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The following is a conversation with Richard Craib, founder of Numerati, 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 money management in general by empowering people who are interested in trading stocks with modern and quickly advancing tools of machine learning.


Quick mention of our sponsors, audible audio books, Chahal Labs Machine Learning Company, Blankest app that summarizes books and athletic greens all in one nutrition drink click. The sponsor links to get a discount and to support this podcast.


As a side note, let me say that this whole set of events 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, with the Internet and its distributed nature represents 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 and Apple podcast, follow on Spotify, support our patron or connect with me on Twitter, Àlex Friedemann, as usual, although a few minutes of ads now and no ads in the middle.


I try to make this interesting, but I give you timestamp. So if you skip, please go check out the sponsors by clicking on the links in the description. It's the best way to support this podcast. This episode is brought to you by audible and audio book 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 Orrible, which feels like cheating, but it's not the same book.


Examples include American Kozmic, which is about UFOs. Surely you're joking, Mr. Fun by the man himself, Richard Feynman. The Ascent of Money by Niall Ferguson, which is a great history about money. Your Inner Fish by Neil Shubin, which is one of my favorite books on evolution, The NewSat by Stephenie Meyer's, which I think is the best, most objective work of 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 Shirer.


I think it's over 50 hours long and one hell of a crazy ride through the darkest moments of human history. Next two weeks. Orrible is doing a special offer for listeners of this podcast. Only ten books, nine ninety five a month for your first six months. If you visit Orrible, the council selects or texts selects to five hundred five hundred. I don't even know how that works or why you'd want to do that. Just go to our podcast.


That's like that's way better I think. But I might be clueless if you like texting I guess. Go ahead and text. They have thousands of titles to choose from. So visit orrible dot com slash Lex. Now they're considering supporting this podcast. So you know what to do if you want to help out its audible dot com slash likes. This episode also brought to you by Trial Labs, a company that helps build AIB 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, are just curious about machine learning, check them out. Child labs, dot com slash, LAX. They're working on price optimization, early detection, 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.


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. Chahal Labs is legit. If you own a business and want to see how I can help you check them out at trial labs that counselors likes. This episode is also supported by Blankest, my favorite app for Learning New Things. Blankest takes the key ideas from thousands of nonfiction books and condense them down into just fifteen minutes that you can read or listen to.


As part of that, I use blinkers 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 blinkers. You get unlimited access to read or listen to a massive library of condensed nonfiction books. I also use Blinkers forecast to quickly catch up on podcast episodes I've missed. Right now, Blankest has a special offer just for the listeners of this podcast.


Go to Blankest that Karzai selects to start your free seven day trial and get twenty five percent off of a blankest premium membership that's blinking dot com slash Lex. They want me to spell out blankest, but I'm sorry folks, if you don't know how to. Blankest, you're on your own in this world. The 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 was 75 vitamins 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 the 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 official of taking 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 three fish oil. When you go to athletic Greenstar car slash leks to claim the special offer that's athletic Greenstar, come 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 Craib. From your perspective, can you summarize the important events around this amazing saga that we've been living through of Wall Street bets, the Subrata and GameStop and in general, just what are your thoughts about it?


From technical to the philosophical level? I think it's amazing. It's like my favorite story ever.


Like when I was reading about I was like, this is the best. And it's it's also connected with my company, which we can talk about. But what I liked about it is like I like decentralized coordination and looking at the mechanisms that these are Wall Street bets users use to hype each other up to get excited to prove that that they bought the stock and they're holding and and then also to see that how big of an impact that that decentralized coordination had.


It really was a big deal.


Were you impressed by the distributed coordination, the collaboration amongst like I don't know what the numbers are. I know numerous. Looking at the data after all of this is over and done 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 and distribute a 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's an actual username, by the way.


We're talking about there's a website called Reddit and there's Subrata. It's on it. And a lot of people mostly anonymous. I think for the most part, anonymous can create user accounts and then can and just talk on form like style boards. You should know a Reddit as if you don't know. Let's check it out. If you don't know it is, maybe go to the subway. At first it was cute pictures of cats and dogs. That's my recommendation anyway.


Yeah, that would be a good start to read it. When you get into it more, go to our Wall Street pets. It gets dark quickly or we'll probably talk about that.


So. So, yeah. So there's these users and it's there's no contracts like you're saying, no contracts. The user anonymous. But there are little things that that do help. 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 to your next thing. And then they are also putting up screenshots like this.


This is the I I here's the trades I've made and here's a screenshot now. You could fake the screenshot, but but but still, it seems like if you've got a lot of karma and you've had a good performance on the 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 I can follow that trade easily.


And there's a bunch of people like that. So you kind of integrating all that information together yourself to see like, huh, there's something happening here.


And then you jump 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 a flock of whatever birds.


And exactly 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 Tesla novated. 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 too Galaxie brain for for a decentralized community.


How do they come up with it? How do they know that was the right one? 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've 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 shorting means that these are a bunch of people.


When you short a stock, you're betting on the on you're predicting the s going to go down and then you will make money. If it does. And then what's a short squeeze?


It's really that if you if you are a hedge fund and you take a big short position in a in a. 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 they believe will go down.


So it's an interesting situation, particularly because it's not zero sum. If you say let's let's all get together and make a bubble in watermelons, you buy a bunch of watermelons, the price goes up, comes down again. It's it's it's a zero sum game. If someone's already shorted a stock and you can make them short squeeze, it's actually a positive sum game. So, yes, some relatives will make a lot of money, some will lose a lot, but actually the whole group will make money.


And that's really that's really why it's such a clever thing for them to do, coupled with the fact that shorting I mean, maybe you can push back. But to me, always from an outsider's perspective, it 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. OK, I'm speaking not from an economics or financial perspective. I was speaking from just somebody who loves I'm a fan of a lot of people.


I love celebrating the success of a lot of people.


And this is like the stock market equivalent of like Hater's.


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 for sure. And this is designed for but just always felt like these people are just 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 hit on you on social media. Then you get to see that with the mask on.


So so this is like the man that is people like hedge funds that were shorting are like the the sort of embodiment of the evil or just the bad guy, the overpowerful that's misusing their power.


And here's the crowd. The people, they're standing up and rising up.


So it's not just that they were able to collaborate on Wall Street, but 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 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 Elon right now is like manipulating, encouraging people to buy dogecoin or whatever that like that can be good, charismatic leaders and that can be bad, charismatic leaders.


