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


small model | large model

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The following is a conversation with Richard Crabe,
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founder of Numeri, which is a crowdsourced hedge fund,
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very much in the spirit of Wall Street Bets,
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but where the trading is done not directly by humans,
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but by artificial intelligence systems
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submitted by those humans.
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It's a fascinating and extremely difficult
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machine learning competition
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where the incentives of everybody is aligned,
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the code is kept and owned by the people who develop it,
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the data, anonymized data is very well organized
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and made freely available.
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I think this kind of idea has a chance to change
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the nature of stock trading
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and even just money management in general
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by empowering people who are interested in trading stocks
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with the modern and quickly advancing tools
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of machine learning.
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Quick mention of our sponsors,
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Audible Audio Books,
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Trial Labs Machine Learning Company,
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Blinkist app that summarizes books,
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and Athletic Greens, all in one nutrition drink.
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Click the sponsor links to get a discount
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and to support this podcast.
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As a side note, let me say that this whole set of events
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around GameStop and Wall Street Bets
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has been really inspiring to me as a demonstration
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that a distributed system,
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a large number of regular people
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are able to coordinate and collaborate
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in taking on the elite centralized power structures,
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especially when those elites are misbehaving.
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I believe that power in as many cases as possible
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should be distributed.
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And in this case, the internet, as it is for many cases,
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is the fundamental enabler of that power.
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And at the core, what the internet
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in its distributed nature represents is freedom.
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Of course, the thing about freedom
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is it enables chaos or progress, or sometimes both.
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And that's kind of the point of the thing.
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Freedom is empowering, but ultimately unpredictable.
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And I think in the end, freedom wins.
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If you enjoy this podcast, subscribe on YouTube,
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review it on Apple Podcasts, follow on Spotify,
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support on Patreon, or connect with me on Twitter
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at Lex Friedman.
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And now, here's my conversation with Richard Crabe.
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From your perspective, can you summarize
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the important events around this amazing saga
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that we've been living through of Wall Street Bets,
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the subreddit and GameStop, and in general,
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just what are your thoughts about it
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from a technical to the philosophical level?
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I think it's amazing.
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It's like my favorite story ever.
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Like when I was reading about it,
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I was like, this is the best.
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And it's also connected with my company,
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which we can talk about.
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But what I liked about it is like,
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I like decentralized coordination
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and looking at the mechanisms
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that these are Wall Street Bets users use
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to hype each other up, to get excited,
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to prove that they bought the stock and they're holding.
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And then also to see that how big of an impact
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that that decentralized coordination had.
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So it really was a big deal.
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Were you impressed by the distributed coordination,
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the collaboration amongst like,
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I don't know what the numbers are.
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I know I'm numerized looking at the data.
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After all of this is over and done,
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it'd be interesting to see like
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from a large scale distributed system perspective
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to see how everything played out.
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But just from your current perspective, what we know,
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is it obvious to you that such incredible level
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of coordination could happen
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where a lot of people come together in a distributed sense,
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there's an emergent behavior that happens after that.
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No, it's not at all obvious.
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And one of the reasons is the lack of credibility.
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To coordinate with someone,
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you need to make credible contracts or credible claims.
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So if you have a username on our Wall Street Bets,
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like some of them are, like deep fucking value
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is one of them.
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That's an actual username.
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By the way, we're talking about,
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there's a website called Reddit
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and there's subreddits on it.
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And a lot of people, mostly anonymous,
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I think for the most part anonymous,
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can create user accounts
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and then can then just talk on forum like style boards.
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You should know what Reddit is.
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If you don't know what Reddit is, check it out.
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If you don't know what Reddit is,
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maybe go to the awesome subreddit first,
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aww with cute pictures of cats and dogs.
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That's my recommendation.
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Anyway.
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Okay, yeah, that would be a good start to Reddit.
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When you get into it more, go to our Wall Street Bets.
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It gets dark quickly.
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We'll probably talk about that too.
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So yeah, so there's these users
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and there's no contracts, like you were saying.
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There's no contracts, the users are anonymous,
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but there are little things that do help.
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So for example,
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if you've posted a really good investment idea in the past,
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that exists on Reddit as well.
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And it might have lots of upvotes.
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And that's also kind of like giving credibility
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to your next thing.
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And then they are also putting up screenshots,
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like here's the trades I've made and here's a screenshot.
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Now you could fake the screenshot,
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but still it seems like if you've got a lot of karma
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and you've had a good performance on the community,
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it somehow becomes credible enough
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for other people to be like, you know what?
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He actually probably did put a million dollars into this.
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And you know what, I can follow that trade easily.
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And there's a bunch of people like that.
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So you're kind of integrating all that information
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together yourself to see like, huh,
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there's something happening here.
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And then you jump onto this little boat of like behavior,
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like we should buy the stock or sell the stock.
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And then another person jumps on,
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another person jumps on.
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And all of a sudden you have just a huge number of people
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behaving in the same direction.
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It's like flock of whatever birds.
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Exactly.
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What was strange with this one,
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it wasn't just let's all buy Tesla.
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We love Elon, we love Tesla, let's all buy Tesla.
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Because that we've heard before, right?
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Everybody likes Tesla.
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Well, now they do.
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So what they did with this in this case,
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they're buying a stock that was bad.
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They're buying it because it was bad.
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And that's really weird because that's a little bit
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too galaxy brain for a decentralized community.
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How did they come up with it?
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How did they know that was the right one?
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And the reason they liked it
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is because it had really, really high short interest.
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It had been shorted more than its own float, I believe.
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And so they figured out that if they all bought
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this bad stock, they could short squeeze some hedge funds.
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And those hedge funds would have to capitulate
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and buy the stock at really, really high prices.
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And we should say that shorted means that
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these are a bunch of people, when you short a stock,
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you're betting on the, you're predicting
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that the stock's going to go down
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and then you will make money if it does.
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And then what's a short squeeze?
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It's really that if you are a hedge fund
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and you take a big short position in a company,
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there's a certain level at which
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you can't sustain holding that position.
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There's no limit to how high a stock can go,
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but there is a limit to how low it can go, right?
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So if you short something, you have infinite loss potential.
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And if the stock doubles overnight, like GameStop did,
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you're putting a lot of stress on that hedge fund.
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And that hedge fund manager might have to say,
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you know what, I have to get out of the trade.
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And the only way to get out is to buy the bad stock
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that they don't want, like they believe will go down.
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So it's an interesting situation,
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particularly because it's not zero sum.
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If you say, let's all get together
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and make a bubble in watermelons,
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you buy a bunch of watermelons,
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the price goes up, it comes down again,
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it's a zero sum game.
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If someone's already shorted a stock
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and you can make them short squeeze,
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it's actually a positive sum game.
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So yes, some Redditors will make a lot of money,
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some will lose a lot,
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but actually the whole group will make money.
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And that's really why it was such a clever thing
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for them to do.
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And coupled to the fact that shorting,
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I mean, maybe you can push back,
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but to me always from an outsider's perspective,
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seemed, I hope I'm not using too strong of a word,
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but it seemed almost unethical.
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Maybe not unethical, maybe it's just a asshole thing to do.
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Okay, I'm speaking not from an economics
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or financial perspective,
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I'm speaking from just somebody who loves,
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I'm a fan of a lot of people,
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I love celebrating the success of a lot of people.
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And this is like the stock market equivalent of like haters.
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I know that's not what it is.
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I know that there's efficient,
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you wanna have an economy efficient mechanism
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for punishing sort of overhyped, overvalued things.
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That's what shorthand guess is designed for.
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But it just always felt like these people are just,
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because they're not just betting on the loss of the company.
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It feels like they're also using their leverage and power
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to manipulate media or just to write articles
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or just to hate on you on social media.
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Then you get to see that with Elon Musk and so on.
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So this is like the man,
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so people like hedge funds that were shorting
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are like the sort of embodiment of the evil
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or just the bad guy, the overpowerful
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that's misusing their power.
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And here's the crowd,
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the people that are standing up and rising up.
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So it's not just that they were able to collaborate
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on Wall Street bets to sort of effectively
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make money for themselves.
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It's also that this is like a symbol
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of the people getting together
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and fighting the centralized elites, the powerful.
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And that, I don't know what your thoughts are
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about that in general.
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At this stage, it feels like that's really exciting
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that people have power,
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just like regular people have power.
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At the same time, it's scary a little bit
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because just studying history,
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people could be manipulated by charismatic leaders.
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And so just like Elon right now is manipulating,
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encouraging people to buy Dogecoin or whatever,
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there can be good charismatic leaders
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and there can be bad charismatic leaders.
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And so it's nerve wracking.
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It's a little bit scary how much power
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a subreddit can have to destroy somebody
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because right now we're celebrating
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they might be attacking or destroying somebody
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that everybody doesn't like,
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but what if they attack somebody
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that is actually good for this world?
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So that, and that's kind of the awesomeness
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and the price of freedom.
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It's like it could destroy the world
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or it can save the world.
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But at this stage, it feels like, I don't know,
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overall, when you sit back,
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do you think this was just a positive wave
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of emergent behavior?
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Is there something negative about what happened?
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Well, yeah, the cool thing is they weren't doing anything,
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the Reddit people weren't doing anything exotic.
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It was a creative trade, but it wasn't exotic.
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It wasn't, it was just buying the stock.
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Okay, maybe they bought some options too,
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but it was the hedge fund that was doing the exotic thing.
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So I liked that.
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It was, it's hard to say, well, we've got together
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and we've pulled all our money together
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and now there's a company out there that's worth more.
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What's wrong with that?
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Yeah. Right?
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But it doesn't talk about the motivations, which is,
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and then we destroyed some hedge funds in the process.
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Is there something to be said about the humor
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and the, I don't know, the edginess,
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sometimes viciousness of that subreddit?
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I haven't looked at it too much,
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but it feels like people can be quite aggressive on there.
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So is there, what is that?
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Is that what Freedom looks like?
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I think it does, yeah.
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You definitely need to let people,
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one of the things that people have compared it to
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is the Occupy Wall Street, which is, let's say,
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some very sincere liberals, like 23 years old, whatever,
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and they go out with signs
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and they have some kind of case to make.
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But this isn't sincere, really.
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It's like a little bit more nihilistic,
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a little bit more YOLO, and therefore a little bit
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more scary because who's scared of the Occupy Wall Street
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people with the signs?
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Nobody.
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But these hedge funds really are scared.
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I was scared of the Wall Street bats people.
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I'm still scared of them.
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Yeah, the anonymity is a bit terrifying and exciting.
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Yeah.
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I mean, yeah, I don't know what to do with this.
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I've been following events in Russia, for example.
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It's like there's a struggle between centralized power
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and the distributed.
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I mean, that's the struggle of the history
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of human civilization, right?
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But this on the internet, just that you can multiply people.
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Like some of them don't have to be real.
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Like you can probably create bots.
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Like it starts getting me, me as a programmer,
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I start to think like, hmm, me as one person,
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how much chaos can I create by writing some bots?
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Yeah.
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And I'm sure I'm not the only one thinking that.
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There's, I'm sure there's hundreds, thousands
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of good developers out there listening to this,
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thinking the same thing.
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And then as that develops further and further
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in the next like decade or two,
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what impact does that have on financial markets,
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on just destruction of reputations of just,
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or politics, the bickering of left and right
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political discourse, the dynamics of that
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being manipulated by, you know,
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people talk about like Russian bots or whatever.
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We're probably in a very early stage of that, right?
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Yeah, exactly.
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And this is a good example.
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So do you have a sense that most of WallStreetBets folks
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are actually individual people, right?
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That's the feeling I have is they're just individual,
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maybe young investors, just doing a little bit
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of an investment, but just on a large scale.
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Yeah, exactly.
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The reason I found out, I've known about WallStreetBets
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for a while, but the reason I found out about GameStop
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was this, just I met somebody at a party
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who told me about it and he was like 21 years old
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and he's like, it's gonna go up 100% in the next one day.
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That we're talking about in last year?
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This was probably, no, this was, yeah, a few days ago.
link |
00:15:29.220
Yeah, it was like maybe two weeks ago or something.
link |
00:15:34.260
So it was already high GameStop,
link |
00:15:37.420
but it was just strange to me that there was someone
link |
00:15:39.300
telling me at a party how to trade stocks
link |
00:15:42.740
who was like 21 years old.
link |
00:15:44.340
And I started to, yeah, I started to look into it.
link |
00:15:49.100
And yeah, and he did make, he made it, yeah,
link |
00:15:52.100
he made 140% in one day, he was right.
link |
00:15:55.500
And now he's supercharged, he's a little bit wealthier
link |
00:15:58.980
and now he's gonna wait for the next thing.
link |
00:16:01.180
And this decentralized entity
link |
00:16:03.100
is just gonna get bigger and bigger.
link |
00:16:04.580
And they're gonna together search for the next thing.
link |
00:16:06.580
So there's thousands of folks like him
link |
00:16:08.820
and they're going to probably search
link |
00:16:10.020
for the next thing to attack.
link |
00:16:11.580
People that have power in this world that sit there
link |
00:16:14.460
with power right now in government and in finance
link |
00:16:18.180
and any kind of position
link |
00:16:20.260
are probably a little bit scared right now.
link |
00:16:22.940
And honestly, that's probably a little bit good.
link |
00:16:26.260
It's dangerous, but it's good.
link |
00:16:28.100
Yeah, it certainly makes you think twice about shorting.
link |
00:16:31.420
It certainly makes you think twice
link |
00:16:32.740
about putting a lot of money into a short.
link |
00:16:35.020
Like these funds put a lot into one or two names.
link |
00:16:38.620
And so it was very, very badly risk managed.
link |
00:16:41.700
Do you think shorting is, can you speak at a high level
link |
00:16:46.020
just for your own as a person, is it good for the world?
link |
00:16:50.060
Is it good for markets?
link |
00:16:52.140
I do think that the two kinds of shorting,
link |
00:16:55.180
evil shorting and chill shorting.
link |
00:17:00.860
Evil shorting is what Melvin Capital was doing.
link |
00:17:04.500
And it's like, you put a huge position down,
link |
00:17:08.780
you get all your buddies to also short it
link |
00:17:10.780
and you start making press
link |
00:17:12.420
and trying to bring this company down.
link |
00:17:16.660
And I don't think in some cases,
link |
00:17:20.420
you go out after like fraudulent companies say,
link |
00:17:22.380
this company is a fraud.
link |
00:17:24.100
Maybe that's okay.
link |
00:17:24.940
Like some, but they weren't even saying,
link |
00:17:27.020
they're just saying it's a bad company
link |
00:17:29.140
and we're going to bring it to the ground,
link |
00:17:30.940
bring it to its knees.
link |
00:17:32.020
So a quant fund like Numerai,
link |
00:17:37.100
we always have lots of positions
link |
00:17:39.100
and we never have a position
link |
00:17:40.260
that's like more than 1% of our fund.
link |
00:17:43.420
So we actually have right now, 250 shorts.
link |
00:17:48.260
I don't know any of them except for one
link |
00:17:52.060
because it was one of the meme stocks.
link |
00:17:53.940
But we shorting them not to make them go,
link |
00:17:58.940
we don't even want them to go down necessarily.
link |
00:18:01.460
That doesn't sound a bit strange that I say that,
link |
00:18:03.180
but we just want them to not go up as much as our longs.
link |
00:18:09.420
So by shorting a little bit,
link |
00:18:13.420
we can actually go long more
link |
00:18:15.060
in the things we do believe in.
link |
00:18:16.780
So when we were going long in Tesla,
link |
00:18:19.500
we could do it with more money than we had
link |
00:18:22.020
because we would borrow from banks
link |
00:18:24.860
who would lend us money to go down.
link |
00:18:27.380
Who would lend us money because we had longs and shorts,
link |
00:18:32.220
because we didn't have market exposure,
link |
00:18:34.660
we didn't have market risk.
link |
00:18:35.780
And so I think that's a good thing
link |
00:18:37.380
because that means we can short the oil companies
link |
00:18:41.060
and go long Tesla and make the future come forward faster.
link |
00:18:44.180
And I do think that's not a bad thing.
link |
00:18:47.180
So we've talked about this incredible distributed system
link |
00:18:51.060
created by Wall Street Bets.
link |
00:18:52.580
And then there's a platform which is Robinhood,
link |
00:18:56.940
which allows investors to efficiently as far,
link |
00:18:59.340
you can correct me if I'm wrong,
link |
00:19:00.500
but there's those and there's others in this new MRI
link |
00:19:04.220
that allow you to make it accessible for people to invest.
