point is 01:47:52 It's like an app for something. So yeah, that's a big one. And then I also think something I thought about recently is I had a job as a quant, at a fund, for about two and a half years. And part of me thinks if I had spent another two years there, I would have learned a lot more and had even more knowledge to be where new to basically accelerate how long Numerite took. So the idea that you can sit in an air conditioned room and get free food or even sit at home now in your underwear and make
Starting point is 01:48:33 a huge amount of money and learn whatever you want and get it's just crazy. It's such a good deal. Yeah. Oh, that's interesting. That's the case for I was terrified of that like a Google I thought I would become really comfortable in that air-condition room and That I was afraid the quan situation is I mean will you present this is really brilliant that It's exceptionally valuable the lessons you learn because you get to get paid while you learn from others. If you see jobs in the space of your passion that way, that it's just an education. It's like the best kind of education. But of course, you have, from my perspective, you have to be really careful on that to get comfortable. Again, in a relationship, then you buy a house or whatever the hell it is. And then you get, you know, and then you convince yourself like, well, I have to pay these fees for the car, for the house of a blah, blah, blah. And then there's momentum and all of a sudden,
Starting point is 01:49:34 you're on your deathbed and there's grandchildren. And you drink your whiskey and complaining about kids these days. So I, you know, that I'm afraid of that momentum, but you're right. Like, there's something special about education you get working at these companies. Yeah. And I remember on my desk, I had the, like, a bunch of papers on quond finance, a bunch of papers on optimization. And then the paper on Ethereum, just on my desk as well, and the white paper. And it's like, it's amazing how my, how kind of, and you can learn. And it's like, it's amazing how I kind of, and you can learn about, so that I also thought, I think this idea of like learning about intersections
Starting point is 01:50:11 of things. I don't think there are too many people that know like, as much about crypto and quant finance and machine learning as I do. And that's a really nice set of three things to know stuff about. And that was because I had like free time in my job. Okay.
Starting point is 01:50:29 Let me ask the perfectly and practical, but the most important question. What's the meaning of all the things you're trying to do so many amazing things? Why? What's the meaning of this life of yours? Or ours? I don't know. Humans. Yeah, so have you had people say,
Starting point is 01:50:50 asking what meaning of life is, is like asking the wrong question or something? The question is wrong. Yeah. No, usually people get too nervous to be able to say that, because it's like your question sucks. I don't think there's an answer. It's like the searching for it.
Starting point is 01:51:04 It's like sometimes asking it. It's like sometimes asking it. It's like sometimes sitting back and looking up at the stars and being like, huh, I wonder if there's aliens up there. There's a useful like a palette cleanser aspect to it because it kind of wakes you up to like all the little busy, hurried day to day activities, all the meetings, all the things you're like a part of, we're just like ants, a part of a system, a part of another system.
Starting point is 01:51:32 And then when this, asking this bigger question allows you to kind of zoom out and think about it, but there's ultimately, I think it's an impossible thing for a limited capacity, like cognitive capacity to capture, but it's fun to listen to a limited capacity, like cognitive capacity to capture. But it's fun to listen to somebody who's exceptionally successful, exceptionally busy, now who's also young like you.
Starting point is 01:51:53 They ask these kinds of questions about death. Do you consider your own mortality kind of thing and life, whether that enters your mind. Because it often doesn't, it kind of almost gets in the way. Yeah. It's amazing how many things you can like that are trivial, that could occupy a lot of your mind until something, until something bad happens or something flips you. And then you start thinking about the people you love that are in your life, and you start thinking about like holy shit
Starting point is 01:52:25 This right ends exactly. Yeah, I I just had COVID And I had it quite bad. It wasn't what wasn't really bad It was just like I also got a simultaneous like lung infection So I had like almost like bronchitis or whatever. I don't even I don't understand I had like almost like bronchitis or whatever. I don't even, I don't understand that stuff, but it felt, I started, and then you forced to be isolated.
Starting point is 01:52:50 Right. And so it's actually kind of nice. It because it's very, it's very depressing. And then I've heard stories of, I think it's Tron Parker, he had like all these diseases as a child. And he had to like just stay in bed for years. And then he like made Napster.
Starting point is 01:53:06 It's like pretty cool. So yeah, I had about 15 days of this recently, just last month. And it feels like it did shock me into a new kind of energy and ambition. Where there are moments when you were just like terrified at the combination of loneliness. And like, you know, the thing about COVID is like there's some combination of loneliness. And like, you know, the thing about COVID
Starting point is 01:53:26 is like there's some degree of uncertainty. Like it feels like it's a new thing, a new monster that's arrived on this earth. And so, you know, dealing with it alone, a lot of people are dying. It's like wondering like, yeah, you do wonder. I mean, for sure.
Starting point is 01:53:43 And then these, there are, there you've been new strains in South Africa, which do wonder. I mean, for sure. And then these there are the even new strains in South Africa, which is where I was. And maybe I maybe the new strain had some interaction with my jeans. And I'm just going to die, but ultimately, it was liberating. So I loved it. Oh, I love, I love that I got out of it. Okay. Because it also affects your mind. You get confusion and kind of a lot of fatigue. And you can't do usual tricks of psyching yourself out of it.
Starting point is 01:54:08 So you know sometimes it's like, man, I feel tired. Okay, I'm just gonna go have coffee and then I'll be fine. It's like, now I feel tired. I don't even wanna get out of bed to get coffee because I feel so tired. And then you have to confront,
Starting point is 01:54:21 there's no like quick fix cure and you're trapped at home. But that, so now you have this little thing that happened to you, those reminder that you're mortal and you get to carry that flag in trying to create something special in this world, right? With Numerai. Listen, this was like one of my favorite conversations, because the way you think about this world of money and just this world in general is so clear
Starting point is 01:54:49 and you're able to explain it so eloquently, which has really fun, really appreciate you talking to it. Thank you, thank you. Thanks for listening to this conversation with Richard Crabe and thank you to our sponsors, Audible Audio Books, Trial Labs, Machine Learning Company, Blinkist app that summarizes books and athletic greens all in one nutrition drink. Click the sponsor links to get a discount at the support this blog has.
Starting point is 01:55:16 And now let me leave you some words from Warren Buffett. Games are won by players who focus on the playing field, not by those whose eyes are glued to the scoreboard. Thank you.

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