And so it's nerve wracking. It's a little bit scary how much power somebody can have to destroy somebody, because right now we're celebrating. They might be attacking or destroying somebody that everybody doesn't like. But what if they attack somebody that is actually good for this world? So that and that's kind of the the awesomeness and the price of freedom is like it could destroy the world or 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 is there something negative about what happened?


Well, yeah, the cool thing is that they weren't doing anything. The Reddit people weren't doing anything exotic. It was it was a creative trade, but it wasn't exotic. It wasn't it was just buying the stock. OK, maybe they bought some options, too, but it was the hedge fund that was doing the exotic thing. So I like that. It was it's hard to say. Well, you know, we've got together and we put all pooled all our money together and now there's a company out there that's worth more.


What's wrong with that? Yeah, right, but it doesn't talk about, you know, the motivations, which is and then we destroyed some hedge funds in the process.


Is there something to be said about the the humor and. I don't know the edginess, sometimes viciousness of that. I haven't looked at it too much, but it feels like people can be quite aggressive there. So is there. What is that is that what 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, some very sincere liberals, like twenty three years old, whatever, and they go out with signs and say 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 they're scared of the who's scared of the Wall Street, Occupy Wall Street people with the signs.


Nobody but these hedge funds really are scared.


I was scared of the of the Wall Street bets, 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. It's you know, I've been following events in Russia, for example. 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 a people like some of them don't have to be real.


You can probably create bots like it starts getting me, me, me as a programmer. I start to think like me as one person. How much cash can 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 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 two, what impact does that have on financial markets and just destruction of reputations of just or politics?


You know, the bickering of left and right political discourse, the dynamics of that being manipulated by, you know, people talk about like Russian bots or whatever.


We're probably in a very early stage of that.


Right, exactly. And this is a good example. Do you have a sense that most of Wall Street bets folks are actually individual people? Right. That that's the feeling I have, is there's just individual maybe young investors 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 osteopaths for a while, but the reason I found about GameStop was this. I met somebody at a party who told me about it and he was like twenty one years old. And he's like, it's going to go up one hundred percent. And the next one day we were talking about in last year this was probably no, this was yeah.


A few days ago. Oh yeah.


It was like maybe maybe two weeks ago or something.


So it was, it was already high game stuff. But it was just strange to me that there was someone telling me at a party how to trade stocks. He was like twenty one years old. And and I sort of started to look into it. And yeah, he and he did make he made it. Yeah. I mean one hundred forty percent in one day he was right and now he's, you know, supercharged, he's a little bit wealthier and now he's going to wait for the next thing.


And this decentralized entity is just going to get bigger and bigger and they're going to together 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 and in finance, in any kind of position are probably a little bit scary 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. Certainly it makes you think twice about putting a lot of money into a short like these funds put a lot into one, 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? Is it good for the world? Is it good for markets?


I do think that the two kinds of shorting, evil shorting and shorting evil shorting is what Malvin Capital was doing.


And it's like you put a huge position down. You get all your buddies to also shorted and you start making press and and trying to bring this company down. Yeah. And I don't think in some cases you go out after, like, fraudulent companies say this company is a fraud. Maybe that's OK. Like some. But but they weren't even saying, hey, I'm just saying it's a bad company and we're going to bring it to the ground, bring it to its knees.


I'm a quant fund like Dumarey. We always have lots of positions and we never have a position that's like more than one percent of our fund.


So we actually have right now two hundred and fifty shorts.


I don't know any of them except for one because it was one of the meme stocks, but yeah, but it 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.


I say that, but we just want them to to not go up as much as our longs. Right. 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 and 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, because we didn't have market exposure to market risk. And so I think that's a good thing because that means, you know, we can short the oil companies and go long 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 banks, and then there is a platform which is Robinhood, which allows investors to efficiently, as far as you can, correct me if I'm wrong, but, you know, there's those and there's others and this Numerati 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 stocks that we're referring to.


Do you have a thought on actually like 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 or 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, 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 you need to put up more collateral.


So we had a short. It wasn't GameStop, luckily it's BlackBerry and it went up like 100 percent in a day, it was one of these meme stocks, super bad company. The A's don't like it. They always think it's going down. What's a meme stock? A meme stock is kind of a new term for these stocks that catch memetic momentum on Reddit. Yeah, and so the meme stocks were GameStop, the biggest one game stunk, as Elon calls it, AMC and BlackBerry was one.


Nokia was one. So these are high short interest stocks as well. So they these are targeted stocks that some people say, oh, isn't it?


Isn't it adorable that these these people are investing money in these companies that are, you know, nostalgic? It's like you're going to the AMC movie theater. It's like nostalgic. It's like, no, it's not why they're doing it. 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 not a history. Do you have a sense that that. What is your prediction of what our history would have looked like? Well, you wouldn't have needed very many more days of that kind of chaos to to hurt hedge funds. I think it's underrated how how damaging it could have been, because when your shorts go up, your collateral requirements for them go up similar to Robin Hood, like we have a prime broker that says said to us, you need to put up, you know, like forty dollars per per hundred dollars of short exposure and then the next day.


Is it actually you have to put up all of it 100 percent.


And we would like what.


But if that happens, that if that happens to all the shore, all the commonly held hedge fund shorts, because they're all kind of holding the same things, if that happens, not only do you have to.


Cover the short, which means you're buying the bad companies, you need to sell your good companies in order to cover the short right.


So suddenly, like all the good companies, all the ones that the hedge funds like are coming down and all the 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 game stock doubling, AMC doubling, you would have had more and more hedge fund deleveraging.


But so hedge funds, I mean, they get a lot of shit, but they do have a sense that they do some good for the world.


I mean, so OK, first of all, Wall Street bets itself kind of distributer, hedge fund, numerous as a kind of hedge fund. So like hedge funds, a very broad category. I mean, if some of those were destroyed, would that be good for the world or would there be coupled with the the destroying, the evil shorting?


Would there be just a lot of pain in terms of investment in good companies?


Yeah, I think I like to tell people if they hate hedge funds is I don't think you want to rerun American economic history without hedge funds.


So so en masse they're. Yeah. Yeah, they're good. Yeah.


You really wouldn't want to because hedge funds are kind of like picking up. They're making liquidity right. In stocks. And so if you if you love venture capitalists.


They're investing in new technology so good, you have to also kind of 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. 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 eye hedge fund.


And 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 Robin Hood, sort of had to make decisions really quickly, probably had to wake up in the middle of the night kind of thing, you know, and he also had a conversation with Elon Musk on clubhouse, which I just signed up for. It was it was a fascinating one of the great journalistic performances of our time with your model is the phrase for all of Larry's.