link |
00:19:09.580
But that said, Robinhood was in a centralized way
link |
00:19:15.700
applied its power to restrict trading
link |
00:19:17.740
on the stocks that we're referring to.
link |
00:19:19.900
Do you have a thoughts on actually
link |
00:19:21.860
like the things that happened?
link |
00:19:23.940
I don't know how much you were paying attention
link |
00:19:26.580
to sort of the shadiness around the whole thing.
link |
00:19:30.420
Do you think it was forced to do it?
link |
00:19:32.540
Or was there something shady going on?
link |
00:19:34.420
What are your thoughts in general?
link |
00:19:36.060
Well, I think I wanna see the alternate history.
link |
00:19:39.860
Like I wanna see the counterfactual history
link |
00:19:43.020
of them not doing that.
link |
00:19:44.740
How bad would it have gotten for hedge funds?
link |
00:19:47.980
How much more damage could have been done
link |
00:19:50.220
if the momentum of these short squeezes could continue?
link |
00:19:53.400
What happens when there are short squeezes,
link |
00:19:57.240
even if they're in a few stocks,
link |
00:20:00.520
they affect kind of all the other shorts too.
link |
00:20:02.920
And suddenly brokers are saying things like,
link |
00:20:05.680
you need to put up more collateral.
link |
00:20:07.400
So we had a short, it wasn't GameStop luckily,
link |
00:20:12.080
it was Blackberry and it went up like 100% in a day.
link |
00:20:15.440
It was one of these meme stocks, super bad company.
link |
00:20:17.640
The AIs don't like it, okay?
link |
00:20:19.720
The AIs think it's going down.
link |
00:20:21.240
What's a meme stock?
link |
00:20:22.400
A meme stock is kind of a new term for these stocks
link |
00:20:26.360
that catch memetic momentum on Reddit.
link |
00:20:32.080
And so the meme stocks were GameStop, the biggest one,
link |
00:20:36.080
GameStonk, as Elon calls it, AMC.
link |
00:20:39.440
And Blackberry was one, Nokia was one.
link |
00:20:44.880
So these are high short interest stocks as well.
link |
00:20:47.960
So these are targeted stocks.
link |
00:20:50.040
Some people say, oh, isn't it adorable
link |
00:20:53.360
that these people are investing money
link |
00:20:56.280
in these companies that are nostalgic?
link |
00:20:59.440
It's like, you go into the AMC movie theater,
link |
00:21:01.640
it's like nostalgic.
link |
00:21:02.480
It's like, no, it's not why they're doing it.
link |
00:21:05.040
It's that they had a lot of short interest.
link |
00:21:07.000
That was the main thing.
link |
00:21:08.320
And so there were high chance of short squeeze.
link |
00:21:11.520
In saying, I would love to see an alternate history,
link |
00:21:14.040
do you have a sense that that,
link |
00:21:17.080
what is your prediction of what that history would look like?
link |
00:21:19.840
Well, you wouldn't have needed very many more days
link |
00:21:23.040
of that kind of chaos to hurt hedge funds.
link |
00:21:28.440
I think it's underrated how damaging it could have been.
link |
00:21:32.840
Because when your shorts go up,
link |
00:21:38.440
your collateral requirements for them go up.
link |
00:21:40.520
It's similar to Robinhood.
link |
00:21:41.880
Like we have a prime broker that says, said to us,
link |
00:21:46.080
you need to put up like $40 per $100 of short exposure.
link |
00:21:51.480
And then the next day they said,
link |
00:21:52.560
actually you have to put up all of it, 100%.
link |
00:21:56.480
And we were like, what?
link |
00:21:58.960
But if that happens to all the short,
link |
00:22:02.440
all the commonly held hedge fund shorts,
link |
00:22:05.560
because they're all kind of holding the same things.
link |
00:22:08.320
If that happens, not only do you have to cover the short,
link |
00:22:13.320
which means you're buying the bad companies,
link |
00:22:16.160
you need to sell your good companies
link |
00:22:18.720
in order to cover the short.
link |
00:22:20.880
So suddenly like all the good companies,
link |
00:22:23.640
all the ones that the hedge funds like are coming down
link |
00:22:26.200
and all the ones that the hedge funds hate are going up
link |
00:22:29.920
in a cascading way.
link |
00:22:33.920
So I believe that if you could have had a few more days
link |
00:22:37.120
of GameStop doubling, AMC doubling,
link |
00:22:40.840
you would have had more and more hedge fund deleveraging.
link |
00:22:45.480
But so hedge funds, I mean, they get a lot of shit,
link |
00:22:48.360
but they, do you have a sense
link |
00:22:51.320
that they do some good for the world?
link |
00:22:53.480
I mean, ultimately, so, okay.
link |
00:22:55.320
First of all, Wall Street bets itself
link |
00:22:57.040
is a kind of distributed hedge fund.
link |
00:22:59.320
Numeri is a kind of hedge fund.
link |
00:23:01.520
So I got, hedge fund is a very broad category.
link |
00:23:04.000
I mean, like if some of those were destroyed,
link |
00:23:07.200
would that be good for the world?
link |
00:23:08.880
Or would there be coupled
link |
00:23:11.960
with the destroying the evil shorting,
link |
00:23:15.160
would there be just a lot of pain
link |
00:23:16.640
in terms of investment in good companies?
link |
00:23:18.960
Yeah, a thing I like to tell people
link |
00:23:21.360
if they hate hedge funds is,
link |
00:23:23.680
I don't think you want to rerun American economic history
link |
00:23:27.960
without hedge funds.
link |
00:23:29.680
So on mass they're, yeah, they're good.
link |
00:23:34.000
Yeah, you really wouldn't want to.
link |
00:23:36.040
Because hedge funds are kind of like picking up,
link |
00:23:38.640
they're making liquidity, right, in stocks.
link |
00:23:41.200
And so if you love venture capitalists,
link |
00:23:45.520
they're investing in new technology, it's so good.
link |
00:23:48.320
You have to also kind of like hedge funds
link |
00:23:50.560
because they're the reason venture capitalists exist
link |
00:23:54.040
because their companies can have a liquidity event
link |
00:23:56.520
when they go to the public markets.
link |
00:23:58.960
So it's kind of essential that we have them.
link |
00:24:01.960
There are many different kinds of them.
link |
00:24:04.440
I believe we could maybe get away
link |
00:24:06.240
with only having an AI hedge fund.
link |
00:24:11.560
But we don't necessarily need
link |
00:24:13.120
these evil billions type hedge funds
link |
00:24:15.280
that make the media and try to kill companies.
link |
00:24:18.600
But we definitely need hedge funds.
link |
00:24:20.160
Maybe from your perspective,
link |
00:24:21.760
because you run such an organization
link |
00:24:27.360
and Vlad, the CEO of Robinhood,
link |
00:24:30.760
sort of had to make decisions really quickly,
link |
00:24:32.720
probably had to wake up
link |
00:24:33.680
in the middle of the night kind of thing.
link |
00:24:36.920
And he also had a conversation with Elon Musk on Clubhouse,
link |
00:24:40.680
which I just signed up for.
link |
00:24:42.360
It was a fascinating,
link |
00:24:43.560
one of the great journalistic performances of our time
link |
00:24:47.480
with Elon Musk.
link |
00:24:49.080
Pull a surprise for Elon.
link |
00:24:51.080
How hilarious would it be if he gets a pull a surprise?
link |
00:24:55.880
And then his Wikipedia would be like journalist
link |
00:24:58.240
and part time entrepreneur.
link |
00:25:00.360
Business magnate.
link |
00:25:01.200
Business magnate.
link |
00:25:02.840
As you know, I don't know if you can comment
link |
00:25:05.520
on any aspects of that,
link |
00:25:06.720
but like, if you were Vlad,
link |
00:25:08.600
how would you do things differently?
link |
00:25:10.080
What are your thoughts about his interaction with Elon?
link |
00:25:13.320
How he should have played it differently?
link |
00:25:15.640
Like, I guess there's a lot of aspects to this interaction.
link |
00:25:19.400
One is about transparency.
link |
00:25:20.920
Like how much do you want to tell people
link |
00:25:23.240
about really what went down?
link |
00:25:24.880
There's NDAs potentially involved.
link |
00:25:27.320
How much in private do you want to push back
link |
00:25:32.720
and say, no, fuck you, to centralize power?
link |
00:25:36.240
Whatever the phone calls you're getting,
link |
00:25:37.560
which I'm sure he was getting some kind of phone calls
link |
00:25:40.200
that might not be contractual.
link |
00:25:42.080
Like it's not contracts that are forcing him,
link |
00:25:44.160
but he was being, what do you call it?
link |
00:25:47.400
Like pressured to behave in certain kinds of ways
link |
00:25:49.960
from all kinds of directions.
link |
00:25:51.560
Like what do you take from this whole situation?
link |
00:25:55.760
I was very excited to see Vlad's response.
link |
00:25:58.320
I mean, it's pretty cool to have him talk to Elon.
link |
00:26:00.920
And one of the things that like struck me
link |
00:26:02.840
in the first like few seconds of Vlad speaking was like,
link |
00:26:06.320
I was like, is Vlad like a boomer?
link |
00:26:10.920
Like, but hear me out.
link |
00:26:13.120
Like he seemed like a 55 year old man
link |
00:26:16.200
talking to a 20 year old.
link |
00:26:18.080
Elon was like the 20 year old.
link |
00:26:19.920
And he's like the 55 year old man.
link |
00:26:21.920
You can see why Citadel are NMR buddies, right?
link |
00:26:25.280
Like you can, you can see why.
link |
00:26:27.800
It's like, this is a nice, it's not a bad thing.
link |
00:26:30.200
It's like, he's got a respectable professional attitude.
link |
00:26:35.400
Well, he also tried to do like a jokey thing.
link |
00:26:38.120
Like, no, we're not being ageist here.
link |
00:26:41.360
Boomer, but like a 60 year old CEO of Bank of America
link |
00:26:46.880
would try to make a joke for the kids.
link |
00:26:48.400
That's what Vlad's like.
link |
00:26:49.840
Yeah, I was like, what is this?
link |
00:26:51.760
This guy's like, what is he, 30?
link |
00:26:53.680
Yeah.
link |
00:26:55.040
And I'm like, this is weird.
link |
00:26:56.840
Yeah.
link |
00:26:58.040
But I think, and maybe that's also what I like
link |
00:27:00.480
about Elon's kind of influence on American business
link |
00:27:03.520
is like, he's super like anti the professional.
link |
00:27:07.280
Like why say, you know, a hundred words about nothing?
link |
00:27:13.120
And so I liked how he was cutting in and saying,
link |
00:27:15.320
Vlad, what do you mean?
link |
00:27:16.160
Spill the beans, bro.
link |
00:27:17.440
Yeah, so you don't have to be courteous.
link |
00:27:19.520
It's like the first principles thinking.
link |
00:27:21.040
It's like, what the hell happened?
link |
00:27:23.200
Yes.
link |
00:27:24.040
Let's just talk like normal people.
link |
00:27:26.600
The problem of course is, you know, for Elon,
link |
00:27:31.600
it's cost them, what is it?
link |
00:27:33.320
Tens of millions of dollars is tweeting like that.
link |
00:27:36.520
But perhaps it's a worthy price to pay
link |
00:27:39.680
because ultimately there's something magical
link |
00:27:42.160
about just being real and honest
link |
00:27:45.840
and just going off the cuff and making the mistakes
link |
00:27:48.320
and paying for them, but just being real.
link |
00:27:50.800
And then moments like this,
link |
00:27:52.880
that was an opportunity for Vlad to be that.
link |
00:27:55.080
And it felt like he wasn't.
link |
00:27:57.400
Do you think we'll ever find out what really went down
link |
00:28:02.600
if there was something shady underneath it all?
link |
00:28:05.200
Yeah, I mean, it would be sad if nothing shady happened,
link |
00:28:09.800
but his presence made it shady.
link |
00:28:12.120
Sometimes I feel like that would mark Zuckerberg,
link |
00:28:15.240
the CEO of Facebook.
link |
00:28:18.000
Sometimes I feel like, yeah,
link |
00:28:19.040
there's a lot of shitty things that Facebook is doing,
link |
00:28:22.280
but sometimes I think he makes it look worse
link |
00:28:25.120
by the way he presents himself about those things.
link |
00:28:28.440
Like I honestly think that a large amount of people
link |
00:28:31.400
at Facebook just have a huge unstable chaotic system
link |
00:28:36.800
and they're all, not all, but mass are trying to do good
link |
00:28:40.760
with this chaotic system.
link |
00:28:42.320
But the presentation is like,
link |
00:28:43.760
it sounds like there's a lot of back room conversations
link |
00:28:47.680
that are trying to manipulate people.
link |
00:28:49.640
And there's something about the realness that Elon has
link |
00:28:53.400
that it feels like CEO should have
link |
00:28:55.720
and Vlad had that opportunity.
link |
00:28:57.200
I think Mark Zuckerberg had that too when he was younger.
link |
00:28:59.840
Younger.
link |
00:29:00.680
And somebody said, you gotta be more professional, man.
link |
00:29:02.800
You can't say, you know, lol to an interview.
link |
00:29:06.880
And then suddenly he became like this distant person
link |
00:29:10.720
that was hot.
link |
00:29:11.560
Like you'd rather have him make mistakes,
link |
00:29:13.400
but be honest than be like professional
link |
00:29:16.080
and never make mistakes.
link |
00:29:18.000
Yeah, one of the difficult hires I think
link |
00:29:22.000
is like marketing people or like PR people
link |
00:29:25.680
is you have to hire people that get the fact
link |
00:29:28.320
that you can say lol on an interview.
link |
00:29:31.000
Or, you know, take risks as opposed to what the PR,
link |
00:29:37.200
I've talked to quite a few big CEOs
link |
00:29:39.720
and the people around them are trying to constantly
link |
00:29:44.720
minimize risk of like, what if he says the wrong thing?
link |
00:29:48.000
What if she says the wrong thing?
link |
00:29:49.480
It's like, what, be careful.
link |
00:29:51.360
It's constantly like, ooh, like, I don't know.
link |
00:29:53.720
And there's this nervous energy that builds up over time
link |
00:29:56.560
with larger and larger teams where the whole thing,
link |
00:29:59.720
like I visited YouTube, for example.
link |
00:30:01.520
Everybody I talked at YouTube, incredible engineering
link |
00:30:05.080
and incredible system, but everybody's scared.
link |
00:30:08.520
Like, let's be honest about this like madness
link |
00:30:13.080
that we have going on of huge amounts of video
link |
00:30:15.840
that we can't possibly ever handle.
link |
00:30:17.640
There's a bunch of hate on YouTube.
link |
00:30:19.680
There's this chaos of comments,
link |
00:30:21.480
bunch of conspiracy theories, some of which might be true.
link |
00:30:24.280
And then just like this mess that we're dealing with
link |
00:30:27.360
and it's exciting, it's beautiful.
link |
00:30:30.160
It's a place where like democratizes education,
link |
00:30:32.840
all that kind of stuff.
link |
00:30:34.200
And instead they're all like sitting in like,
link |
00:30:36.920
trying to be very polite and saying like,
link |
00:30:38.720
well, we just want to improve the health of our platforms.
link |
00:30:41.640
Like, it's like this discussion like,
link |
00:30:44.720
all right, man, let's just be real.
link |
00:30:46.040
Let's both advertise how amazing this fricking thing is,
link |
00:30:50.480
but also to say like, we don't know what we're doing.
link |
00:30:53.200
We have all these Nazis posting videos on YouTube.
link |
00:30:56.040
We don't know how to like handle it.
link |
00:30:58.040
And just being real like that,
link |
00:31:00.000
because I suppose that's just a skill.
link |
00:31:02.240
Maybe it can't be taught, but over time,
link |
00:31:05.080
the whatever the dynamics of the company is,
link |
00:31:06.960
it does seem like Zuckerberg and others get worn down.
link |
00:31:09.840
They just get tired.
link |
00:31:10.960
Yeah.
link |
00:31:11.920
They get tired of.
link |
00:31:12.760
Not being real.
link |
00:31:13.720
Of not being real, which is sad.
link |
00:31:16.360
So let's talk about Numerai,
link |
00:31:17.720
which is an incredible company system idea, I think,
link |
00:31:24.680
but good place to start.
link |
00:31:26.520
What is Numerai and how does it work?
link |
00:31:30.600
So Numerai is the first hedge fund
link |
00:31:32.960
that gives away all of its data.
link |
00:31:35.160
So this is like probably the last thing
link |
00:31:37.640
a hedge fund would do, right?
link |
00:31:39.160
Why would we give away a data?
link |
00:31:40.280
It's like giving away your edge.
link |
00:31:42.960
But the reason we do it is because we're looking for people
link |
00:31:46.840
to model our data.
link |
00:31:49.080
And the way we do it is by obfuscating the data.
link |
00:31:52.840
So when you look at Numerai's data
link |
00:31:55.360
that you can download for free,
link |
00:31:57.520
it just looks like a million rows
link |
00:32:00.440
of numbers between zero and one.
link |
00:32:02.920
And you have no idea what the columns mean,
link |
00:32:05.280
but you do know that if you're good at machine learning
link |
00:32:09.120
or have done regressions before,
link |
00:32:11.520
you know that I can still find patterns in this data,
link |
00:32:14.640
even though I don't know what the features mean.
link |
00:32:17.560
And the data itself is a time series data.
link |
00:32:20.480
And even though it's obfuscated, anonymized,
link |
00:32:24.480
what is the source data like approximately?
link |
00:32:26.920
What are we talking about?
link |
00:32:27.960
So we are buying data from lots of different data vendors
link |
00:32:32.360
and they would also never want us to share that data.
link |
00:32:36.600
So we have strict contracts with them.
link |
00:32:38.560
So we only can,
link |
00:32:41.200
but that's the kind of data you could never buy yourself
link |
00:32:43.480
unless you had maybe a million dollars a year
link |
00:32:46.760
of budget to buy data.
link |
00:32:48.760
So what's happened with the hedge fund industry
link |
00:32:50.600
is you have a lot of talented people
link |
00:32:54.600
who used to be able to trade and still can trade,
link |
00:32:59.640
but now they have such a data disadvantage,
link |
00:33:02.200
it would never make sense for them to trade themselves.
link |
00:33:07.120
But Numerai, by giving away this obfuscated data,
link |
00:33:09.640
we can give them a really, really high quality data set
link |
00:33:12.240
that would otherwise be very expensive.
link |
00:33:14.800
And they can use whatever new machine learning technique
link |
00:33:18.680
they want to find patterns in that data
link |
00:33:22.040
that we can use in our hedge fund.
link |
00:33:24.000
And so how much variety is there in underlying data?
link |
00:33:27.080
We're talking about,
link |
00:33:29.560
I apologize if I'm using the wrong terms,
link |
00:33:31.080
but one is just like the stock price.
link |
00:33:34.360
The other, there's like options and all that kind of stuff,
link |
00:33:36.840
like the, what are they called, order books or whatever.
link |
00:33:41.520
Is there maybe other totally unrelated
link |
00:33:45.320
directly to the stock market data,
link |
00:33:47.120
like natural language as well, all that kind of stuff?
link |
00:33:51.320
Yeah, we were really focused on stock data
link |
00:33:55.120
that's specific to stocks.
link |
00:33:56.560
So things like you can have like a,
link |
00:33:59.840
every stock has like a PE ratio.
link |
00:34:01.880
For some stocks, it's not as meaningful,
link |
00:34:03.800
but every stock has that.
link |
00:34:05.560
Every stock has one year momentum,
link |
00:34:07.560
how much they went up in the last year,
link |
00:34:10.680
but those are very common factors.
link |
00:34:12.520
But we try to get lots and lots of those factors
link |
00:34:15.400
that we have for many, many years,
link |
00:34:17.040
like 15, 20 years history.
link |
00:34:21.520
And then the setup of the problem is commonly in quant
link |
00:34:25.680
called like cross sectional global equity.
link |
00:34:28.120
You're not really trying to say,
link |
00:34:29.720
I believe this stock will go up.
link |
00:34:31.920
You're trying to say the relative position of this stock
link |
00:34:36.240
in feature space makes it not a bad buy in a portfolio.
link |
00:34:41.720
So it captures some period of time
link |
00:34:44.480
and you're trying to find the patterns,
link |
00:34:46.040
the dynamics captured by the data of that period of time
link |
00:34:49.920
in order to make short term predictions
link |
00:34:51.760
about what's going to happen.
link |
00:34:53.160
Yeah, so our predictions are also not that short.
link |
00:34:55.720
We're not really caring about things like order books
link |
00:34:58.760
and tech data, not high frequency at all.
link |
00:35:02.360
We're actually holding things for quite a bit longer.
link |
00:35:05.080
So our prediction time horizon is about one month.
link |
00:35:07.800
We end up holding stocks
link |
00:35:08.840
for maybe like three or four months.
link |
00:35:10.760
So I kind of believe that's a little bit more
link |
00:35:12.440
like investing than kind of plumbing,
link |
00:35:17.840
like to go long a stock that's mispriced on one exchange
link |
00:35:21.840
and short on another exchange, that's just arbitrage.
link |
00:35:26.120
But what we're trying to do is really know something more
link |
00:35:30.000
about the longer term future of the stock.
link |
00:35:31.920
Yeah, so from the patterns,
link |
00:35:33.320
from these like periods of time series data,
link |
00:35:37.000
you're trying to understand something fundamental
link |
00:35:39.480
about the stock, not like about deep value,
link |
00:35:43.280
about like it's big in the context of the market,
link |
00:35:46.360
is it underpriced, overpriced, all that kind of stuff.
link |
00:35:48.880
So like, this is about investing.
link |
00:35:50.800
It's not about like, just like you said,
link |
00:35:52.840
high frequency trading,
link |
00:35:54.640
which I think is a fascinating open question
link |
00:35:57.040
from a machine learning perspective,
link |
00:35:58.480
but just to like sort of build on that.
link |
00:36:00.880
So you've anonymized the data
link |
00:36:02.800
and now you're giving away the data.
link |
00:36:05.240
And then now anyone can try to build algorithms
link |
00:36:12.000
that make investing decisions on top of that data
link |
00:36:14.760
or predictions on the top of that data.
link |
00:36:16.440
Exactly.
link |
00:36:17.280
And so that's, what does that look like?
link |
00:36:21.400
What's the goal of that?
link |
00:36:22.240
What are the underlying principles of that?
link |
00:36:24.440
So the first thing is,
link |
00:36:26.320
we could obviously model that data in house, right?
link |
00:36:29.080
We can make an XGBoost model on the data
link |
00:36:33.320
and that would be quite good too.
link |
00:36:36.200
But what we're trying to do is by opening it up
link |
00:36:40.240
and letting anybody participate,
link |
00:36:43.040
we can do quite a lot better than if we modeled it ourselves
link |
00:36:47.560
and a lot better on the stock market
link |
00:36:50.120
doesn't need to be very much.
link |
00:36:52.120
Like it really matters the difference
link |
00:36:54.000
between if you can make 10 and 12%
link |
00:36:56.520
in an equity market neutral hedge fund
link |
00:36:58.560
because usually you're charging 2% fees.
link |
00:37:02.800
So if you can do 2% better,
link |
00:37:05.080
that's like all your fees, it's worth it.
link |
00:37:07.600
So we're trying to make sure
link |
00:37:09.440
that we always have the best possible model
link |
00:37:11.360
as new machine learning libraries come out,
link |
00:37:13.320
new techniques come out,
link |
00:37:14.960
they get automatically synthesized.
link |
00:37:16.760
Like if there's a great paper on supervised learning,
link |
00:37:19.840
someone on Numerai will figure out
link |
00:37:21.840
how to use it on Numerai's data.
link |
00:37:23.480
And is there an ensemble of models going on
link |
00:37:28.960
or is it more towards kind of like one or two or three
link |
00:37:33.440
like best performing models?
link |
00:37:35.360
So the way we decide on how to weight
link |
00:37:37.760
all of the predictions together
link |
00:37:40.360
is by how much the users are staking on them.
link |
00:37:44.720
How much of the cryptocurrency
link |
00:37:46.280
that they're putting behind their models.
link |
00:37:48.280
So they're saying, I believe in my model.
link |
00:37:51.280
You can trust me because I'm gonna put skin in the game.
link |
00:37:55.320
And so we can take the stake weighted predictions
link |
00:37:57.960
from all our users, add those together,
link |
00:38:01.040
average those together,
link |
00:38:02.240
and that's a much better model than any one model
link |
00:38:05.920
in the sum because ensembling a lot of models together
link |
00:38:08.800
is kind of the key thing you need to do in investing too.
link |
00:38:12.400
Yeah, so you're putting,
link |
00:38:14.520
so there's a kind of duality from the user,
link |
00:38:16.800
from the perspective of a machine learning engineer
link |
00:38:19.360
where it's both a competition, just a really interesting,
link |
00:38:22.480
difficult machine learning problem,
link |
00:38:24.720
and it's a way to invest algorithmically.
link |
00:38:29.840
So like, but the way to invest algorithmically
link |
00:38:33.800
also is a way to put skin in the game
link |
00:38:37.360
that communicates to you that the quality of the algorithm
link |
00:38:42.840
and also forces you to really be serious
link |
00:38:46.960
about the models that you build.
link |
00:38:49.440
So it's like, everything just works nicely together.
link |
00:38:52.320
Like, I guess one way to say that
link |
00:38:54.640
is the interests are aligned.
link |
00:38:58.000
Okay, so it's just like poker is not fun
link |
00:39:02.320
when it's like for very low stakes.
link |
00:39:04.760
The higher the stakes,
link |
00:39:05.880
the more the dynamics of the system
link |
00:39:07.480
starts playing out correctly.
link |
00:39:10.760
Like as a small side note,
link |
00:39:12.120
is there something you can say about which kind,
link |
00:39:16.480
looking at the big broad view of machine learning today
link |
00:39:19.240
or AI, what kind of algorithms seem to do good
link |
00:39:24.640
in these kinds of competitions at this time?
link |
00:39:27.120
Is there some universal thing you can say,
link |
00:39:29.960
like neural networks suck,
link |
00:39:32.040
recurrent neural networks suck, transformers suck,
link |
00:39:34.480
or they're awesome, like old school,
link |
00:39:37.680
sort of more basic kind of classifiers are better,
link |
00:39:40.360
all that, is there some kind of conclusions
link |
00:39:42.440
so far that you can say?
link |
00:39:44.040
There is definitely something pretty nice about tree models,
link |
00:39:47.640
like XGBoost,
link |
00:39:50.160
and they just seem to work pretty nicely
link |
00:39:53.120
on this type of data.
link |
00:39:54.880
So out of the box,
link |
00:39:56.320
if you're trying to come a hundredth
link |
00:39:59.480
in the competition, in the tournament,
link |
00:40:01.400
maybe you would try to use that.
link |
00:40:04.080
But what's particularly interesting about the problem
link |
00:40:09.240
that not many people understand,
link |
00:40:11.800
if you're familiar with machine learning,
link |
00:40:14.680
this typically will surprise you when you model our data.
link |
00:40:18.400
So one of the things that you look at in finance
link |
00:40:23.920
is you don't wanna be too exposed to any one risk.
link |
00:40:28.240
Like, even if the best sector in the world
link |
00:40:33.840
to invest in over the last 10 years was tech,
link |
00:40:37.960
does not mean you should put all of your money into tech.
link |
00:40:40.760
So if you train a model,
link |
00:40:42.880
it would say, put all your money in tech, it's super good.
link |
00:40:45.680
But what you wanna do is actually be very careful
link |
00:40:49.040
of how much of this exposure you have to certain features.
link |
00:40:53.360
So on Numeri, what a lot of people figure out is,
link |
00:40:58.400
actually, if you train a model on this kind of data,
link |
00:41:02.040
you wanna somehow neutralize or minimize your exposure
link |
00:41:05.400
to these certain features, which is unusual,
link |
00:41:08.160
because if you did train a stoplight
link |
00:41:11.840
or stop street detection on computer vision,
link |
00:41:18.080
your favorite feature, let's say you have an auto encoder
link |
00:41:21.720
and it's figuring out, okay, it's gotta be red
link |
00:41:23.320
and it's gotta be white,
link |
00:41:25.040
that's the last thing you wanna reduce your exposure to.
link |
00:41:30.280
Why would you reduce your exposure
link |
00:41:31.440
to the thing that's helping your model the most?
link |
00:41:34.520
And that's actually this counterintuitive thing
link |
00:41:36.360
you have to do with machine learning on financial data.
link |
00:41:38.600
So reducing your exposure
link |
00:41:41.760
would help you generalize the things that are...
link |
00:41:44.040
So basically, a financial data has a large amount
link |
00:41:48.600
of patterns that appeared in the past
link |
00:41:51.560
and also a large amount of patterns
link |
00:41:53.240
that have not appeared in the past.
link |
00:41:55.040
And so like in that sense,
link |
00:41:56.160
you have to reduce the exposure to red lights,
link |
00:41:59.880
to the color red.
link |
00:42:02.440
That's interesting, but how much of this is art
link |
00:42:05.080
and how much of it is science from your perspective so far
link |
00:42:09.080
in terms of as you start to climb
link |
00:42:11.080
from the 100th position to the 95th in the competition?
link |
00:42:16.000
Yeah, well, if you do make yourself super exposed
link |
00:42:20.360
to one or two features,
link |
00:42:23.200
you can have a lot of volatility
link |
00:42:25.680
when you're playing Numerai.
link |
00:42:26.920
You could maybe very rapidly rise to be high
link |
00:42:31.200
if you were getting lucky.
link |
00:42:33.000
Yes.
link |
00:42:34.240
And that's a bit like the stock market.
link |
00:42:36.120
Sure, take on massive risk exposure,
link |
00:42:38.800
put all your money into one stock
link |
00:42:41.040
and you might make 100%,
link |
00:42:43.640
but it doesn't in the long run work out very well.
link |
00:42:47.680
And so the best users are trying to stay high
link |
00:42:53.520
for as long as possible,
link |
00:42:55.920
not necessarily try to be first for a little bit.
link |
00:43:00.040
So me, a developer, machine learning researcher,
link |
00:43:04.840
how do I, Lex Friedman, participate in this competition
link |
00:43:07.920
and how do others,
link |
00:43:09.400
which I'm sure there'll be a lot of others
link |
00:43:10.840
interested in participating in this competition,
link |
00:43:12.920
what are, let's see, there's like a million questions,
link |
00:43:15.720
but like first one is how do I get started?
link |
00:43:19.640
Well, you can go to numero.ai,
link |
00:43:22.440
sign up, download the data.
link |
00:43:24.600
And on the data is pretty small.
link |
00:43:30.080
In the data pack you download,
link |
00:43:32.000
there's like an example script,
link |
00:43:33.960
Python script that just builds a XGBoost model
link |
00:43:37.840
very quickly from the data.
link |
00:43:40.720
And so in a very short time,
link |
00:43:44.000
you can have an example model.
link |
00:43:46.080
Is that a particular structure?
link |
00:43:47.680
Like what, is this model then submitted somewhere?
link |
00:43:50.680
So there needs to be some kind of structure
link |
00:43:52.520
that communicates with some kind of API.
link |
00:43:54.760
Like how does the whole,
link |
00:43:56.480
how does your model, once you've built,
link |
00:43:58.640
once you create a little baby Frankenstein,
link |
00:44:01.440
how does it then live in the world?
link |
00:44:02.760
Okay, well, we want you to keep your baby Frankenstein
link |
00:44:05.120
at home and take care of it.
link |
00:44:06.880
We don't want it.
link |
00:44:07.920
So you never upload your model to us.
link |
00:44:10.760
You always only giving us predictions.
link |
00:44:14.680
So we never see the code that wrote your model,
link |
00:44:17.160
which is pretty cool,
link |
00:44:18.160
that our whole hedge fund is built from models
link |
00:44:20.560
where we've never, ever seen the code.
link |
00:44:23.720
But it's important for the users because it's their IP,
link |
00:44:27.040
why do they want to give it to us?
link |
00:44:28.000
That's brilliant.
link |
00:44:28.840
So they've got it themselves,
link |
00:44:31.040
but they can basically almost like license
link |
00:44:34.200
the predictions from that model to us.
link |
00:44:36.720
License the predictions, yeah.
link |
00:44:38.680
So. Think about it.
link |
00:44:40.160
What some users do is they set up a compute server
link |
00:44:43.920
and we call it Numeric Compute.
link |
00:44:45.120
It's like a little AWS kind of image
link |
00:44:47.280
and you can automate this process.
link |
00:44:50.160
So we can ping you.