Would it be if he gets a call and then his Wikipedia be like journalist and part time entrepreneur?


Is this business, as you know?


I don't know if you can comment on any aspects of that, but like if you were Vlad, how would you do things differently?


What is your thoughts about his interaction with Elon, how he should have played it differently, like. I guess there's a lot of aspects to this interaction, one is about transparency, like how much do you want to tell people about really what went down and potentially involved?


How much? And 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? What do you take from this whole situation?


I was very excited to see the 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 of Lude speaking was like. I was like. Is Vlad like a boomer, like like like he seemed like a 55 year old man talking to a 20 year old, Ellen was like the 20. Yeah, and he's like the 55 year old man. You can see why Citadel are anymore buddies, right?


Like you can you can see why it's like this is this is a nice of bad things. Like he's like a he's got to look like a respectable professional attitude.


Well, he also tried to do like a jokey thing, like, no, we're not being ageist here, Boomer. But like like like a 60 year old CEO of Bank of America would try to make a joke for the kids. That's that's exactly.


Yeah. 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 maybe that's also what I like about Ellen's kind of influence on American business is like he's super like a.. The professional. Right. Like why, why say why say a hundred words about nothing. And so I liked how he was cutting in and saying flat. What do you mean spill the beans bro.


Yeah. So you don't have to be courteous. It's like the first principles thinking is 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, tens 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, that was an opportunity for Vlad to be there and he felt like he wasn't. And do you think there 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. Right. But his presence made it shady. Sometimes I feel like that with Mark Zuckerberg, the CEO of Facebook. Sometimes I feel like, yeah, there's a lot of shady things that Facebook is doing, but sometimes I think he makes it look worse, by the way he presents himself about those things. Like, I honestly think that a large amount of people have Facebook. I just have a huge, unstable, chaotic system.


And they're all not all but enmasse 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. And there's there's something about the realness that Elon has that it feels like CEOs should have had that opportunity.


I think Mark Zuckerberg had that, too, when he was younger, younger, and somebody said, you've got to be more professional, man. You can't say, you know, law to an interview.


And then suddenly he became like the distance person that was like, you'd rather have him make mistakes, but be honest, then be like professional, never make mistakes.




One of the difficult hires, 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 I, you know, take risks as opposed to what the PR I thought to quite a few big CEOs and. The people around them are trying to constantly minimize the risk of, like what he says, the wrong thing. What if she says the wrong thing? It's got to be careful.


It's constantly like, oh, like, I don't know. And there's this nervous energy that builds up over time with large, larger teams where the whole thing may go.


Visit a YouTube, for example.


Everybody I talk to YouTube, incredible engineering, an incredible system, but everybody's scared.


Like, let's be let's be honest about this like 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, a bunch of conspiracy theories, some of which may be true. And just like this mess that we're dealing with and it's exciting is 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 this and like, all right, man, let's just be real.


Let's let's let's both advertise how amazing this frickin 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 handle it. And just being real like that, I suppose that's just the skill maybe can't be taught.


But over time, the 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 numerary, which is an incredible company system idea, I think.


But good place to start. What is Niemira and how does it work?


So Nimura 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 for people to model our data. And the way we do it is by obfuscating the data. So when you get when you look at numerous data that you can download for free, it just looks like like a million rows and of 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 patterns in this data, even though I don't know I don't know what the features mean.


And the data self is a time series data and even not a 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 we only can get it. But that's the kind of data you could never buy yourself unless you had maybe a million dollars a year of budget to buy data.


So what 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 to to trade themselves. But Numerati, by giving away this obfuscated data, we can give them a really, really high quality data set that 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 right is there an underlying data we're talking about of apologize for 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. Like is there may be other totally unrelated to directly to the stock market data, like the like natural language as well, all that kind of stuff. Yeah.


We were really focused on stock data that's specific to stocks.


So things like you can have like a every stock has like a p e ratio for some stocks is not as meaningful, but every stock has that, 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 a history.


And and then the set up of the problem is commonly in quant, 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 in a portfolio to capture some period of time.


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 are 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. 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 then then kind of plumbing like to go long, a stock that's mispriced on one exchange and short on another exchange. That's just arbitrage.


But what we're trying to do is really know, know, know something more about the longer term future of the stock. So from the patterns from these, like, periods of time shares did it, you're trying to understand something fundamental about the stock, not like about deep value, about is big in the context of the market is underpriced, overpriced, all that kind of stuff. So this is about investing. It's not about just, like you said, high frequency trading, which I think is a fascinating open question for a machine learning perspective.


But just to sort of build on that, so you've anonymize the data and now you're giving away the data and then now anyone can. Try to build algorithms that make investing decisions on top of that data or predictions at the top of their data. Exactly.


And so that that's. What is so what does that look like, what's the goal there? 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 excuse model on the data, and that would be quite good, too. But what we're trying to do is by by opening it up and letting anybody participate, we can do quite a lot better than if we modeled it ourselves.


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 percent equity market neutral hedge fund, because usually you're you're charging two percent fees. So if you can do two percent 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 new techniques come out, they get automatically synthesized.


Like if there's a great paper on supervised learning, someone on numerary will figure out how to use it on numerous data.


And is there an ensemble of models going on or is it always 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 weight all of the predictions together is by how much the users are staking on them. How much of the cryptocurrency that they're 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 in the sun, because unscrambling a lot of models together is kind of the key thing you need to do in investing to. Yeah.


So you're putting there's a kind of duality from the user, from the perspective of machine learning. Engineer with your is both a competition, just a really interesting, difficult machine learning problem. And it's a way to to invest algorithmically.


So it and but the the way to invest algorithmically also is a way to put skin in the game that communicates to you that you're the quality of the algorithm and also forces you to really be serious about the models that you build.


So I think everything just works nicely together. Like, I guess one way to say that is the interests are aligned. So it's just like poker is not not fun when it's like for very low stakes. The higher the stakes, the more the dynamics of the system starts playing out correctly. As like a small side note, is there something you can say about. Which kind, looking at the big, broad view of machine learning today, or A.I., 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 networks suck recurring, you'll never suck, transformers suck or they're awesome, like old school.


Sort of more basic kind of classifiers are better, although there is there some kind of conclusion so far? They say there is definitely something pretty nice about tree models like like X, and they just seem to work pretty nicely on this type of data.


So out of the box if you're trying to come. One hundred in the competition in the tournament, maybe you would try to use that, but what's what's particularly interesting about the problem that not many people understand, if you're familiar with machine learning, this typically will surprise you when you model our 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 if you train the model, it would say put all your money into tech, super good. But what you want to do is actually be very careful of how much of the exposure you have to certain features.


So on Nimura, what a lot of people figure out is actually if you train a model on this kind of data, you want to somehow neutralize or minimize your exposure to these certain features, which is unusual because if if you did train a stoplight or stop street detection on computer vision, the your favorite feature, let's say you could you have an auto encoder and it's figuring out, OK, 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? The thing that's helping you, your model the most and that's actually the counterintuitive thing you have to do with machine learning on financial data.


So reducing it's reducing your exposure would help you generalize to things that are basically a financial data, has a large amount of patterns that appeared in the past and also a large amount of patterns that if not appear in the past. And so, like in that sense, you have to reduce the exposure to red lights to to the color red. That's interesting.


But how much of this is art and how much of a science, from your perspective so far in terms of as you start to climb from the hundredth position to the ninety fifth in the competition?


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 numerary. 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 one hundred percent. But it doesn't in the long run, work out very well.


And so the best users are are trying to stay high for as long as possible and not not necessarily try to beat thirst for a little bit.


So for me, a developer, machine learning researcher, how do I let Freeman participate in this competition and others? So 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 numerary, sign up, download the data. And on the data is pretty small in the data pack you download, there's like an example script Python script that just builds a 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's needs to be some kind of structure that communicates with some kind of API because the whole.


Yeah, how does your model, once you build, wants to create a little baby Frankenstein. Yeah. Does it then live in it. Well, we want you to keep your baby Frankenstein at home. Take care of it. We don't want it. OK, so we 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. Yeah. That whole hedge fund is built from models we never, ever see in the code. But it's important for the users because it's their IP.


They want to give it to us as brilliant. So they've got it themselves, but they can basically almost like license the the predictions from that.


So think about it. What some users do is they set up a computer server and we call Numerati compute. It's like a little 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.


OK, cool. So that's is that described somewhere like what the preferred is the Awassa 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 to download the data, maybe play around, see if you can modify the basic algorithm provided in the same example, and then you would set up a little server on the US that then runs this model and takes Peng's and then makes predictions. And so how does your own money actually come into play doing the stake of cryptocurrency?




So you don't have to stake. You can start without staking in 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 overfit.


But then you can get numerary many different ways. You can buy it on, you can buy some on Coinbase, you can buy some on Younus swap, you can buy some on finance.


So what did you say this is how do you pronounce it? So this is the new Marai cryptocurrency. Yeah. Anma Anmar was it. You just say Atama. It is.


It is technically called numerary Niemira.


I like it. Yeah but Ademar simple Alamar numerary. OK, so and you could buy it you know basically anywhere.


Yeah. So it's a bit strange because sometimes people like is this like pay to play. Right. And it's like sware. 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 from us. Right.


It's like, it's also we never if you're, if you do badly, we destroy your cryptocurrency.


OK, 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 like we're the house. Like we're definitely on the same team. Yes. You're helping us make a hedge fund that's never been done before. Yes.


Again, interests are aligned. There's no there's no tension there at all, which is really fascinating, given away everything. And then the IP is owned by sort of the code. You never share the code. That's fascinating. So since I have you here and you said one hundredth, I didn't ask how many. So we'll just.


But if I 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 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 try.


And, uh, but you also going to need a lot of compute, probably. And so some of the best uses are are, you know, actually the very first time someone won on numerous. I would I wrote them a personal email like, you know, you've won some money. We're so excited to give you three hundred dollars. And then they said, I spend way more on the computer, but this is fundamentally a machine learning problem.


First, I think this is one of the exciting things I don't know for in 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, great people, but it feels like from the community that have experienced these are people who see finance as a fascinating problem, space source of data.


But ultimately they're machine learning people or EHI people, which is a very different kind of flavor of community.


And 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 in and tell me give me some hints, um, how I can do all of this thing, because this boomer I'm not sure I still got it, but because some of it is it's like cargo competitions, like some of it.


Is certainly set of ideas like research ideas and 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 works like tricks. I mean, you could argue most of deep learning research is just tricks on top of tricks.


But there is 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 cargo 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.


And this is like, OK, cool. But what's cool is you're you're the out of sample is the real life stock market. We we don't even know like we don't know the answer to the problem.


We don't like you'll have to find out live. And so we've had users who've like submitted every week for for like four years because it's kind of a it's a we say it's the hardest data science problem on the planet.




And in that sense, maybe sounds like maybe a bit too much like a marketing thing, but it's the hardest because the stock market is like literally they're 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 a numerator, you really have something that that is like working on the real stock market.


Yeah, because there's like humans involved in the stock market. That's you know, you could argue that maybe 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?


And you start thinking about that, but ultimately also boils down to a problem where the data is accessible, it's made accessible, made really easy and efficient at submitting algorithms. So it's not just, you know, it's not about the data being out there like the weather. It's about making the data super accessible, making a building a community around it like this is what imaging that 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 a community. And that 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 is mechanisms by which standards, mechanisms by which to judge your performance, all those kinds of things, and the 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 the biggest one is it's it's non stationary time series. We've tried to regularize the data so you can find patterns by by doing certain things to the features in 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 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 it's even the training data has the same same dislocations. And so, yeah, it's so. And then there's yeah. There's so many things that might, might, you might want to try this, this like there's unlimited possible number of models.




And so.


By by having it be open, we can at least search that space, zooming back out to the philosophical, you said the numeral is very much like Wall Street that 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, the two. So maybe can you speak to the similarities and the differences and in which ways more and more powerful? In which way is Wall Street gets more powerful?


Yeah, this is why the Wall Street story is so interesting to me, because it's like feels like connected and looking at how just looking at the form of Wall Street that it's I was talking earlier about how how can you make credible claims. You're anonymous. OK, well, maybe you can take a screenshot or maybe you can upvote someone, maybe you can have karma on Reddit and those kinds of things make this emerging thing possible. Numberi. 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 get lucky and some of them did.


Yes, staking was are like solution to could we 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 bot accounts anymore. Either I stake my accounts, in which case I should believe in them because I could lose my stake or I don't. And that's a very powerful thing that having a negative incentive and a positive incentive can make can make things a lot better.


And staking is like this. Is this really nice, like key thing about block change?


It's like something special you can do where they're not even trusting us with their stake.


In some ways they're trusting the block chain. 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. Then our users are staking on their models as powerful in some sense from a human psychology perspective.