link |
00:44:51.200
We can be like, we need more predictions now.
link |
00:44:53.000
And then you send it to us.
link |
00:44:55.520
Okay, cool.
link |
00:44:56.360
So that's, is that described somewhere,
link |
00:45:00.080
like what the preferred is, the AWS,
link |
00:45:02.160
or whether another cloud platform,
link |
00:45:04.880
is there, I mean, is there sort of specific technical things
link |
00:45:07.680
you want to say that comes to mind
link |
00:45:09.600
that is a good path for getting started?
link |
00:45:12.800
So download the data, maybe play around,
link |
00:45:16.040
see if you can modify the basic algorithm provided
link |
00:45:22.160
in the example.
link |
00:45:25.760
And then you, what, set up a little server on the AWS
link |
00:45:28.600
that then runs this model and takes pings
link |
00:45:31.840
and then makes predictions.
link |
00:45:34.120
And so how does your own money actually come into play
link |
00:45:37.720
doing the stake of a cryptocurrency?
link |
00:45:41.240
Yeah, so you don't have to stake.
link |
00:45:44.120
You can start without staking.
link |
00:45:45.480
And many users might try for months
link |
00:45:49.040
without staking anything at all
link |
00:45:50.560
to see if their model works on the real life data, right?
link |
00:45:54.840
And is not overfit.
link |
00:45:57.080
But then you can get Numeraire many different ways.
link |
00:46:01.960
You can buy it on, you can buy some on Coinbase.
link |
00:46:04.960
You can buy some on Uniswap.
link |
00:46:06.760
You can buy some on Binance.
link |
00:46:09.240
So what did you say this is?
link |
00:46:11.160
How do you pronounce it?
link |
00:46:12.080
So this is the Numeraire cryptocurrency.
link |
00:46:15.040
Yeah, NMR.
link |
00:46:16.440
NMR, you just say NMR?
link |
00:46:19.280
It is technically called Numeraire.
link |
00:46:21.800
Numeraire, I like it.
link |
00:46:23.560
Yeah, but NMR is simple.
link |
00:46:26.280
NMR, Numeraire.
link |
00:46:27.280
Okay, so, and you could buy it basically anywhere.
link |
00:46:31.960
Yeah, so it's a bit strange
link |
00:46:33.080
because sometimes people are like,
link |
00:46:34.400
is this like pay to play?
link |
00:46:36.160
Right.
link |
00:46:37.000
And it's like, yeah, you need to put some money down
link |
00:46:40.800
to show us you believe in your model.
link |
00:46:42.600
But weirdly, we're not selling you the,
link |
00:46:45.160
like you can't buy the cryptocurrency from us.
link |
00:46:48.240
Right.
link |
00:46:49.080
It's like, it's also, we never,
link |
00:46:51.800
if you do badly, we destroy your cryptocurrency.
link |
00:46:57.440
Okay, that's not good, right?
link |
00:46:58.520
You don't want it to be destroyed.
link |
00:47:00.000
But what's good about it is it's also not coming to us.
link |
00:47:03.520
Right.
link |
00:47:04.360
So it's not like we win when you lose or something,
link |
00:47:06.920
like we're the house.
link |
00:47:08.560
Like we're definitely on the same team.
link |
00:47:10.360
Yes.
link |
00:47:11.200
Helping us make a hedge fund that's never been done before.
link |
00:47:14.200
Yeah, so again, interests are aligned.
link |
00:47:15.760
There's no, there's no tension there at all,
link |
00:47:18.360
which is really fascinating.
link |
00:47:19.920
You're giving away everything
link |
00:47:21.000
and then the IP is owned by sort of the code.
link |
00:47:24.400
You never share the code.
link |
00:47:25.680
That's fascinating.
link |
00:47:27.120
So since I have you here and you said a hundred,
link |
00:47:31.000
I didn't ask out of how many, so we'll just,
link |
00:47:34.960
but if I then once you get started
link |
00:47:37.960
and you find this interesting, how do you then win
link |
00:47:43.640
or do well, but also how do you potentially try to win
link |
00:47:47.280
if this is something you want to take on seriously
link |
00:47:49.880
from the machine learning perspective,
link |
00:47:51.200
not from a financial perspective?
link |
00:47:53.320
Yeah, I think that first of all,
link |
00:47:55.760
you would want to talk to the community.
link |
00:47:57.240
People are pretty open.
link |
00:47:58.880
We give out really interesting scripts and ideas
link |
00:48:01.960
for things you might want to try.
link |
00:48:03.600
And, but you're also going to need a lot of compute probably.
link |
00:48:09.520
And so some of the best users are, you know,
link |
00:48:12.400
actually the very first time someone won on Numerai,
link |
00:48:15.400
I would, I wrote them a personal email.
link |
00:48:17.080
It's like, you know, you've won some money.
link |
00:48:18.880
We're so excited to give you $300.
link |
00:48:21.560
And then they said, I spend way more on the compute,
link |
00:48:26.040
but.
link |
00:48:26.880
So this is fundamentally a machine learning problem first,
link |
00:48:29.200
I think is this is one of the exciting things.
link |
00:48:31.640
I don't know if we'll, in how many ways we can approach this,
link |
00:48:34.400
but really this is less about kind of no offense,
link |
00:48:40.200
but like finance people, finance minded people,
link |
00:48:43.320
they're also, I'm sure great people,
link |
00:48:45.400
but it feels like from the community that I've experienced,
link |
00:48:49.640
these are people who see finance
link |
00:48:52.120
as a fascinating problem space, source of data,
link |
00:48:57.520
but ultimately they're machine learning people or AI people,
link |
00:49:01.240
which is a very different kind of flavor of community.
link |
00:49:03.520
And I mean, I should say to that,
link |
00:49:07.560
I'd love to participate in this and I will participate in this
link |
00:49:10.640
and I'd love to hear from other people.
link |
00:49:12.840
If you're listening to this,
link |
00:49:13.720
if you're a machine learning person,
link |
00:49:15.520
you should participate in it and tell me,
link |
00:49:17.640
give me some hints how I can do well at this thing.
link |
00:49:21.320
Cause this boomer, I'm not sure I still got it,
link |
00:49:24.200
but cause some of it is, it's like a Kaggle competitions.
link |
00:49:28.360
Like some of it is certainly set of ideas,
link |
00:49:33.280
like research ideas, like fundamental innovation,
link |
00:49:37.400
but I'm sure some of it is like deeply understanding,
link |
00:49:40.000
getting like an intuition about the data.
link |
00:49:42.680
And then like a lot of it will be like figuring out
link |
00:49:45.760
like what works, like tricks.
link |
00:49:47.760
I mean, you could argue most of deep learning research
link |
00:49:50.040
is just tricks on top of tricks,
link |
00:49:51.520
but there's some of it is just the art
link |
00:49:55.880
of getting to know how to work in a really difficult
link |
00:49:58.800
machine learning problem.
link |
00:50:00.560
And I think what's important,
link |
00:50:02.000
the important difference with something
link |
00:50:03.520
like a Kaggle competition,
link |
00:50:04.720
where they'll set up this kind of toy problem
link |
00:50:08.320
and then there will be an out of sample test,
link |
00:50:10.640
like, Hey, you did well out of sample.
link |
00:50:12.320
And this is like, okay, cool.
link |
00:50:14.920
But what's cool with Numeri is the out of sample
link |
00:50:19.120
is the real life stock market.
link |
00:50:22.080
We don't even know,
link |
00:50:23.400
like we don't know the onset of the problem.
link |
00:50:25.640
We don't, like you'll have to find out live.
link |
00:50:28.320
And so we've had users who've like submitted every week
link |
00:50:31.640
for like four years because it's kind of,
link |
00:50:38.280
we say it's the hardest data science problem
link |
00:50:40.640
on the planet, right?
link |
00:50:41.840
And it sounds maybe sounds like maybe
link |
00:50:44.080
but too much for like a marketing thing,
link |
00:50:45.600
but it's the hardest because it's the stock market.
link |
00:50:48.840
It's like literally there are like billions of dollars
link |
00:50:51.640
at stake and like no one's like letting it be inefficient
link |
00:50:55.480
on purpose.
link |
00:50:56.680
So if you can find something that works at Numeri,
link |
00:50:58.760
you really have something that is like working
link |
00:51:01.760
on the real stock market.
link |
00:51:03.680
Yeah, because there's like humans involved
link |
00:51:05.720
in the stock market.
link |
00:51:06.560
I mean, you could argue there might be harder data sets
link |
00:51:09.920
like maybe predicting the weather,
link |
00:51:11.320
all those kinds of things.
link |
00:51:12.280
But the fundamental statement here is, which I like,
link |
00:51:16.080
I was thinking like,
link |
00:51:16.920
is this really the hardest data science problem?
link |
00:51:19.520
And you start thinking about that,
link |
00:51:21.160
but ultimately it also boils down to a problem
link |
00:51:24.880
where the data is accessible.
link |
00:51:26.720
It's made accessible, made really easy and efficient
link |
00:51:31.320
at like submitting algorithms.
link |
00:51:33.960
So it's not just, you know,
link |
00:51:35.560
it's not about the data being out there, like the weather.
link |
00:51:38.120
It's about making the data super accessible,
link |
00:51:40.480
making the ability of community around it.
link |
00:51:43.040
Like this is what ImageNet did.
link |
00:51:45.200
Exactly.
link |
00:51:46.040
Like it's not just, there's always images.
link |
00:51:49.080
The point is you aggregate them together.
link |
00:51:51.280
You give it a little title.
link |
00:51:52.680
This is a community and that was one of the hardest,
link |
00:51:56.920
right, for a time.
link |
00:51:58.960
And most important data science problems in the world
link |
00:52:03.960
because it was accessible, because it was made sort of,
link |
00:52:08.680
like there was mechanisms by which like standards
link |
00:52:12.320
and mechanisms by which you judge your performance,
link |
00:52:14.040
all those kinds of things.
link |
00:52:14.880
And Numerize actually step up from that.
link |
00:52:17.360
Is there something more you can say about why
link |
00:52:19.680
from your perspective it's the hardest problem in the world?
link |
00:52:24.560
I mean, you said it's connected to the market.
link |
00:52:26.560
So if you could find a pattern in the market,
link |
00:52:29.320
that's a really difficult thing to do
link |
00:52:31.200
because a lot of people are trying to do it.
link |
00:52:33.320
Exactly.
link |
00:52:34.160
But there's also the biggest one is
link |
00:52:37.200
it's non stationary time series.
link |
00:52:40.480
We've tried to regularize the data
link |
00:52:42.680
so you can find patterns by doing certain things
link |
00:52:46.920
to the features and the target.
link |
00:52:48.600
But ultimately you're in a space where you don't,
link |
00:52:51.880
there's no guarantees that the out of sample distributions
link |
00:52:55.720
will conform to any of the training data.
link |
00:52:59.680
And every single era, which we call on the website,
link |
00:53:04.800
like every single era in the data,
link |
00:53:07.040
which is like sort of showing you the order of the time.
link |
00:53:12.640
Even the training data has the same dislocations.
link |
00:53:16.320
And so, yeah, and then there's so many things
link |
00:53:22.360
that you might wanna try.
link |
00:53:25.880
There's unlimited possible number of models, right?
link |
00:53:30.320
And so by having it be open,
link |
00:53:37.520
we can at least search that space.
link |
00:53:40.600
Zooming back out to the philosophical,
link |
00:53:42.440
you said that Numerai is very much like Wall Street Bets.
link |
00:53:46.560
Is there, I think it'd be interesting
link |
00:53:51.120
to dig in why you think so.
link |
00:53:52.480
I think you're speaking to the distributed nature of the two
link |
00:53:56.240
and the power of the people nature of the two.
link |
00:53:59.680
So maybe can you speak to the similarities
link |
00:54:02.280
and the differences and in which way is Numerai more powerful
link |
00:54:06.080
in which way is Wall Street Bets more powerful?
link |
00:54:09.400
Yeah, this is why the Wall Street Bets story
link |
00:54:11.000
is so interesting to me because it's like,
link |
00:54:12.800
feels like we're connected.
link |
00:54:15.120
And looking at how,
link |
00:54:16.880
just looking at the form of Wall Street Bets,
link |
00:54:19.480
I was talking earlier about how,
link |
00:54:21.480
how can you make credible claims?
link |
00:54:23.480
You're anonymous.
link |
00:54:24.360
Okay, well, maybe you can take a screenshot.
link |
00:54:26.920
Or maybe you can upvote someone.
link |
00:54:29.120
Maybe you can have karma on Reddit.
link |
00:54:31.280
And those kinds of things make this emerging thing possible.
link |
00:54:35.640
Numerai, it didn't work at all when we started.
link |
00:54:40.120
It didn't work at all.
link |
00:54:41.680
Why?
link |
00:54:42.560
People made multiple accounts.
link |
00:54:43.880
They made really random models
link |
00:54:45.720
and hoped they would get lucky.
link |
00:54:47.120
And some of them did.
link |
00:54:48.520
Yes.
link |
00:54:49.440
Staking was our solution to,
link |
00:54:53.200
could we make it so that we could trust?
link |
00:54:56.800
We could know which model people believed in the most.
link |
00:55:00.120
And we could weight models that had high stake more
link |
00:55:04.600
and effectively coordinate this group of people
link |
00:55:07.840
to be like, well, actually there's no incentive
link |
00:55:10.160
to creating bot accounts anymore.
link |
00:55:12.560
Either I stake my accounts,
link |
00:55:14.640
in which case I should believe in them
link |
00:55:16.080
because I could lose my stake or I don't.
link |
00:55:18.720
And that's a very powerful thing
link |
00:55:20.840
that having a negative incentive
link |
00:55:23.120
and a positive incentive can make things a lot better.
link |
00:55:26.840
And staking is like this,
link |
00:55:28.240
is this really nice like key thing about blockchain.
link |
00:55:31.560
It's like something special you can do
link |
00:55:33.760
where they're not even trusting us
link |
00:55:35.880
with their stake in some ways.
link |
00:55:37.560
They're trusting the blockchain, right?
link |
00:55:40.040
So the incentives, like you say,
link |
00:55:42.240
it's about making these perfect incentives
link |
00:55:44.360
so that you can have coordination to solve one problem.
link |
00:55:47.920
And nowadays I sleep easy
link |
00:55:52.120
because I have less money in my own hedge fund
link |
00:55:56.680
than our users are staking on their models.
link |
00:56:00.640
That's powerful.
link |
00:56:01.680
In some sense, from a human psychology perspective,
link |
00:56:04.280
it's fascinating that the WallStreetBets worked at all, right?
link |
00:56:08.960
That amidst that chaos, emerging behavior,
link |
00:56:12.920
like behavior that made sense emerged.
link |
00:56:15.720
It would be fascinating to think if numerized style staking
link |
00:56:20.160
could then be transferred to places like Reddit, you know?
link |
00:56:24.880
And not necessarily for financial investments,
link |
00:56:27.080
but I wish sometimes people would have to stake something
link |
00:56:34.360
in the comments they make on the internet.
link |
00:56:36.800
Yeah.
link |
00:56:37.840
That's the problem with anonymity is like,
link |
00:56:40.480
anonymity is freedom and power
link |
00:56:42.200
that you don't have to, you can speak your mind,
link |
00:56:44.960
but it's too easy to just be shitty.
link |
00:56:47.760
Yeah, exactly.
link |
00:56:49.840
So this, I mean, you're making me realize
link |
00:56:52.360
from a profoundly philosophical aspect, numerized staking
link |
00:56:58.360
is a really clean way to solve this problem.
link |
00:57:01.280
It's a really beautiful way.
link |
00:57:02.280
Of course, it only with Numerai currently works
link |
00:57:05.360
for a very particular problem, right?
link |
00:57:07.760
Not for human interaction on the internet,
link |
00:57:10.280
but that's fascinating.
link |
00:57:11.560
Yeah, there's nothing to stop people.
link |
00:57:13.520
In fact, we've open sourced the code we use for staking
link |
00:57:17.280
in a protocol we call Erasure.
link |
00:57:19.960
And if Reddit wanted to, they could even use that code
link |
00:57:23.560
to enable staking on our Wall Street pets.
link |
00:57:29.040
And they're actually researching now,
link |
00:57:30.600
they've had some Ethereum grants
link |
00:57:32.440
on how could they have more crypto stuff in there
link |
00:57:37.200
in Ethereum, because wouldn't that be interesting?