It's fascinating that whilst you both worked at all right, that amidst that chaos, emergent behavior like behavior that made sense emerged. It would be fascinating to think of numerous style staking could then be transferred to places like Reddit, you know, and not necessarily for financial investments.


But I wish sometimes people would, you know, would have to stake something in the comments they make on the Internet. Yeah, think that's that's the problem with anonymity is like anonymity is freedom and power that you don't have to you can speak your mind, but it's too easy to just be shitty.


Yeah, exactly.


And so this I mean, you're making me realize from a profoundly philosophical aspect, memorize staking is a really clean way to solve this problem.


But it's a really beautiful way. Of course, it only with numerary currently works for a very particular problem. Right.


Not for human interaction on the Internet. But that's fascinating.


Yeah, there's nothing to stop people. In fact, we've open sourced like the code we use for staking in a protocol we call erasure. And any if Reddit wanted to, they could even use that code to do have have enabled staking on our Wall Street bets. And they're actually researching now. They've had some etherial grants on how could they have more crypto stuff in there in a theory, 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 my I have staked millions against this claim. That's powerful. And then what could you do?


And of course, I don't have to be millions. It can be just a very small amount, but then just a huge number of users doing that kind of stake.


Exactly. That, you know, that could change the Internet, it would change. And then Wall Street, they 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 numerary style infrastructure where A.I. systems backed 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 A.I. systems with high level human supervision?


Yeah, the thing is that some of them could be could be bad actors. Some of the humans know, well, these systems could be tricky. So actually, I once met a hedge fund manager and it's kind of interesting. He said a 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. Yeah, 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 so arrogant.


Like, of course you can you can't do this, but maybe he can and maybe he really isn't doing things he knows he could do, but would 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, there would be like one person that says, hey, maybe and then they get trampled over.


That's that's the terrifying thing. Actually, there's a lot of people have written about this is somehow that, like little voice, that's human morality gets silenced when we get in groups and start chanting.


Yeah, and that's terrifying. But like, I think maybe I misunderstood.


I thought that you're seeing ISIS systems can be dangerous, but you just describe how he was dangerous. So which is safer. So, I mean, one thing is Niemira. Yeah. So Wall Street bets these kinds of like these kinds of attacks, like it's not possible to to model numerous data and then come up with the idea from the model. Let's short squeeze game start. Right. It's not even framed in that way. It's not like possible to have that idea.


So but it is possible for that kind of a bunch of humans. So I think. Is it's numerary could get very powerful without it being dangerous, but Wall Street, that 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 about numerous data today and numerous signals and what that looks like in 10, 20, 30, 50, 100 years. You know, like right now, I guess maybe you can correct me, but the data that we're working with is like a window so, you know, anonymized, obfuscated window into a particular aspect, the time period of the market. And, you know, 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 where you could include kind of human to human communication that was available for like to buy GameStop, for example, on on Wall Street.


But so maybe the Staback can you speak to what is numerous signals and what are the different data sets that are involved?


So with numerous signals, you're still providing predictions to us, but you can do it from your own data sets. So numerators all you have to model our data to come up with predictions. Numerous 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. Mm hmm. And, um, and that's why it's particularly valuable, because it's going to be signals.


You're only rewarded for signals that are orthogonal to our core signal. So you have to be doing something uncorrelated. And so strange alternative data tends to have that property. There isn't too many other signals that are correlated with.


With, you know, 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 signals in thousands that we use at Nomura. And the structure, the signal is similar.


So this is just numbers and time series data. It's the. Exactly. And it's just like it's kind of providing a ranking of stocks. So you just say give it a one. Means you like the stock. Zero means you don't like the stock and you provide that for the five thousand stocks in the world. And they somehow converted the natural language that's in the wash.


Exactly. So then they made the open source this CoLab notebook. You can go and see it. And so, yeah, it's taking that, making a sentiment score and then turning it into a rankest test score.


Yeah. Like the stock sucks. So the stock is awesome. And then converting. That's that's Facetune. Look at that data would be fascinating. So on the signal side, what's the vision long term, what do you see that becoming? So we want to manage all the money in the world. That's his mission. And to get that we need to have all the data and have all of the talent. Like, there's no way to first principles if you had really good modeling and really good data that you would lose, right?


It's just a question of how much do you need to get to get really good. So Numerati already has some really nice data that we give out this year. We are taxing that. And I actually think we'll 10x the amount of data we have on Nimura every year for at least the next ten 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 that can turn that into a signal and give it to us.


And in some sense, that kind of data has the edge cases, the weirdnesses, 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 entered through this back door.




And it's it's also a little bit shorter term. So the signals are about a seven day time horizon and the numerator like a 30 day. So it's often for foster situations.


You've written about a master plan and you've mentioned which I love in a similar sort of style of big style thinking you would like numerary to manage all of the world's money.


So how do we get there from from yesterday to several years from now, like what's what is the plan?


So do you've already started to allude to get all the data and get it?


Yeah, all the talent Yemens 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 Ph.D. 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 numerary 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 numerary problem. It feels like a lot of the knowledge there is also transferable to other domains.


Exactly. It's our top one of our top users is he works at NASA Jet Propulsion Lab. Yeah. And he's he's like, amazing. I went to go visit him there. And it's like he's got like numerary posters and he's like it's like it looks like, you know, the movies 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 to Europa Clipper mission, actually.


Literally what you're saying, literally, we he's smart enough that we really want his intelligence to reach the stock market because the stock market's a good thing. Hedge funds are a good thing. All kinds of hedge funds especially. But we don't want him to quit his job so he can just do nimura on 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 their stock markets are good for my sort of outsider perspective.


Is there a sense do you think trading stocks 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, the way you think about it is it fundamentally is still investing. I do think, um, I mean, it's a good question, it's 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 applies to investing.


Like one thing you don't do in gambling is put all your money in one bet you have bankroll management and it's a key part of it. And small alterations to your bankroll management might be better than improvements to your skill. So there and then there are things we care about in our fund, like we want to make a lot of independent bets.


We talk about it like we want to make a lot of independent bets, because that's going to be a higher Sharpe than if you have a lot of bets that depend on each other like all in one sector. But but, yeah, I mean, the point the the point is that you want the prices of the stocks to be to be reflective of of how of the value of the underlying value.


Yeah. Yeah.


You shouldn't have there be like a hedge fund that's able to say, well, I've looked at some data and all of this stuff super mispriced like that, super bad for society. If it's 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 with these? Whatever they're called, like derivatives, like the, you know, options and shorting and all that kind of stuff, it's like layers of game on top of the actual like what you said, which is like the basic thing that Wall Street was doing, which is like just buying stocks.


Yeah, there are a lot of games that people play 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 collateralized debt obligations like these are the these are the kind of like enemies of 2008 and then the long term capital management thing.


It was like was like they had 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, the common sense just like went out the window.


So the I yeah, I don't I don't I don't respect long term capital management.


OK, but Numerati doesn't actually use any derivatives unless you call shorting derivative.


We just we do put money into companies. We and that does help the companies we're investing in.


It's just in little ways. We really did buy Tesla and and it did. And we you know, we were not we played some role in in that success.


Super small, make no mistake.


But still, I think that's important. Can I ask you a pothead question, which is what is money, man?


So if we just kind of zoom out and look at it, because I'd love to talk to you about cryptocurrency, which perhaps could be the future of money in general.


How do you think about. Money, he said, Numerati, the vision, the goal is to to run, to manage the world's money. What is money? In your view? 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 talked about things like this, like what's what is the company really?


It's like it's a bunch of people who, like, kind of show up to work together and they solve a problem and they might not be a stock out there that that's trading that represents what they're doing. But it's it's not the real thing. And being involved in crypto like early put in crowd sale of Ethereum and and all these other things and different crypto hedge funds and things that have invested in and it's like it's just it's just kind of like.


It feels like. How I used to think about money stuff is just it's just like totally warped because you yeah, you kind of you stop caring about, like the the price and you care about, like the product. So buy the product.


You mean like the different mechanisms that money is exchanged. I mean money is ultimately a kind of you know, on one is a store of wealth, but it's it's also a mechanism of exchanging wealth. But that like what wealth means becomes a totally different things with cryptocurrency, where it's almost like these little contracts, the agreements, these transactions between human beings that represent something that's bigger and just like cash being exchanged. Seven-Eleven, it feels like. Yeah.


Maybe outlines of what is finance like you. It's what are you doing when you can when you have the ability to 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, like if you didn't have the money. But now, like, weirdly, you can get it with and like, yeah, all you have is this like loan, which is like so now you can bring you can bring a different future into the world. And that's how I when I was saying earlier about if you rerun American history, economic history without these these these things like, you know, a lot of take out loans, you're not allowed to have have derivatives, you're allowed 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 by kind of bringing the future forward.


Finance is empowering. It's we sometimes forget this, but it enables innovation and enables big risk takers and bold builders that ultimately make this world better. 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?


Yes, and my friends told me about Bitcoin and I 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 like that.


This could be valuable. And then I but I did.


So I didn't feel like I was early in cryptocurrency, in fact, because I was like it was like 2014. It felt like a long time after Bitcoin.


And then but then I really like some of the things that 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 like the different constructs you could have inside of a theory and that you couldn't have on Bitcoin Reichsmark contractional.


Exactly. Yeah. And even the there were even spoke about different. Yeah.


Different constructions you could have. Yeah. That's the cooldowns between Bitcoin and Ethereum of it's in the space of ideas.


Feel so young. Maybe I wonder what cryptocurrency 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 a cryptocurrency that you're especially find interesting that technically, financially, philosophically, you think this is something you're keeping your eye on?


Well, I don't really I'm not looking to like invest in crypto currencies any more, but I, I they are I mean, there 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 there are some that I like the privacy ones I, I like, I like the cash for. It's like coolness. It's actually it's like a different kind of invention compared to some of the other things I can speak to. Just briefly to privacy, what is there some mechanisms of preserving some privacy of the site? I guess everything is public.


Yeah, that's the yeah.


None of the transactions are private. Yeah.


And so, you know, even like I have some of my I have some numerary and you can just see it, in fact you can go to a website and says like, you know, like ether scan and I'll say like numerary founder. And I'm like how the hell you guys know that.


So they can reverse engineer whatever that's called. Yeah. So they can see me move it to they can see me. Oh. Why is he moving it. Yeah.


So, so but yeah. Zarkasih then they also when you can make private transactions you can also play different games. Yes. And it's unclear, it's like what's quite cool but like I wonder what games were being played there.


I want to know.


So from from a deeply analytical perspective, can you describe why Dogecoin is going to win, which it surely will.


It very likely will take over the world and once we expand 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 Dogecoin, where you've spoken to some of the the meme stocks, the memetics of the whole thing that it feels like?


The joke can become the reality, like the meme, the joke has power in this world. Yes, fascinating. Exactly.


It's it's 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 the catalyst for everybody on the Internet. Kind of like spreading the joke, right? Exactly. The joke of it. So it's it's it's the initial spark of the fire for Wall Street, but type of situation.


Yeah. And that's fascinating because jokes seem to spread faster than other mechanisms, like funny shit is very effective and captivating the like the discourse on the Internet.




And I think you can have like the I like the one meme like Doege. I haven't heard that name in a long time.


Yeah. Like I think back to that very often. That's funny.


Every time I think back to it there's a little probability that I might buy those guys.


And so you just have millions of people who have had all these great jokes told them, and every now and then they reminisce. So that wasn't yeah, that was really funny. And then they're like, let me buy them.


Wouldn't it be interesting if, like, the entire if you 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 that were high and probably some really advanced drugs and we're all just laughing non-stop.


It's some weird, like dystopian future of just humor. Elon has made me realize how good it feels to just not take it 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 Lall is like 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. I often think that, like, will memes save the world or destroy because I think both the possible directions.


Yeah, I think this is a big problem. I mean, 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 aside, an American like I really want to have a sincere conversation.


It's like hard to even keep a straight face. Yeah. Because everything is so there's so much levity. So it's complicated. I like how sincere actually like your Twitter can be.


Like I I'm in love with the world. Yeah. I get so much shit for it.


I'm not I'm never going to stop because I was like, do you have to be able to sometimes just be real and be positive and just be see the cliched things which ultimately those things actually capture some fundamental truths about life? Yeah, but it's a dance and I think John does a good job of that now from an engineering perspective of being able to joke. But every once in a while, mostly to pull back and be like his real problems, let's solve them and so on, and then be able to jump back to a joke that's ultimately I think, I guess, a skill that we have to learn.


I but I guess your advice is to invest everything anyone listening owns into Dogecoin. That's what I heard from this direction. Exactly.


Yeah, I husband is unavailable. Just go straight to Dogecoin.


You're running a successful company. And it's just interesting because my mind has been in that space of potentially being one of the 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 asking someone to invest in your company, don't say. I think maybe one day we might make a million dollars.