link |
00:57:40.360
Like, imagine you could, instead of seeing a screenshot,
link |
00:57:43.920
like, guys, I promise I will not sell my GameStop.
link |
00:57:49.360
We're just going to go huge.
link |
00:57:50.720
We're not going to sell at all.
link |
00:57:53.800
And here is a smart contract, which no one in the world,
link |
00:57:58.480
including me, can undo, that says,
link |
00:58:02.480
I have staked millions against this claim.
link |
00:58:08.200
That's powerful.
link |
00:58:09.200
And then what could you do?
link |
00:58:11.240
And of course, it doesn't have to be millions.
link |
00:58:12.720
It could be just a very small amount,
link |
00:58:14.560
but then just a huge number of users doing that kind of stake.
link |
00:58:17.480
Exactly.
link |
00:58:20.160
That could change the internet.
link |
00:58:21.920
It would change, and then Wall Street.
link |
00:58:23.960
It would change Wall Street.
link |
00:58:25.240
They would never have been able to,
link |
00:58:26.800
they would still be short squeezing one day
link |
00:58:29.520
after the next, every single hedge fund collapsing.
link |
00:58:32.680
If we look into the future, do you think it's possible
link |
00:58:35.360
that numerae style infrastructure,
link |
00:58:39.080
where AI systems backed by humans are doing the trading,
link |
00:58:44.760
is what the entirety of the stock market is,
link |
00:58:48.200
or the entirety of the economy, is
link |
00:58:50.240
run by basically this army of AI systems
link |
00:58:54.240
with high level human supervision?
link |
00:58:57.360
Yeah, the thing is that some of them could be bad actors.
link |
00:59:02.640
Some of the humans?
link |
00:59:03.400
No, well, these systems could be tricky.
link |
00:59:06.080
So actually, I once met a hedge fund manager,
link |
00:59:08.800
and this is kind of interesting.
link |
00:59:10.040
He said, very famous one, and he said,
link |
00:59:14.280
we can see, sometimes we can see things in the market
link |
00:59:17.600
where we know we can make money, but it will mess shit up.
link |
00:59:22.760
We know we can make money, but it will mess things up.
link |
00:59:25.360
And we choose not to do those things.
link |
00:59:28.200
And on the one hand, maybe this is like, oh, you're
link |
00:59:30.160
being super arrogant.
link |
00:59:31.920
Of course you can't do this, but maybe he can.
link |
00:59:35.240
And maybe he really isn't doing things
link |
00:59:38.280
he knows he could do, but would be pretty bad.
link |
00:59:43.560
Would the Reddit army have that kind of morality or concern
link |
00:59:51.760
for what they're doing?
link |
00:59:53.680
Probably not, based on what we've seen.
link |
00:59:55.560
The madness of crowds.
link |
00:59:57.600
There'll be one person that says, hey, maybe,
link |
01:00:00.840
and then they get trampled over.
link |
01:00:03.920
That's the terrifying thing, actually.
link |
01:00:07.320
A lot of people have written about this,
link |
01:00:08.960
is somehow that little voice that's human morality
link |
01:00:13.880
gets silenced when we get into groups and start chanting.
link |
01:00:17.920
And that's terrifying.
link |
01:00:18.760
But I think maybe I misunderstood.
link |
01:00:22.320
I thought that you're saying AI systems can be dangerous,
link |
01:00:25.920
but you just describe how humans can be dangerous.
link |
01:00:28.440
So which is safer?
link |
01:00:30.520
So one thing is, so Wall Street bets these kinds of attacks.
link |
01:00:38.640
It's not possible to model, numerize data,
link |
01:00:42.080
and then come up with the idea from the model,
link |
01:00:45.000
let's short squeak, just game stop.
link |
01:00:46.920
It's not even framed in that way.
link |
01:00:49.440
It's not possible to have that idea.
link |
01:00:52.800
But it is possible for a bunch of humans.
link |
01:00:54.960
So I think this, it's, numera could get very powerful
link |
01:00:59.680
without it being dangerous.
link |
01:01:01.840
But Wall Street bets needs to get a little bit more powerful,
link |
01:01:05.480
and it'll be pretty dangerous.
link |
01:01:08.240
Yeah, well, I mean, this is a good place
link |
01:01:11.960
to think about numera data today and numera signals
link |
01:01:17.040
and what that looks like in 10, 20, 30, 50, 100 years.
link |
01:01:22.680
Right now, I guess, maybe you can correct me,
link |
01:01:24.520
but the data that we're working with is like a window.
link |
01:01:28.040
It's an anonymized, obfuscated window
link |
01:01:32.320
into a particular aspect, time period of the market.
link |
01:01:36.640
And you can expand that more and more and more and more,
link |
01:01:40.440
potentially.
link |
01:01:41.160
You can imagine in different dimensions
link |
01:01:43.560
to where it encapsulates all the things that,
link |
01:01:47.120
where you could include kind of human to human communication
link |
01:01:52.080
that was available to buy GameStop, for example,
link |
01:01:55.960
on Wall Street bets.
link |
01:01:57.640
So maybe as a step back, can you speak
link |
01:02:00.000
to what is numera signals and what are the different data
link |
01:02:05.480
sets that are involved?
link |
01:02:07.600
So with numera signals, you're still
link |
01:02:10.800
providing predictions to us, but you can do it
link |
01:02:15.800
from your own data sets.
link |
01:02:18.080
So numera, it's all you have to model our data
link |
01:02:21.040
to come up with predictions.
link |
01:02:22.760
Numa signals is whatever data you can find out there,
link |
01:02:26.560
you can turn it into a signal and give it to us.
link |
01:02:29.880
So it's a way for us to import signals
link |
01:02:32.600
on data we don't yet have.
link |
01:02:36.800
And that's why it's particularly valuable,
link |
01:02:38.720
because it's going to be signals.
link |
01:02:42.240
You're only rewarded for signals that are
link |
01:02:44.200
orthogonal to our core signal.
link |
01:02:47.600
So you have to be doing something uncorrelated.
link |
01:02:50.040
And so strange alternative data tends to have that property.
link |
01:02:55.000
There isn't too many other signals
link |
01:02:57.280
that are correlated with what's happening on Wall Street
link |
01:03:02.320
bets.
link |
01:03:02.920
That's not going to be correlated with the price
link |
01:03:05.440
to earnings ratio.
link |
01:03:07.760
And we have some users, as of recently, as of a week ago,
link |
01:03:11.600
there was a user that created, I think he's in India,
link |
01:03:14.600
he created a signal that is scraped from Wall Street bets.
link |
01:03:21.400
And now we have that signal as one
link |
01:03:24.800
of our signals in thousands that we use at Numerai.
link |
01:03:28.800
And the structure of the signal is similar,
link |
01:03:30.800
so it's just numbers and time series data.
link |
01:03:33.200
It's exactly.
link |
01:03:34.120
And it's just like, you're providing a ranking of stocks.
link |
01:03:37.640
So you just say, a one means you like the stock,
link |
01:03:41.440
zero means you don't like the stock,
link |
01:03:43.320
and you provide that for 5,000 stocks in the world.
link |
01:03:46.640
And they somehow converted the natural language
link |
01:03:49.600
that's in the Wall Street bet.
link |
01:03:51.880
Exactly.
link |
01:03:52.760
And they open sourced this Colab notebook.
link |
01:03:55.480
You can go and see it.
link |
01:03:57.320
And so, yeah, it's making a sentiment score.
link |
01:04:00.280
And then turning it into a rank of stocks.
link |
01:04:02.200
A sentiment score.
link |
01:04:03.160
Yeah.
link |
01:04:04.120
Like, this stock sucks, or this stock is awesome.
link |
01:04:07.160
And then converting.
link |
01:04:08.000
That's fascinating.
link |
01:04:08.840
Just even looking at that data would be fascinating.
link |
01:04:11.520
So on the signal side, what's the vision?
link |
01:04:15.680
This long term, what do you see that becoming?
link |
01:04:18.240
So we want to manage all the money in the world.
link |
01:04:21.720
That's Numerai's mission.
link |
01:04:23.760
And to get that, we need to have all the data
link |
01:04:27.400
and have all of the talent.
link |
01:04:30.200
Like, there's no way, first principles,
link |
01:04:32.400
if you had really good modeling and really good data
link |
01:04:35.480
that you would lose, right?
link |
01:04:37.800
It's just a question of how much do you need to get really good.
link |
01:04:41.440
So Numerai already has some really nice data
link |
01:04:43.960
that we give out.
link |
01:04:45.160
This year, we are 10xing that.
link |
01:04:48.360
And I actually think we'll 10x the amount of data
link |
01:04:50.600
we have on Numerai every year for at least the next 10 years.
link |
01:04:55.200
Wow.
link |
01:04:55.840
So it's going to get very big, the data we give out.
link |
01:04:59.080
And signals is more data.
link |
01:05:03.640
People with any other random data set
link |
01:05:06.400
can turn that into a signal and give it to us.
link |
01:05:09.080
And in some sense, that kind of data
link |
01:05:10.560
is the edge cases, the weirdness is the,
link |
01:05:12.840
so you're focused on the bulk, the main data.
link |
01:05:16.360
And then there's just weirdness from all over the place
link |
01:05:18.640
that just can enter through this back door of Numerai signals.
link |
01:05:22.080
Exactly.
link |
01:05:22.640
And it's also a little bit shorter term.
link |
01:05:26.280
So the signals are about a seven day time horizon.
link |
01:05:31.160
And on Numerai, it's like a 30 day.
link |
01:05:33.920
So it's often for faster situations.
link |
01:05:38.560
You've written about a master plan.
link |
01:05:40.320
And you've mentioned, which I love,
link |
01:05:43.040
in a similar sort of style of big style thinking,
link |
01:05:46.520
you would like Numerai to manage all of the world's money.
link |
01:05:52.920
So how do we get there from yesterday
link |
01:05:56.400
to several years from now?
link |
01:05:59.480
Like what is the plan?
link |
01:06:02.040
So you've already started to allure to get all the data
link |
01:06:06.280
and get all the talent, humans, models.
link |
01:06:11.760
Exactly.
link |
01:06:12.680
I mean, the important thing to note there is,
link |
01:06:14.800
what would that mean?
link |
01:06:16.080
And I think the biggest thing it means
link |
01:06:18.000
is if there was one hedge fund, you
link |
01:06:22.400
would have not so much talent wasted
link |
01:06:26.200
on all the other hedge funds.
link |
01:06:27.760
Like it's super weird how the industry works.
link |
01:06:30.400
It's like one hedge fund gets a data source and hires a PhD.
link |
01:06:34.000
And another hedge fund has to buy the same data source
link |
01:06:36.440
and hire a PhD.
link |
01:06:37.600
And suddenly, a third of American PhDs
link |
01:06:40.000
are working at hedge funds.
link |
01:06:41.280
And we're not even on Mars.
link |
01:06:43.680
And so in some ways, Numerai, it's
link |
01:06:46.280
all about freeing up people who work at hedge funds
link |
01:06:49.760
to go work for Elon.
link |
01:06:52.480
Yeah.
link |
01:06:53.000
And also, the people who are working on Numerai problem,
link |
01:06:58.200
it feels like a lot of the knowledge
link |
01:07:00.240
there is also transferable to other domains.
link |
01:07:02.360
Exactly.
link |
01:07:03.920
One of our top users, he works at NASA Jet Propulsion Lab.
link |
01:07:08.080
And he's amazing.
link |
01:07:10.000
I went to go visit him there.
link |
01:07:11.680
And he's got Numerai posters.
link |
01:07:13.800
And it looks like the movies.
link |
01:07:16.560
It looks like Apollo 11 or whatever.
link |
01:07:19.320
Yeah, the point is he didn't quit his job to join full time.
link |
01:07:26.120
He's working on getting us to Jupiter's moon.
link |
01:07:29.880
That's his mission, the Europa Klippa mission.
link |
01:07:31.920
Actually, literally what you're saying.
link |
01:07:33.520
Literally.
link |
01:07:34.200
He's smart enough that we really want his intelligence
link |
01:07:37.360
to reach the stock market.
link |
01:07:38.480
Because the stock market's a good thing.
link |
01:07:39.600
Hedge funds are a good thing.
link |
01:07:40.800
All kinds of hedge funds, especially.
link |
01:07:43.040
But we don't want him to quit his job.
link |
01:07:45.360
So he can just do Numerai on the weekends.
link |
01:07:47.120
And that's what he does.
link |
01:07:47.840
He just made a model and it just automatically submits to us.
link |
01:07:50.400
And he's like one of our best users.
link |
01:07:53.240
You mentioned briefly that stock markets are good.
link |
01:07:57.400
From my sort of outsider perspective, is there a sense,
link |
01:08:01.920
do you think trading stocks is closer to gambling?
link |
01:08:06.880
Or is it closer to investing?
link |
01:08:09.480
Sometimes it feels like it's gambling as opposed to betting
link |
01:08:14.160
on companies that succeed.
link |
01:08:15.560
And this is maybe connected to our discussion of shorting
link |
01:08:17.720
in general, but from your sense, the way you think about it,
link |
01:08:21.000
is it fundamentally still investing?
link |
01:08:23.840
I do think, I mean, it's a good question.
link |
01:08:29.720
I've also seen lately people say, this is like speculation.
link |
01:08:33.480
Is there too much speculation in the market?
link |
01:08:35.680
And it's like, but all the trades are speculative.
link |
01:08:38.680
All the trades have a horizon.
link |
01:08:40.680
People want them to work.
link |
01:08:44.040
So I would say that there's certainly
link |
01:08:48.800
a lot of aspects of gambling math that applies to investing.
link |
01:08:54.920
Like one thing you don't do in gambling
link |
01:08:57.360
is put all your money in one bet.
link |
01:09:00.400
You have bankroll management, and it's a key part of it.
link |
01:09:04.280
And small alterations to your bankroll management
link |
01:09:07.600
might be better than improvements to your skill.
link |
01:09:10.680
And then there are things we care about in our fund.
link |
01:09:13.520
Like we want to make a lot of independent bets.
link |
01:09:16.560
We talk about it, like we want to make
link |
01:09:18.560
a lot of independent bets, because that's
link |
01:09:20.560
going to be a higher sharp than if you have a lot of bets that
link |
01:09:23.400
depend on each other, like all in one sector.
link |
01:09:27.920
But yeah, I mean, the point is that you
link |
01:09:31.320
want the prices of the stocks to be reflective of their value.
link |
01:09:39.120
Of the underlying value of the company.
link |
01:09:40.920
Yeah, you shouldn't have there be like a hedge fund that's
link |
01:09:45.160
able to say, well, I've looked at some data,
link |
01:09:48.160
and all of this stuff's super mispriced.
link |
01:09:51.360
That's super bad for society if it looks like that to someone.
link |
01:09:55.240
I guess the underlying question then
link |
01:09:57.600
is, do you see that the market often drifts away
link |
01:10:01.800
from the underlying value of companies,
link |
01:10:04.480
and it becomes a game in itself?
link |
01:10:06.640
Like with these, whatever they're called,
link |
01:10:09.920
like derivatives, like the options, and shorting,
link |
01:10:17.720
and all that kind of stuff.
link |
01:10:18.880
It's like layers of game on top of the actual,
link |
01:10:22.720
like what you said, which is like the basic thing
link |
01:10:25.120
that the Wall Street Bets was doing,
link |
01:10:26.440
which is like just buying stocks.
link |
01:10:28.680
Yeah.
link |
01:10:29.720
There are a lot of games that people
link |
01:10:31.960
play that are in the derivatives market.
link |
01:10:36.880
And I think a lot of the stuff people dislike when they look
link |
01:10:40.240
at the history of what's happened,
link |
01:10:42.480
they hate like credit default swaps,
link |
01:10:45.600
or collateralized debt obligations.
link |
01:10:48.040
Like these are the enemies of 2008.
link |
01:10:52.080
And then the long term capital management thing,
link |
01:10:54.760
it was like they had 30 times leverage, or something.
link |
01:11:00.000
You could just go to a gas station
link |
01:11:03.280
and ask anybody at the gas station,
link |
01:11:05.720
is it a good idea to have 30 times leverage?
link |
01:11:08.120
And they just say no.
link |
01:11:09.520
It's like common sense just like went out the window.
link |
01:11:12.160
So yeah, I don't respect long term capital management.
link |
01:11:20.520
OK.
link |
01:11:21.560
But Numerai doesn't actually use any derivatives
link |
01:11:24.360
unless you call shorting derivative.
link |
01:11:26.840
We just we do put money into companies.
link |
01:11:29.240
And that does help the companies we're investing in.
link |
01:11:32.240
It's just in little ways.
link |
01:11:34.360
We really did buy Tesla.
link |
01:11:36.360
And it did.
link |
01:11:37.520
And we played some role in its success.
link |
01:11:44.080
Super small, make no mistake.
link |
01:11:46.560
But still, I think that's important.
link |
01:11:48.160
Can I ask you a pothead question,
link |
01:11:51.200
which is what is money, man?
link |
01:11:55.720
So if we just kind of zoom out and look at,
link |
01:11:59.680
because I'd love to talk to you about cryptocurrency, which
link |
01:12:02.280
perhaps could be the future of money.
link |
01:12:04.400
In general, how do you think about money?
link |
01:12:07.720
You said Numerai, the vision, the goal
link |
01:12:10.720
is to run, to manage the world's money.
link |
01:12:15.480
What is money in your view?
link |
01:12:19.440
I don't have a good answer to that.
link |
01:12:22.240
But it's definitely in my personal life,
link |
01:12:25.200
it's become more and more warped.
link |
01:12:29.200
And you start to care about the real thing,
link |
01:12:33.280
like what's really going on here.
link |
01:12:37.040
Elon talks about things like this,
link |
01:12:39.080
like what is a company, really?
link |
01:12:40.880
It's a bunch of people who show up to work together
link |
01:12:43.440
and they solve a problem.
link |
01:12:45.480
And there might not be a stock out there
link |
01:12:47.360
that's trading that represents what they're doing,
link |
01:12:49.920
but it's not the real thing.
link |
01:12:52.920
And being involved in crypto, I put
link |
01:12:57.800
in crowdsale of Ethereum and all these other things
link |
01:13:03.440
and different crypto hedge funds and things
link |
01:13:06.240
that I've invested in.
link |
01:13:07.080
And it's just kind of like, it feels
link |
01:13:09.840
like how I used to think about money stuff
link |
01:13:13.040
is just totally warped.
link |
01:13:15.960
Because you stop caring about the price
link |
01:13:23.080
and you care about the product.
link |
01:13:26.040
So by the product, you mean the different mechanisms
link |
01:13:29.160
that money is exchanged.
link |
01:13:30.440
I mean, money is ultimately a kind of a little,
link |
01:13:33.520
one is a store of wealth, but it's also
link |
01:13:36.360
a mechanism of exchanging wealth.
link |
01:13:38.640
But what wealth means becomes a totally different thing,
link |
01:13:42.680
especially with cryptocurrency, to where it's almost
link |
01:13:45.960
like these little contracts, these little agreements,
link |
01:13:48.400
these transactions between human beings
link |
01:13:50.440
that represent something that's bigger than just cash being
link |
01:13:56.000
exchanged at 7.11, it feels like.
link |
01:13:58.080
Yeah.
link |
01:13:58.680
Maybe I'll answer what is finance.
link |
01:14:03.280
It's what are you doing when you have the ability
link |
01:14:06.600
to take out a loan?
link |
01:14:08.760
You can bring a whole new future into being with finance.
link |
01:14:15.840
If you couldn't get a student loan to get a college degree,
link |
01:14:20.240
you couldn't get a college degree
link |
01:14:22.760
if you didn't have the money.
link |
01:14:23.960
But now, weirdly, you can get it with, and all you have
link |
01:14:29.840
is this loan, which is like, so now you
link |
01:14:32.360
can bring a different future into the world.
link |
01:14:34.360
And that's how when I was saying earlier about if you rerun
link |
01:14:36.960
American economic history without these things,
link |
01:14:40.760
like you're not allowed to take out loans,
link |
01:14:42.560
you're not allowed to have derivatives,
link |
01:14:44.880
you're not allowed to have money,
link |
01:14:47.680
it just doesn't really work.
link |
01:14:49.000
And it's a really magic thing how much
link |
01:14:51.800
you can do with finance by bringing the future forward.
link |
01:14:56.040
Finance is empowering.
link |
01:14:58.080
We sometimes forget this, but it enables innovation.
link |
01:15:01.120
It enables big risk takers and bold builders that ultimately
link |
01:15:04.720
make this world better.
link |
01:15:06.160
You said you were early in on cryptocurrency.
link |
01:15:09.800
Can you give your high level overview
link |
01:15:12.120
of just your thoughts about the past, present, and future
link |
01:15:15.400
of cryptocurrency?
link |
01:15:17.760
Yeah, so my friends told me about Bitcoin,
link |
01:15:19.880
and I was interested in equities a lot.
link |
01:15:23.800
And I was like, well, it has no net present value.
link |
01:15:27.720
It has no future cash flows.
link |
01:15:29.960
Bitcoin pays no dividends.
link |
01:15:33.080
So I really couldn't get my head around it,
link |
01:15:36.120
that this could be valuable.
link |
01:15:39.520
And then I didn't feel like I was early in cryptocurrency,
link |
01:15:44.360
in fact, because it was like 2014.
link |
01:15:46.560
It felt like a long time after Bitcoin.
link |
01:15:50.120
But then I really liked some of the things
link |
01:15:52.320
that Ethereum was doing.
link |
01:15:54.200
It seemed like a super visionary thing.
link |
01:15:57.120
I was reading something that was just
link |
01:15:59.480
going to change the world when I was reading the white paper.
link |
01:16:03.240
And I liked the different constructs
link |
01:16:06.120
you could have inside of Ethereum
link |
01:16:08.000
that you couldn't have on Bitcoin.
link |
01:16:10.200
Like smart contracts and all that kind of stuff?
link |
01:16:11.800
Exactly, yeah.
link |
01:16:12.640
And even spoke about different constructions you could have.
link |
01:16:18.880
Yeah, that's a cool dance between Bitcoin and Ethereum.
link |
01:16:21.920
It's in the space of ideas.
link |
01:16:23.640
It feels so young.
link |
01:16:25.240
Like, I wonder what cryptocurrencies will look like
link |
01:16:29.360
in the future.
link |
01:16:30.160
If Bitcoin or Ethereum 2.0 or some version
link |
01:16:33.680
will stick around or any of those,
link |
01:16:35.920
who's going to win out?
link |
01:16:37.120
Or if there's even a concept of winning out at all?
link |
01:16:39.880
Is there a cryptocurrency that you especially
link |
01:16:44.640
find interesting that technically, financially,
link |
01:16:48.960
philosophically, you think is something
link |
01:16:52.200
you're keeping your eye on?
link |
01:16:54.080
Well, I don't really.
link |
01:16:55.360
I'm not looking to invest in cryptocurrencies anymore.
link |
01:16:59.200
But I mean, and many are almost identical.
link |
01:17:05.040
I mean, there wasn't too much difference
link |
01:17:09.600
between even Ethereum and Bitcoin in some ways, right?
link |
01:17:13.520
But there are some that I like the privacy ones.
link |
01:17:15.880
I mean, I like Zcash for its coolness.
link |
01:17:19.120
It's actually a different kind of invention
link |
01:17:23.640
compared to some of the other things.
link |
01:17:25.560
OK, can you speak just briefly to privacy?
link |
01:17:29.520
Is there some mechanism of preserving
link |
01:17:31.200
some privacy of the universe?
link |
01:17:32.680
So I guess everything is public.
link |
01:17:34.720
Yeah.
link |
01:17:35.200
Is that the problem?
link |
01:17:36.360
Yeah, none of the transactions are private.
link |
01:17:40.000
And so I have some numeraire.
link |
01:17:46.640
And you can just see it.
link |
01:17:48.120
In fact, you can go to a website and it says like,
link |
01:17:50.040
you can go to like, etherscan.
link |
01:17:51.520
And it'll say like, numeraire founder.
link |
01:17:54.640
And I'm like, how the hell do you guys know this?
link |
01:17:57.720
So they can reverse the near, whatever that's called.
link |
01:18:00.200
Yeah, and so they can see me move it, too.
link |
01:18:02.160
They can see me.
link |
01:18:02.920
Oh, why is he moving it?
link |
01:18:04.040
Yeah.
link |
01:18:06.040
So but yeah, Zcash.
link |
01:18:10.520
Also, when you can make private transactions,
link |
01:18:12.640
you can also play different games.
link |
01:18:14.400
Yes.
link |
01:18:15.560
And it's unclear.
link |
01:18:17.840
It's like what's quite cool about Zcash
link |
01:18:19.360
is I wonder what games are being played there.
link |
01:18:21.640
No one will know.
link |
01:18:23.040
So from a deeply analytical perspective,
link |
01:18:27.200
can you describe why Dogecoin is going to win?
link |
01:18:31.200
Which it surely will.
link |
01:18:32.440
Like it very likely will take over the world.
link |
01:18:34.960
And once we expand out into the universe,
link |
01:18:37.360
we'll take over the universe.
link |
01:18:40.080
Or on a more serious note, like what
link |
01:18:42.480
are your thoughts on the recent success of Dogecoin
link |
01:18:45.160
where you've spoken to sort of the meme stocks,
link |
01:18:49.200
the memetics of the whole thing, that it feels like the joke can
link |
01:18:55.240
become the reality.
link |
01:18:58.160
Like the meme, the joke has power in this world.
link |
01:19:02.400
Yeah.
link |
01:19:02.880
It's fascinating.
link |
01:19:04.080
Exactly.
link |
01:19:05.520
It's like why is it correlated with Elon tweeting about it?
link |
01:19:12.240
It's not just Elon alone tweeting, right?
link |
01:19:15.040
It's like Elon tweeting and that becomes
link |
01:19:17.960
a catalyst for everybody on the internet kind of like spreading
link |
01:19:22.080
the joke, right?
link |
01:19:22.960
Exactly.
link |
01:19:23.480
The joke of it.
link |
01:19:24.200
So it's the initial spark of the fire for Wall Street
link |
01:19:28.560
bets type of situation.
link |
01:19:30.520
Yeah.
link |
01:19:31.040
And that's fascinating because jokes
link |
01:19:33.680
seem to spread faster than other mechanisms.
link |
01:19:37.880
Like funny shit is very effective at captivating
link |
01:19:43.440
the discourse on the internet.
link |
01:19:47.160
Yeah, and I think you can have, like I like the one meme,
link |
01:19:51.520
like Doge, I haven't heard that name in a long time.
link |
01:19:57.760
Like I think back to that meme often.
link |
01:20:00.760
That's like funny.
link |
01:20:01.640
And every time I think back to it,
link |
01:20:04.120
there's a little probability that I might buy it, right?
link |
01:20:08.680
And so imagine you have millions of people who have had
link |
01:20:12.080
all these great jokes, told them,
link |
01:20:14.400
and every now and then they reminisce,
link |
01:20:16.320
oh, that was really funny.
link |
01:20:17.840
And then they're like, let me buy some.
link |
01:20:21.960
Wouldn't that be interesting if we travel in time
link |
01:20:25.440
like multiple centuries where the entirety
link |
01:20:28.720
of the communication of the human species is like humor?
link |
01:20:33.400
Like it's all just jokes.
link |
01:20:35.480
Like we're high on probably some really advanced drugs
link |
01:20:39.840
and we're all just laughing nonstop.
link |
01:20:42.480
It's a weird like dystopian future of just humor.
link |
01:20:47.320
Elon has made me realize how like good it feels
link |
01:20:53.200
to just not take shit seriously every once in a while
link |
01:20:55.400
and just relieve like the pressure of the world.
link |
01:20:58.600
At the same time, the reason I don't always like
link |
01:21:03.240
when people finish their sentences with lol
link |
01:21:06.360
is like when you don't take anything seriously.
link |
01:21:11.360
When everything becomes a joke,
link |
01:21:13.840
then it feels like that way of thinking
link |
01:21:20.200
feels like it will destroy the world.
link |
01:21:22.280
It's like, I often think of like,
link |
01:21:24.000
will memes save the world or destroy it?
link |
01:21:25.880
Because I think both are possible directions.
link |
01:21:28.560
Yeah, I think this is a big problem.
link |
01:21:30.320
I mean, I always felt that about America,
link |
01:21:33.200
a lot of people are telling jokes kind of all the time
link |
01:21:36.320
and they're kind of good at it.
link |
01:21:37.800
And you take someone aside, an American,
link |
01:21:42.080
you're like, I really wanna have a sincere conversation.
link |
01:21:44.240
It's like hard to even keep a straight face
link |
01:21:46.760
because everything is so, there's so much levity.
link |
01:21:50.400
So it's complicated.
link |
01:21:51.320
I like how sincere actually like your Twitter can be.
link |
01:21:54.920
You're like, I am in love with the world today.
link |
01:21:57.920
I get so much shit for it, it's hilarious.
link |
01:22:00.640
I'm never gonna stop because I realize like,
link |
01:22:03.120
you have to be able to sometimes just be real
link |
01:22:05.240
and be positive and just be, say the cliche things,
link |
01:22:09.200
which ultimately those things actually capture
link |
01:22:11.960
some fundamental truths about life.
link |
01:22:15.040
But it's a dance.
link |
01:22:16.560
And I think Elon does a good job of that
link |
01:22:20.560
from an engineering perspective of being able to joke,
link |
01:22:22.960
but everyone's mostly to pull back and be like,
link |
01:22:26.800
here's real problems, let's solve them and so on.
link |
01:22:29.720
And then be able to jump back to a joke.
link |
01:22:31.800
So it's ultimately, I think, I guess a skill that we
link |
01:22:36.280
have to learn.
link |
01:22:39.040
But I guess your advice is to invest everything
link |
01:22:41.760
anyone listening owns into Dogecoin.
link |
01:22:44.640
That's what I heard from this interaction.
link |
01:22:46.120
Yeah, no, exactly.
link |
01:22:46.960
Yeah, our hedge fund is unavailable.
link |
01:22:50.360
Just go straight to Dogecoin.
link |
01:22:52.320
You're running a successful company.
link |
01:22:55.120
It's just interesting because my mind has been in that space
link |
01:22:58.600
of potentially just being one of the millions of other
link |
01:23:01.920
entrepreneurs.
link |
01:23:03.360
What's your advice on how to build a successful startup,
link |
01:23:08.400
how to build a successful company?
link |
01:23:10.480
I think that one thing I do like,
link |
01:23:13.760
and it might be a particular thing about America,
link |
01:23:16.880
but there is something about playing,
link |
01:23:20.600
tell people what you really want to happen in the world.
link |
01:23:23.960
Don't stop.
link |
01:23:25.400
It's not gonna make it,
link |
01:23:28.720
like if you're asking someone to invest in your company,
link |
01:23:31.080
don't say, I think maybe one day we might make
link |
01:23:33.720
a million dollars.
link |
01:23:35.920
When you actually believe something else,
link |
01:23:38.520
you actually believe you're actually more optimistic,
link |
01:23:41.480
but you're toning down your optimism because you want
link |
01:23:45.240
to appear like low risk.
link |
01:23:50.080
But actually it's super high risk if your company
link |
01:23:53.320
becomes mediocre because no one wants to work
link |
01:23:56.720
in a mediocre company.
link |
01:23:57.560
No one wants to invest in a mediocre company.
link |
01:24:00.000
So you should play the real game.
link |
01:24:02.640
And obviously this doesn't apply to all businesses,
link |
01:24:04.480
but if you play a venture backed startup kind of game,
link |
01:24:07.720
like play for keeps, play to win, go big.
link |
01:24:11.600
And it's very hard to do that.
link |
01:24:13.240
I've always feel like, yeah,
link |
01:24:18.200
you can start narrowing your focus because 10 people
link |
01:24:22.040
are telling you, you gotta care about this boring thing
link |
01:24:26.200
that won't matter five years from now.
link |
01:24:28.000
And you should push back and do the real,
link |
01:24:31.600
play the real game.
link |
01:24:32.440
So be bold.
link |
01:24:33.840
So both, I mean, there's an interesting duality there.
link |
01:24:37.840
So there's the way you speak to other people
link |
01:24:41.080
about like your plans and what you are like privately
link |
01:24:45.360
just in your own mind.
link |
01:24:48.120
And maybe it's connected with what you were saying about,
link |
01:24:50.160
yeah, sincerity as well.
link |
01:24:51.920
Like if you appear to be sincerely optimistic
link |
01:24:55.800
about something that's big or crazy,
link |
01:24:59.680
it's putting yourself up to be kind of like
link |
01:25:01.640
ridiculed or something.
link |
01:25:03.160
And so if you say, my mission is to, yeah, go to Mars,
link |
01:25:08.000
it's just so bonkers that it's hard to say.