Um, when you actually believe something else, you actually believe you're actually more optimistic, but you're toning down your optimism because you want to 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 investment. You're happy. So you should play the real game. 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've always feel like I yeah, I start you can start narrowing, narrowing your focus because ten people are telling you, you know, you've got to care about this. Boring thing that won't matter five years from now, and you should push back and do the real play, the real game to be bold. So both I mean, there's a there's an interesting duality there.


So there's the way you speak to other people about like your plans and what you are like privately just in your own mind.


And maybe it's connected with what you were saying about the sincerity as well. Like if you if you appear to be sincerely optimistic about something that's big or crazy, it's putting yourself up to be kind of like ridiculed or something.


Yes. And so if you say my mission, 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. 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 when those people get in a room together, like they can actually do it.


Yeah, yeah. There's yeah, that's that's an also makes life really fun when you're in that room.


So all that together ultimately. I don't know. That's what makes this crazy ride of Australia really look fun. And is example a person who succeeded that many other inspiring figures, which is said I used to be a Google and there's.


There's something that happens sometimes when a company grows bigger and bigger and bigger, where that kind of ambition kind of quiets down a little bit. Yeah, 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, I still love that dream of that, you know, these Toscan books, but in every way possible, make the world's information accessible.


Same with Wikipedia.


Every time I open up Wikipedia, I'm just, ah, inspired by how awesome humans are mad at creating this together.


I don't know what the meetings are over there, but they it's just beautiful.


Like what they've created is incredible. 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 and it's strange to me also, I think you're right that this how many boring companies they are, something I talk about, especially in FinTech, it's like, why am I excited about this is so lame?


Like, what is this isn't even as important.


Even if you succeed, this is going to be like, terrible.


Yeah, this is not good. And it's just strange how people can kind of get fake, enthusiastic about, like, boring ideas. Yeah. When there's so many bigger ideas that. Yeah. I mean you read these things like this company raises money and it's like that's a lot of money for the worst idea I've ever heard. Some ideas are.


Really? So I worked autonomous vehicles quite a bit and so many ways in which you can present that idea to yourself, to the team you work with just yet, like to yourself, when you're quietly looking in the mirror in the morning, that's really boring or really exciting, like if you're really ambitious with autonomous vehicles there. It changes the nature of like human robot interaction to change 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 by manufacture. I mean the cars, the transportation is so fundamentally connected to cars. And if that changes, it changes the fabric of society, of movies, of everything.


And if you go bald and take risks and go be willing to go bankrupt with your company as opposed to cautiously, you can 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 are really afraid. The entirety of their marketing is grounded in fear and presenting enough smoke to where they keep raising funds so they can consciously use technology of previous decade or previous two decades to kind of test vehicles here and there, as opposed to do crazy things in bold and go huge scale to huge data collection.


And yet so that's just an example.


Like 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 interaction do you have with investors or with investors? Like the whole process is the entire mystery to me.


Is there some people that just have influence on the trajectory of your thinking completely, or is it just this collective energy behind the company?


Yeah, I mean, I came here and I, I, I was amazed how. Yeah. People would. I was only here for a few months and I met some incredible investors, but and I almost run out of money and once they invested I was like, I am not going to let you down.


And I was like, OK, gonna send them like an email update every like three minutes. Yeah.


And then I don't care at all.


So we kind of want to, I don't know, like so for some 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 very little for them to add. Right. There's little for them to add on product. There's a lot for them to add on like business development. 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 to tell the investors, so there basically is like, I believe in you, there's something I like to cut your jib.


There's something in your idea, in your ambition and your plans that I like. And it's almost like a pat on the back and say, go, go get em, kid.


Yeah, it is a bit like that. And that's cool. That's a good way to do it. I'm glad they do it that way.


Like the one meeting I had, which was like really good with this was meeting Howard Morgan, who who's actually a co-founder of Renaissance Technologies in the late 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 like so, you know, use mathematical models.


And then he was like, I yeah, I started Renaissance.


I know a bit about this. And then I was like, oh, my God.


So, yeah, but and then I think he kind of said, well yeah. He said, well because I was he was working at first round capital as a partner and they kind of said 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 they end up I was just saying, you convince them that 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 some tech company, not a hedge fund, right?


Yeah, numerous boyin. It's what caught my eye. There's something special there. So I really do hope you succeed in the obvious. 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 Simons.


He comes up in another world of mine really often, and he's just a brilliant guy on the mathematics side as a mathematician. But he's also brilliant finance hedge fund manager guy. Have you gotten the chance to interact with him at all? Have you learned anything from him on the math and the finance and the philosophy life side of things?


I've played poker with him. It was pretty cool. It was like actually in the show billions. They kind of do a little thing about this poker tournament thing with all the hedge fund managers, and that's a real life thing.


And they had a lot of like World Series of bracelet, Worcester's poker 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 why are you here? And I was like, oh, Howard sent me, you know, he's like, go play this tournament, meet some of the other players and then the Texas Hold'em.


Yeah. That Texas Hold'em tournament. Yeah. Do you play poker yourself or is it.


Yeah, I do. I mean it was crazy. On my right was the CEO, who's the current CEO of Renaissance, Peter Brown, and Peter Muller, who's a hedge fund manager, PDT.


And yeah, I mean it was just like and then, you know, just everyone and then all these great World Series like people I know from like TV and Robert Mercer, who's fucking crazy, he was there. He is a guy who who who donated the most money to Trump. And he's just like, it's a lot of personality character. Yeah. Geez, that's crazy. So it's quite cool. How. Yeah. Like the it was really fun.


And then I managed to knock out Peter Miller. I have a I got a little trophy for knocking him out because he was a previous champion.


In fact, I think he's won the most and he's won three times. Super smart guy.


But but but I will say Jim outlasted me in the tournament and they're all extremely good at poker.


Yeah, but they're also so it was a ten thousand dollar 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 Ribis and like they all do a shit ton of ribis for charity.


Yeah. So immediately they're like going all in and I'm like, man, like so I end up adding more as well. So it's like you couldn't play at all without doing that.


Yeah. The stakes are high, but you're you're connected to a lot of these folks.


They're kind of titans of just of economics and tech in general. Do you feel burdened from this young guy?


I did feel a bit out of 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 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. Yeah. And then they would say even things like, remember Peter. Yeah, said to me something like, I don't think A.I. is going to 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 but he can see he's I can see it having a really big impact on things like self-driving 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 there was that same day that Libra I think it is the poker playing. I started to beat like the humans. Yeah. So it was kind of funny hearing them like say, oh, I'm not sure I could ever attack that problem.