link |
01:25:12.640
It is, but one powerful thing, just like you said,
link |
01:25:17.680
is if you say it and you believe it,
link |
01:25:20.240
then actually amazing people come and work with you.
link |
01:25:25.680
Exactly.
link |
01:25:26.520
It's not just skill, but the dreams.
link |
01:25:28.800
There's something about optimism that,
link |
01:25:31.640
like that fire that you have when you're optimistic
link |
01:25:33.960
of actually having the hope of building
link |
01:25:36.200
something totally cool, something totally new,
link |
01:25:38.960
that when those people get in a room together,
link |
01:25:41.120
like they can actually do it.
link |
01:25:42.840
Yeah.
link |
01:25:43.840
Yeah, there's, yeah, that's,
link |
01:25:47.480
and also makes life really fun when you're in that room.
link |
01:25:50.800
So all of that together, ultimately,
link |
01:25:55.080
I don't know, that's what makes this crazy ride
link |
01:25:57.160
of a startup really look fun.
link |
01:25:59.640
And Elon is an example of a person who succeeded at that.
link |
01:26:02.520
There's not many other inspiring figures, which is sad.
link |
01:26:06.040
I used to be at Google and there's something that happens
link |
01:26:11.120
that sometimes when the company grows
link |
01:26:13.200
bigger and bigger and bigger,
link |
01:26:14.440
where that kind of ambition kind of quiets down a little bit.
link |
01:26:18.760
Yeah.
link |
01:26:19.600
Google had this ambition, still does,
link |
01:26:21.840
of making the world's information accessible to everyone.
link |
01:26:24.880
And I remember, I don't know, that's beautiful.
link |
01:26:28.320
I still love that dream of that they used to scan books,
link |
01:26:33.160
but just in every way possible
link |
01:26:34.760
make the world's information accessible.
link |
01:26:37.480
Same with Wikipedia.
link |
01:26:38.640
Every time I open up Wikipedia,
link |
01:26:40.480
I'm just awe inspired by how awesome humans are, man.
link |
01:26:47.200
And creating this together,
link |
01:26:48.600
I don't know what the meanings are over there,
link |
01:26:50.280
but it's just beautiful.
link |
01:26:52.720
Like what they've created is incredible.
link |
01:26:55.200
And I'd love to be able to be part of something like that.
link |
01:26:58.880
And you're right, for that, you have to be bold.
link |
01:27:01.800
And there's, and strange to me also,
link |
01:27:03.480
I think you're right that there's
link |
01:27:04.600
how many boring companies there are.
link |
01:27:06.760
Something I always talk about, especially in FinTech,
link |
01:27:08.880
it's like, why am I excited about, this is so lame.
link |
01:27:13.400
Like what is, this isn't even important.
link |
01:27:16.360
Even if you succeed, this is gonna be like terrible.
link |
01:27:19.320
This is not good.
link |
01:27:21.040
And it's just strange how people can kind of
link |
01:27:23.320
get fake enthusiastic about like boring ideas
link |
01:27:27.720
when there's so many bigger ideas that,
link |
01:27:32.600
yeah, I mean, you read these things,
link |
01:27:33.680
like this company raises money,
link |
01:27:35.000
and it's just like, that's a lot of money
link |
01:27:36.400
for the worst idea I've ever heard.
link |
01:27:38.520
Some ideas are really big.
link |
01:27:41.440
So like I worked on autonomous vehicles quite a bit.
link |
01:27:44.520
And there's so many ways in which you can present
link |
01:27:48.080
that idea to yourself, to the team you work with,
link |
01:27:50.680
to just, yeah, like to yourself when you're quietly
link |
01:27:53.120
looking in the mirror in the morning,
link |
01:27:55.200
that's really boring or really exciting.
link |
01:27:58.320
Like if you're really ambitious with autonomous vehicles,
link |
01:28:01.880
it changes the nature of like human robot interaction,
link |
01:28:06.320
it changes the nature of how we move.
link |
01:28:08.160
Forget money, forget all that stuff.
link |
01:28:09.920
It changes like everything about robotics and AI,
link |
01:28:13.240
machine learning, it changes everything about manufacture.
link |
01:28:16.440
I mean, cars, transportation is so fundamentally connected
link |
01:28:20.080
to cars, and if that changes,
link |
01:28:22.320
it's changing the fabric of society,
link |
01:28:24.560
of movies, of everything.
link |
01:28:27.360
And if you go bold and take risks
link |
01:28:29.560
and be willing to go bankrupt with your company,
link |
01:28:33.800
as opposed to cautiously, you can really change the world.
link |
01:28:37.520
And it's so sad for me to see all these autonomous companies,
link |
01:28:40.560
autonomous vehicle companies,
link |
01:28:41.520
they're like really more focused about fundraising
link |
01:28:45.160
and kind of like smoke and mirrors,
link |
01:28:46.400
they're really afraid,
link |
01:28:48.240
the entirety of their marketing is grounded in fear
link |
01:28:51.760
and presenting enough smoke to where they keep raising funds
link |
01:28:54.960
so they can cautiously use technology of a previous decade
link |
01:28:59.080
or previous two decades to kind of test vehicles
link |
01:29:02.400
here and there, as opposed to do crazy things
link |
01:29:04.960
and bold and go huge at scale, do huge data collection.
link |
01:29:10.080
And yeah, so that's just an example.
link |
01:29:12.760
Like the idea can be big,
link |
01:29:14.400
but if you don't allow yourself to take that idea
link |
01:29:17.080
and think really big with it,
link |
01:29:20.160
then you're not gonna make anything happen.
link |
01:29:22.320
Yeah, you're absolutely right in that.
link |
01:29:24.200
So you've been connected in your work
link |
01:29:28.880
with a bunch of amazing people.
link |
01:29:31.280
How much interaction do you have with investors,
link |
01:29:34.440
that whole process is an entire mystery to me.
link |
01:29:36.840
Is there some people that just have influence
link |
01:29:38.600
on the trajectory of your thinking completely,
link |
01:29:42.960
or is it just this collective energy behind the company?
link |
01:29:46.920
Yeah, I mean, I came here and I was amazed how,
link |
01:29:52.160
yeah, people would, I was only here for a few months
link |
01:29:54.840
and I met some incredible investors
link |
01:29:57.160
and I'd almost run out of money.
link |
01:29:59.720
And once they invested, I was like,
link |
01:30:04.880
I am not gonna let you down.
link |
01:30:06.800
And I was like, okay, I'm gonna send them
link |
01:30:08.280
like an email update every like three minutes.
link |
01:30:11.600
And then they don't care at all.
link |
01:30:14.160
So they kind of wanna, I don't know, like,
link |
01:30:15.720
so for some, I like it when it's just like,
link |
01:30:18.200
they're always available to talk,
link |
01:30:20.040
but a lot of building a business,
link |
01:30:23.360
especially a high tech business,
link |
01:30:26.560
there's a little for them to add, right?
link |
01:30:29.240
There's little for them to add on product.
link |
01:30:31.240
There's a lot for them to add on like business development.
link |
01:30:34.320
And if we are doing product research,
link |
01:30:36.400
which is for us research into the market,
link |
01:30:39.000
research into how to make a great hedge fund,
link |
01:30:41.800
and we do that for years,
link |
01:30:44.920
there's not much to tell the investors.
link |
01:30:47.120
So that basically is like, I believe in you.
link |
01:30:49.040
There's something, I like the cut of your jib.
link |
01:30:52.440
There's something in your idea, in your ambition,
link |
01:30:55.760
in your plans that I like.
link |
01:30:57.880
And it's almost like a pat on the back.
link |
01:30:59.800
It's like, go get them kid.
link |
01:31:01.560
Yeah, it is a bit like that.
link |
01:31:02.720
And that's cool.
link |
01:31:04.360
That's a good way to do it.
link |
01:31:05.280
I'm glad they do it that way.
link |
01:31:07.120
Like the one meeting I had,
link |
01:31:08.800
which was like really good with this
link |
01:31:10.240
was meeting Howard Morgan,
link |
01:31:13.280
who's actually a co founder of Renaissance Technologies
link |
01:31:16.760
in the like 1980s and worked with Jim Simons.
link |
01:31:21.000
And he was in the room
link |
01:31:25.840
and I was meeting some other guy and he was in the room
link |
01:31:28.200
and I was explaining how quantitative finance works.
link |
01:31:33.000
I was like, so they use mathematical models.
link |
01:31:36.600
And then he was like, yeah, I started Renaissance.
link |
01:31:40.480
I know a bit about this.
link |
01:31:43.160
And then I was like, oh my God.
link |
01:31:46.680
So yeah, but then, and then I think he kind of said, well,
link |
01:31:50.320
yeah, he said, well, cause I was talking,
link |
01:31:52.160
he was working at first round capital as a partner
link |
01:31:55.920
and they kind of said, they didn't want to invest.
link |
01:31:59.200
And then I wrote a blog post describing the idea
link |
01:32:01.920
and I was like, I really think you guys should invest.
link |
01:32:03.640
And then they end up.
link |
01:32:04.560
Oh, interesting.
link |
01:32:05.760
You convinced them on that.
link |
01:32:06.600
That must be good.
link |
01:32:07.440
Yeah, cause they're like,
link |
01:32:08.280
we don't really invest in hedge funds.
link |
01:32:09.120
And I was like, you don't see like what I'm doing.
link |
01:32:11.240
This is so a tech company, not a hedge fund, right?
link |
01:32:14.400
Yeah, and Numerai is brilliant.
link |
01:32:15.800
It's, when it caught my eye,
link |
01:32:18.240
there's something special there.
link |
01:32:19.240
So I really do hope you succeed in the,
link |
01:32:22.720
obviously it's a risky thing you're taking on,
link |
01:32:24.880
the ambition of it, the size of it,
link |
01:32:26.560
but I do hope you succeed.
link |
01:32:28.320
You mentioned Jim Simons.
link |
01:32:30.400
He comes up in another world of mine really often on the,
link |
01:32:34.520
he's just a brilliant guy on the mathematics side
link |
01:32:37.720
as a mathematician,
link |
01:32:38.760
but he's also brilliant finance hedge fund manager guy.
link |
01:32:44.120
Have you gotten a chance to interact with him at all?
link |
01:32:47.040
Have you learned anything from him on the math,
link |
01:32:51.080
on the finance, on the philosophy, life side, things?
link |
01:32:54.960
I've played poker with him.
link |
01:32:56.280
It was pretty cool.
link |
01:32:57.120
It was like, actually in the show, Billions,
link |
01:32:59.680
they kind of do a little thing about this poker tournament
link |
01:33:02.680
thing with all the hedge fund managers.
link |
01:33:04.240
And that's real life thing.
link |
01:33:06.840
And they have a lot of like world series of bracelet,
link |
01:33:09.760
world series poker bracelets holders,
link |
01:33:11.800
but it's kind of Jim's thing.
link |
01:33:13.520
And I met him there and yeah, it was kind of brief,
link |
01:33:19.200
but I was just like, he's like, oh, how do you,
link |
01:33:21.480
why are you here?
link |
01:33:22.320
And I was like, oh, Howard sent me, you know,
link |
01:33:23.880
he's like, go play this tournament,
link |
01:33:25.960
meet some of the other players.
link |
01:33:27.800
And then...
link |
01:33:29.000
Was it Texas Holdem?
link |
01:33:30.120
Yeah, Texas Holdem tournament, yeah.
link |
01:33:32.240
Do you play poker yourself or was it?
link |
01:33:33.800
Yeah, I do.
link |
01:33:34.880
I mean, it was crazy.
link |
01:33:36.440
On my right was the CEO,
link |
01:33:39.080
who's the current CEO of Renaissance, Peter Brown.
link |
01:33:42.200
And Peter Muller, who's a hedge fund manager at PDT.
link |
01:33:49.160
And yeah, I mean, it was just like,
link |
01:33:50.440
and then, you know, just everyone.
link |
01:33:51.760
And then all these bracelet world series,
link |
01:33:53.200
like people that I know from like TV.
link |
01:33:56.960
And Robert Mercer, who's fucking crazy.
link |
01:34:01.440
Who's that?
link |
01:34:02.280
He's the guy who donated the most money to Trump.
link |
01:34:08.280
And he's just like...
link |
01:34:09.120
It's a lot of personality.
link |
01:34:10.240
Character, yeah, geez, it's crazy.
link |
01:34:13.920
So it's quite cool how, yeah, like the, it was really fun.
link |
01:34:17.600
And then I managed to knock out Peter Muller.
link |
01:34:19.600
I have a, I got a little trophy for knocking him out
link |
01:34:22.680
because he was a previous champion.
link |
01:34:24.440
In fact, I think he's won the most.
link |
01:34:25.880
I think he's won three times.
link |
01:34:27.560
Super smart guy.
link |
01:34:30.520
But I will say Jim outlasted me in the tournament.
link |
01:34:35.520
And they're all extremely good at poker,
link |
01:34:41.680
but they're also, so it was a $10,000 buy in.
link |
01:34:45.880
And I was like, this is kind of expensive,
link |
01:34:50.400
but it all goes to charity, Jim's math charity.
link |
01:34:54.440
But then the way they play, they have like rebis
link |
01:34:58.360
and like they all do a shit ton of rebis
link |
01:35:01.080
because it's for charity.
link |
01:35:02.720
So immediately they're like going all in
link |
01:35:06.240
and I'm like, man, like, so I ended up adding more as well.
link |
01:35:12.000
So it's like you couldn't play at all without doing that.
link |
01:35:15.360
Yeah, the stakes are high.
link |
01:35:16.640
But you're connected to a lot of these folks
link |
01:35:18.760
that are kind of titans of just of economics
link |
01:35:25.760
and tech in general.
link |
01:35:27.200
Do you feel a burden from this?
link |
01:35:28.720
You're a young guy.
link |
01:35:30.200
I did feel a bit out of place there.
link |
01:35:33.760
The company was quite new
link |
01:35:35.640
and they also don't speak about things, right?
link |
01:35:39.920
So it's not like going to meet a famous rocket engineer
link |
01:35:44.320
who will tell you how to make a rocket.
link |
01:35:46.200
They do not want to tell you anything
link |
01:35:48.040
about how to make a hedge fund.
link |
01:35:49.600
It's like all secretive and that part I didn't like.
link |
01:35:54.200
And they were also kind of making fun of me a little bit.
link |
01:35:57.720
Like they would say, like they'd call me like,
link |
01:36:00.600
I don't know, the Bitcoin kid or.
link |
01:36:02.000
Yeah, yeah, yeah.
link |
01:36:02.840
And then they would say, even things like,
link |
01:36:05.280
member Peter, yeah, said to me something like,
link |
01:36:08.880
I don't think AI is gonna have a big role in finance.
link |
01:36:12.960
And I was like, hearing this from the CEO of Renaissance
link |
01:36:16.040
was like weird to hear because I was like,
link |
01:36:17.960
of course it will.
link |
01:36:19.080
And he's like, but he can see,
link |
01:36:21.200
I can see it having a really big impact
link |
01:36:23.400
on things like self driving cars.
link |
01:36:25.600
But finance, it's too noisy and whatever.
link |
01:36:28.280
And so I don't think it's like the perfect application.
link |
01:36:30.640
And I was like, that was interesting to hear
link |
01:36:32.520
because it's like, and I think it was that same day
link |
01:36:35.560
that Libra, I think it is, the poker playing AI
link |
01:36:40.840
started to beat like the human.
link |
01:36:42.840
So it was kind of funny hearing them like say,
link |
01:36:44.480
oh, I'm not sure AI could ever attack that problem.
link |
01:36:47.280
And then that very day it's attacking the problem
link |
01:36:49.360
of the game we're playing.
link |
01:36:51.080
Well, there's a kind of a magic to somebody
link |
01:36:55.720
who's exceptionally successful looking at you,
link |
01:36:59.920
giving you respect, but also saying that what you're doing
link |
01:37:03.560
is not going to succeed in a sense.
link |
01:37:06.280
Like they're not really saying it,
link |
01:37:08.200
but I tend to believe from my interactions with people
link |
01:37:11.240
that it's a kind of prod to say like, prove me wrong.
link |
01:37:14.880
Yeah.
link |
01:37:15.720
That's ultimately, that's how those guys talk.
link |
01:37:18.040
They see good talent and they're like.
link |
01:37:20.440
Yeah.
link |
01:37:21.280
And I think they're also saying
link |
01:37:22.400
it's not gonna succeed quickly in some way.