In that very day, it's attacking the problem of the game we're playing.


Well, there's a kind of a magic magic to. Somebody who is exceptionally successful. Looking at you, giving your respects, 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 from my interactions with people that it's a kind of prod to say, like, prove me wrong. Yeah, that's ultimately that's that's how those guys talk.


They see good talent and they're like, yeah. And I think they're also saying it's not going to succeed quickly in some way.


They're like, this is going to take a long time and maybe maybe that's good to know. Mm hmm.


And certainly I in 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 artificial does in that sense. You converting it to a data set is one of the biggest gifts to. The research community to the whole anyone who loves data science and I this is this is kind of fascinating.


I'd love to see where this goes actually think I say sometimes long before Ajai destroys the world, a narrow intelligence will win all the money in the stock market way so narrow.


Yeah. And I want to I don't know if I'm going to be the one who invents that.


So I'm building numerary to make sure that that never I know uses our data to giving a platform to where millions of people can participate and do build that Naropa themselves. People love it when I ask this kind of question about books, about ideas and philosophies and so on.


I was wondering if you had books or ideas, philosophers, thinkers had an influence on your life when you were growing up or just today that you would recommend that people check our blog posts, podcasts, 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 what I was reading zero to one while coming up with Nimura, it's like I was like halfway through the book.


And I really do like a lot of the ideas there. And it's it's also about kind of thinking big and, uh, and also it's like a peculiar little book. It's like, why like this little picture of the hipster versus Unabomber. And it's it's a weird look. So there's kind of like some depth in terms of a book. And if you're thinking of doing a startup. Yeah, it's a good book.


Book I like a lot is maybe my favorite book is David Deutsch's Beginning of Infinity. Mm. Yeah. Um, I just found that so. Optimistic, it puts you everything you read in science, it like makes the world feel like kind of colder because like it's like, you know, we're just just coming from evolution and coming from nothing.


Nothing should be this way or whatever. And humans are not very powerful. We're just like scum on the earth. And the way Davidovich these things and argues that he argues them with the same rigor 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. Yeah. Without being like a hippy. You mentioned kind of advice for startups. Is there in general, whether you do a startup or not, you have advice for young people today. You're like an example, somebody who's paved their own path. And where I would say exceptionally successful is their advice. Somebody who was like 20 today, 18 undergrad are 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 unless you're prepared to make it your life's work like that. A really good way of putting it. And a lot of people think, well, you know, this semester I'm going to take a semester off and in that one semester I'm going to 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.


You should be like super into the idea, so into it that you want to spend a really long time on it.


Is that more about psychology or actual time allocation? Like is it literally the fact that you give one hundred percent for potentially years for it to succeed? Or is it more about just the mindset that it's required?


Yeah, I mean, I think well I think yeah.


You don't want to have certainly to want to have a plan to sell the company quickly or something that it's like, oh, it's like a company that has a very it's like a big fashion component, like it'll only work now. It's like an app for something.


So yeah I that's, that's a big one. And then I also think.


Something I've 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 to be where to basically accelerate how long numerary 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 a huge amount of money and learn whatever you want, and yet 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 conditioned room and that I was afraid. The quant situation is I mean, when you present this is really brilliant, that it's exceptionally valuable, the lessons you learned because you get to get paid while you learn from others.


If you see that, if you see jobs in in the space of your passion, that way there is just an education is like the best kind of education. But of course, you have, from my perspective, 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 and you get you know, and then you convince yourself, like, well, I have to pay these fees for the car, for the house, blah, blah, blah.


And then and there's momentum and all of a sudden you're on your deathbed and there's grandchildren and you're drinking whiskey and complaining about kids these days.


Yeah. 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, I remember on my desk I had the like a bunch of papers on quant finance, a bunch of papers on optimization and then a paper on a theory. I'm just on my desk as well and the white paper. And it's like it's amazing how much how kind of and you can learn about.


So I was that I think this idea of like learning about intersections of things, I don't think that 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.


OK, let me ask the perfectly 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 that people say asking what the meaning of life is, is like asking the wrong question or something?


The question is wrong. Yeah. No, that usually people get too nervous to be able to see that because it's like your question sucks. I don't think there's an answer. It's like the searching for it is 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 there's a useful like a palate 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 like a part of. We're just like ants. A part of a system are part of another system. And and then this asking this bigger question allows you to kind of zoom out and think about it. But ultimately, I think it's an impossible thing for a limited capacity, the cognitive capacity to to capture.


But it's fun to listen to somebody who is exceptionally successful, exceptionally busy now, who's also young, like you, to ask these kinds of questions about like death.


You know, do you consider your own mortality kind of thing and life, whether that enters your mind, because it often doesn't get 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 are in your life.


And you started thinking about like, holy shit, this right ends.




Yeah, I, I, I just had covid and I had a quite bad it wasn't what wasn't really bad is 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. That's tough, but if I started and then you forced to be isolated, right, and so it's actually kind of nice because it's very it's very depressing. And then I've heard stories of I think it's Sean 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.


It's like pretty cool.


So, yeah, I had about 15 days of this recently, just last month. And it it feels like it did shock me into a new kind of energy and ambition.


Were there are moments when you were just like terrified of the combination of loneliness and like, you know, the thing about covid is like there's some degree of uncertainty. Yeah. It feels like it's a new thing, a new monster that's arrived on this earth. And so and, 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. And there are even new strains in South Africa, which is where I was. And maybe maybe the new strain had some interaction of my genes and I'm just going to die. But ultimately, it was liberating.


So I loved it. I love it. I love that I got out of it, OK, because it also affects your mind. You get you get confusion and kind of a lot of fatigue and you can't do your usual tricks of psyching yourself out of it. So, you know, sometimes it's like, oh, man, if you're tired, OK, I'm just going to go have coffee and then I'll be fine. It's like now it's like I feel tired.


I don't even want to get out of bed to get coffee because I feel so tired. And then you have to confront there's no quick fix. Cure. Yeah. And you're trapped at home with 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 in in in trying to create something special in this world.


Right. When Dumarey listen, this is like one of my favorite conversation because you're the way you think about this world of money and just this world in general is so clear and you're able to explain it so eloquently. Richard has really fun. Really appreciate you talking. Thank you.


Thank you. Thanks for listening to this conversation with Rachel Craig and thank you to our sponsors, audible audio books, trailer labs, machine learning company, blankest app that summarizes books and athletic greens all in one nutrition drink click. The sponsor links to get discount and to support this podcast. 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 for listening and hope to see you next time.