link |
01:37:25.880
They're like, this is gonna take a long time
link |
01:37:29.080
and maybe that's good to know.
link |
01:37:32.760
And certainly AI in trading,
link |
01:37:36.320
that's one of the most philosophically interesting questions
link |
01:37:42.280
about artificial intelligence and the nature of money.
link |
01:37:45.920
Because it's like, how much can you extract
link |
01:37:48.920
in terms of patterns from all of these millions
link |
01:37:52.360
of humans interacting using this methodology of money?
link |
01:37:57.240
It's like one of the open questions
link |
01:37:58.680
in the artificial intelligence.
link |
01:37:59.680
In that sense, you converting into a data set
link |
01:38:02.360
is one of like the biggest gifts to the research community,
link |
01:38:07.120
to the whole, anyone who loves data science and AI,
link |
01:38:11.080
this is kind of fascinating.
link |
01:38:14.080
I'd love to see where this goes actually.
link |
01:38:15.680
I think I say sometimes long before AGI destroys the world,
link |
01:38:19.840
a narrow intelligence will win all the money
link |
01:38:21.800
in the stock market.
link |
01:38:23.240
Way, like just a narrow AI.
link |
01:38:25.440
Yeah.
link |
01:38:26.360
And I don't know if I'm gonna be the one who invents that.
link |
01:38:29.920
So I'm building Numerai to make sure
link |
01:38:31.960
that that narrow AI uses our data.
link |
01:38:35.840
So you're giving a platform
link |
01:38:37.000
to where millions of people can participate
link |
01:38:38.800
and do build that narrow AI themselves.
link |
01:38:43.280
People love it when I ask this kind of question
link |
01:38:45.600
about books, about ideas and philosophers and so on.
link |
01:38:50.560
I was wondering if you had books or ideas,
link |
01:38:56.760
philosophers, thinkers that had an influence
link |
01:38:59.120
on your life when you were growing up
link |
01:39:01.440
or just today that you would recommend
link |
01:39:04.520
that people check out blog posts, podcasts, videos,
link |
01:39:08.880
all that kind of stuff.
link |
01:39:09.720
Is there something that just kind of had an impact on you
link |
01:39:12.080
that you couldn't recommend?
link |
01:39:13.760
A super kind of obvious one that I really,
link |
01:39:19.000
I was reading Zero to One while coming up with Numerai.
link |
01:39:22.240
It was like halfway through the book.
link |
01:39:24.880
And I really do like a lot of the ideas there.
link |
01:39:27.160
And it's also about kind of thinking big
link |
01:39:29.360
and also it's like peculiar little book.
link |
01:39:34.760
It's like why, like there's a little picture
link |
01:39:36.400
of the hipster versus Unabomber.
link |
01:39:38.800
And it's a weird little book.
link |
01:39:40.480
So I like, there's kind of like some depth there.
link |
01:39:42.760
In terms of a book on a, if you're thinking
link |
01:39:44.920
of doing a startup, that's a good book.
link |
01:39:47.320
A book I like a lot is maybe my favorite book
link |
01:39:52.320
is David Deutsch's Beginning of Infinity.
link |
01:39:56.200
I just found that so optimistic.
link |
01:40:00.360
It puts you, everything you read in science,
link |
01:40:03.800
it like makes the world feel like kind of colder
link |
01:40:06.520
because like it's like we're just coming from evolution
link |
01:40:10.640
and coming from nothing should be this way or whatever.
link |
01:40:15.200
And humans are not very powerful.
link |
01:40:16.800
We're just like scum on the earth.
link |
01:40:19.240
And the way David Deutsch sees things
link |
01:40:20.960
and argues, he argues them with the same rigor
link |
01:40:23.840
that the cynics often use
link |
01:40:26.200
and then has a much better conclusion.
link |
01:40:29.840
That's some of the statements of things like,
link |
01:40:33.480
anything that doesn't violate the laws
link |
01:40:35.000
of physics can be solved.
link |
01:40:39.280
So ultimately arriving at a hopeful,
link |
01:40:41.800
like a hopeful path forward.
link |
01:40:42.640
Yeah, without being like a hippie.
link |
01:40:45.680
You've mentioned kind of advice for startups.
link |
01:40:47.640
Is there, in general, whether you do a startup or not,
link |
01:40:50.600
do you have advice for young people today?
link |
01:40:52.680
You're like an example of somebody
link |
01:40:54.160
who's paved their own path
link |
01:40:56.240
and were, I would say exceptionally successful.
link |
01:40:59.200
Is there advice, somebody who's like 20 today, 18,
link |
01:41:02.800
undergrad or thinking about going to college,
link |
01:41:05.640
or in college and so on that you would give them?
link |
01:41:09.520
I think I often tell young people don't start companies.
link |
01:41:13.560
Is it not, don't start a company
link |
01:41:16.040
unless you're prepared to make it your life's work.
link |
01:41:19.120
Like that's a really good way of putting it.
link |
01:41:22.480
And a lot of people think, well, this semester
link |
01:41:25.760
I'm gonna take a semester off.
link |
01:41:27.280
And in that one semester,
link |
01:41:28.560
I'm gonna start a company and sell it or whatever.
link |
01:41:31.240
And it's just like, what are you talking about?
link |
01:41:33.360
It doesn't really work that way.
link |
01:41:34.960
You should be like super into the idea,
link |
01:41:37.200
so into it that you wanna spend a really long time on it.
link |
01:41:41.560
Is that more about psychology or actual time allocation?
link |
01:41:44.040
Like, is it literally the fact that you need to give 100%
link |
01:41:47.560
for potentially years for it to succeed?
link |
01:41:49.840
Or is it more about just the mindset that's required?
link |
01:41:53.600
Yeah, I mean, I think, well, any, I think, yeah,
link |
01:41:55.800
you don't wanna have,
link |
01:41:56.640
certainly don't wanna have a plan to sell the company
link |
01:42:00.800
like quickly or something,
link |
01:42:02.160
or it's like a company that has a very,
link |
01:42:05.560
it's like a big fashion component.
link |
01:42:07.360
Like it'll only work now.
link |
01:42:08.720
It's like an app or something.
link |
01:42:12.640
So yeah, that's a big one.
link |
01:42:14.960
And then I also think something I've thought about recently
link |
01:42:18.880
is I had a job as a quant at a fund
link |
01:42:23.480
for about two and a half years.
link |
01:42:25.920
And part of me thinks if I had spent
link |
01:42:29.080
another two years there,
link |
01:42:31.080
I would have learned a lot more
link |
01:42:34.360
and had even more knowledge to be where,
link |
01:42:38.480
to basically accelerate how long Numerai took.
link |
01:42:41.160
So the idea that you can sit in an air conditioned room
link |
01:42:44.720
and get free food,
link |
01:42:46.280
or even sit at home now in your underwear
link |
01:42:48.880
and make a huge amount of money and learn whatever you want
link |
01:42:53.400
and get, it's just crazy.
link |
01:42:55.080
It's such a good deal.
link |
01:42:56.480
Yeah, oh, that's interesting.
link |
01:42:57.920
That's the case for, I was terrified of that.
link |
01:43:00.360
Like at Google, I thought I would become really comfortable
link |
01:43:04.040
in that air conditioned room.
link |
01:43:06.160
And that, I was afraid the quant situation is,
link |
01:43:10.640
I mean, what you present is really brilliant
link |
01:43:13.280
that it's exceptionally valuable, the lessons you learn,
link |
01:43:17.640
because you get to get paid while you learn from others.
link |
01:43:21.120
If you see that, if you see jobs
link |
01:43:24.160
in the space of your passion that way,
link |
01:43:27.800
that it's just an education.
link |
01:43:29.360
It's like the best kind of education.
link |
01:43:31.400
But of course you have, from my perspective,
link |
01:43:34.200
you have to be really careful on that to get comfortable.
link |
01:43:37.320
Again, in a relationship, then you buy a house
link |
01:43:39.760
or whatever the hell it is, and then you get,
link |
01:43:42.720
and then you convince yourself like,
link |
01:43:44.200
well, I have to pay these fees for the car,
link |
01:43:46.640
for the house, blah, blah, blah.
link |
01:43:48.240
And then there's momentum and all of a sudden
link |
01:43:50.360
you're on your death bed and there's grandchildren
link |
01:43:53.080
and you're drinking whiskey
link |
01:43:55.160
and complaining about kids these days.
link |
01:43:56.960
So I'm afraid of that momentum, but you're right.
link |
01:44:00.800
Like there's something special about the education
link |
01:44:04.120
you get working at these companies.
link |
01:44:06.320
Yeah, and I remember on my desk,
link |
01:44:08.200
I had like a bunch of papers on quant finance,
link |
01:44:11.320
a bunch of papers on optimization,
link |
01:44:13.280
and then the paper on Ethereum, just on my desk as well,
link |
01:44:16.680
and the white paper, and it's like,
link |
01:44:19.280
it's been amazing how kind of, and you can learn about,
link |
01:44:23.680
so that, I also thought, I think this idea
link |
01:44:25.680
of like learning about intersections of things,
link |
01:44:28.440
I don't think there are too many people that know
link |
01:44:30.240
like as much about crypto and quant finance
link |
01:44:33.640
and machine learning as I do.
link |
01:44:36.280
And that's a really nice set of three things
link |
01:44:39.280
to know stuff about.
link |
01:44:40.640
And that was because I had like free time in my job.
link |
01:44:45.160
Okay, let me ask the perfectly impractical,
link |
01:44:48.640
but the most important question.
link |
01:44:49.840
What's the meaning of all the things you're trying to do
link |
01:44:53.760
so many amazing things, why?
link |
01:44:56.200
What's the meaning of this life of yours or ours?
link |
01:45:00.800
I don't know.
link |
01:45:01.840
Humans.
link |
01:45:03.400
Yeah, so I have yet had some people say,
link |
01:45:06.300
asking what meaning of life is,
link |
01:45:07.760
is like asking the wrong question or something.
link |
01:45:10.160
The question is wrong.
link |
01:45:11.160
Yeah.
link |
01:45:12.000
No, usually people get too nervous to be able to say that
link |
01:45:14.640
because it's like your question sucks.
link |
01:45:17.480
I don't think there's an answer.
link |
01:45:18.800
It's like the searching for it.
link |
01:45:21.120
It's like sometimes asking it.
link |
01:45:22.880
It's like sometimes sitting back and looking up at the stars
link |
01:45:25.560
and being like, huh, I wonder if there's aliens up there.
link |
01:45:29.800
There's a useful like a palette cleanser aspect to it
link |
01:45:36.520
because it kind of wakes you up to like all the little busy,
link |
01:45:39.600
hurried day to day activities, all the meetings,
link |
01:45:42.680
all the things you'd like a part of.
link |
01:45:45.220
We're just like ants, a part of a system,
link |
01:45:47.640
a part of another system.
link |
01:45:48.920
And then asking this bigger question
link |
01:45:52.120
allows you to kind of zoom out and think about it.
link |
01:45:53.920
But there's ultimately,
link |
01:45:56.240
I think it's an impossible thing for a limited capacity,
link |
01:45:58.880
like cognitive capacity to capture.
link |
01:46:01.520
But it's fun to listen to somebody
link |
01:46:03.040
who's exceptionally successful, exceptionally busy now,
link |
01:46:07.240
who's also young like you,
link |
01:46:09.800
to ask these kinds of questions about like death.
link |
01:46:14.640
You know, do you consider your own mortality kind of thing
link |
01:46:18.280
and life, whether that enters your mind?
link |
01:46:21.760
Because it often doesn't,
link |
01:46:23.240
it kind of almost gets in the way.
link |
01:46:24.920
Yeah.
link |
01:46:26.260
It's amazing how many things you can like that are trivial
link |
01:46:28.840
that could occupy a lot of your mind
link |
01:46:31.280
until something bad happens or something flips you.
link |
01:46:36.400
And then you start thinking about the people you love
link |
01:46:38.480
that are in your life.
link |
01:46:39.760
Then you started thinking about like,
link |
01:46:41.080
holy shit, this ride ends.
link |
01:46:42.840
Exactly.
link |
01:46:43.960
Yeah, I just had COVID and I had it quite bad.
link |
01:46:48.960
What wasn't really bad is just like,
link |
01:46:51.720
I also got a simultaneous like lung infection.
link |
01:46:55.720
So I had like almost like bronchitis or whatever.
link |
01:46:59.280
I don't even, I don't understand that stuff,
link |
01:47:01.960
but I started, and then you're forced to be isolated.
link |
01:47:06.280
Right.
link |
01:47:07.120
And so it's actually kind of nice
link |
01:47:08.880
because it's very depressing.
link |
01:47:12.440
And then I've heard stories of, I think it's Sean Parker.
link |
01:47:15.800
He had like all these diseases as a child
link |
01:47:18.240
and he had to like just stay in bed for years.
link |
01:47:20.640
And then he like made Napster.
link |
01:47:23.320
It's like pretty cool.
link |
01:47:24.840
So yeah, I had about 15 days of this recently,
link |
01:47:27.680
just last month.
link |
01:47:28.520
And it feels like it did shock me
link |
01:47:30.400
into a new kind of energy and ambition.
link |
01:47:34.640
Were there moments when you were just like terrified
link |
01:47:37.960
at the combination of loneliness?
link |
01:47:39.680
And like, you know, the thing about COVID is like,
link |
01:47:43.120
there's some degree of uncertainty.
link |
01:47:45.480
Like it feels like it's a new thing, a new monster
link |
01:47:48.400
that's arrived on this earth.
link |
01:47:50.920
And so, you know, dealing with it alone,
link |
01:47:54.280
a lot of people are dying.
link |
01:47:55.680
It's like wondering like.
link |
01:47:57.240
Yeah, you do wonder, I mean, for sure.
link |
01:47:59.200
And then there are the even new strains in South Africa,
link |
01:48:03.160
which is where I was.
link |
01:48:04.000
And maybe the new strain had some interaction
link |
01:48:06.920
with my genes and I'm just gonna die.
link |
01:48:09.520
But ultimately it was liberating somehow.
link |
01:48:11.440
I loved it.
link |
01:48:12.600
Oh, I loved that I got out of it.
link |
01:48:15.440
Okay.
link |
01:48:16.280
Because it also affects your mind.
link |
01:48:17.120
You get confused, you get confusion
link |
01:48:18.680
and kind of a lot of fatigue
link |
01:48:21.360
and you can't do your usual tricks
link |
01:48:23.360
of psyching yourself out of it.
link |
01:48:24.800
So, you know, sometimes it's like, oh man, I feel tired.
link |
01:48:27.440
Okay, I'm just gonna go have coffee and then I'll be fine.
link |
01:48:29.720
It's like, now it's like, I feel tired.
link |
01:48:31.440
I don't even wanna get out of bed to get coffee
link |
01:48:33.440
because I feel so tired.
link |
01:48:34.680
And then you have to confront,
link |
01:48:37.120
there's no like quick fix cure and you're trapped at home.
link |
01:48:40.840
But that, so now you have this little thing
link |
01:48:43.320
that happened to you that was a reminder
link |
01:48:44.920
that you're mortal and you get to carry that flag
link |
01:48:48.160
in trying to create something special in this world.
link |
01:48:53.280
Right?
link |
01:48:54.120
With Numerai.
link |
01:48:54.960
Listen, this was like one of my favorite conversation
link |
01:48:58.320
because the way you think about this world of money
link |
01:49:03.280
and just this world in general is so clear
link |
01:49:05.200
and you're able to explain it so eloquently.
link |
01:49:08.680
Richard, that was really fun.
link |
01:49:09.960
Really appreciate you talking to me.
link |
01:49:11.000
Thank you.
link |
01:49:11.840
Thank you.
link |
01:49:13.160
Thanks for listening to this conversation with Richard Crave
link |
01:49:15.680
and thank you to our sponsors,
link |
01:49:17.800
Audible Audio Books, Trial Labs,
link |
01:49:20.240
Machine Learning Company, Blinkist app
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01:49:22.840
that summarizes books and Athletic Greens
link |
01:49:25.640
all in one nutrition drink.
link |
01:49:27.560
Click the sponsor links to get a discount
link |
01:49:29.840
and to support this podcast.
link |
01:49:32.080
And now let me leave you with some words from Warren Buffett.
link |
01:49:36.640
Games are won by players who focus on the playing field,
link |
01:49:40.600
not by those whose eyes are glued to the scoreboard.
link |
01:49:44.600
Thank you for listening and hope to see you next time.