The following is a conversation with Richard Crape, founder of Numeri, which is a crowdsourced
hedge fund, very much in the spirit of Wall Street bets, but where the trading is done,
not directly by humans, but by artificial intelligence systems submitted by those humans.
It's a fascinating and extremely difficult machine learning competition
where the incentives of everybody is aligned, the code is kept and owned by the people who
develop it, the data, anonymous data is very well organized and made freely available.
I think this kind of idea has a chance to change the nature of stock trading and even just money
management in general by empowering people who are interested in trading stocks with the modern
and quickly advancing tools of machine learning. Quick mention of our sponsors, Audible Audiobooks,
ChiroLabs Machine Learning Company, Blinkist App that summarizes books and Athletic Greens,
all in one nutrition drink. Click the sponsor links to get a discount and to support this
podcast. As a side note, let me say that this whole set of events around GameStop and Wall
Street bets has been really inspiring to me as a demonstration that a distributed system,
a large number of regular people are able to coordinate and collaborate in
taking on the elite centralized power structures, especially when those elites are misbehaving.
I believe that power in as many cases as possible should be distributed and in this case,
the internet as it is for many cases is the fundamental enabler of that power.
And at the core, what the internet and its distributed nature represents is freedom.
Of course, the thing about freedom is it enables chaos or progress or sometimes both.
And that's kind of the point of the thing. Freedom is empowering, but ultimately unpredictable.
And I think in the end, freedom wins. If you enjoy this podcast, subscribe on YouTube,
review it on Apple podcasts, follow on Spotify, support on Patreon or connect with me on Twitter
at Lex Freedman. And now here's my conversation with Richard Crabe.
From your perspective, can you summarize the important events around this amazing saga that
we've been living through of Wall Street bets, the subreddit and GameStop and in general,
just what are your thoughts about it from a technical to the philosophical level?
I think it's amazing. It's my favorite story ever. When I was reading about it, I was like,
this is the best. And it's also connected with my company, which we can talk about.
But what I liked about it is I like decentralized coordination and looking at the mechanisms
that these are Wall Street bets users use to hype each other up, to get excited,
to prove that they bought the stock and they're holding. And then also to see that how big of
an impact that that decentralized coordination had. It really was a big deal.
Were you impressed by the distributed coordination, the collaboration amongst like,
I don't know what the numbers are, I know a numerized looking at the data.
After all of this is over and done, it'd be interesting to see from a large-scale distributed
system perspective to see how everything played out. But just from your current perspective,
what we know, is it obvious to you that such incredible level of coordination
could happen where a lot of people come together and distribute a sense,
there's an emergent behavior that happens after that?
No, it's not at all obvious. And one of the reasons is the lack of kind of like
credibility. To coordinate with someone, you need to kind of make credible contracts or
credible claims. So if you have a username on our Wall Street bets,
like some of them are, like deep fucking value is one of them.
That's an actual username. By the way, we're talking about,
there's a website called Reddit and there's subreddits on it. And a lot of people, most the
anonymous, I think for the most part, anonymous can create user accounts and then can then just
talk on form like style boards. You should know what Reddit is. If you don't know what Reddit is,
check it out. If you don't know what Reddit is, maybe go to the subreddit first,
www.withcupicturesofgatsanddogs. That's my recommendation. Anyway.
Yeah, that would be a good start to Reddit. When you get into it more, go to our Wall
Street bets. It gets dark quickly. We'll probably talk about that too. So yeah,
so there's these users and there's no contracts, like you were saying.
There's no contracts. The users are anonymous, but there are little things that do help. So
for example, if you've posted a really good investment idea in the past, that exists on
Reddit as well. And it might have lots of upvotes. And that's also kind of like giving
credibility to your next thing. And then they are also putting up screenshots.
Like here's the trades I've made and here's a screenshot. Now you could fake the screenshot,
but still it seems like if you've got a lot of karma and you've had a good
performance on the community, it somehow becomes credible enough for other people to be like,
you know what? He actually probably did put a million dollars into this. And you know what?
I can follow that trade easily. And there's a bunch of people like that. So you're kind of
integrating all that information together yourself to see like, huh, there's something
happening here. And then you jump it onto this little boat of behavior, like we should buy
the stock or sell the stock. And then another person jumps on another person jumps on.
And all of a sudden you have just a huge number of people behaving in the same direction. It's
like flock of whatever birds. Exactly. What was strange with this one, it wasn't just let's all
buy Tesla. We love Elon. We love the Tesla. Let's all buy Tesla because that we've heard before,
right? Everybody likes Tesla. Now they do. So what they did with this in this case,
they're buying a stock that was bad. They're buying it because it was bad. And that's really
weird because that's a little bit too galaxy brain for a decentralized community. How did
they come up with it? How did they know that was the right one? And the reason they liked it
is because it had really, really high short interest. It had been shorted more than its own
float, I believe. And so they figured out that if they all bought this bad stock,
they could short squeeze some hedge funds. And those hedge funds would have to capitulate
and buy the stock at really, really high prices. And we should say that shorted means that
these are a bunch of people, when you short a stock, you're predicting that the stock is
going to go down and then you will make money if it does. And then what's the short squeeze?
It's really that if you are a hedge fund and you take a big short position in a company,
there's a certain level at which you can't sustain holding that position. There's no limit
to how high a stock can go, but there is a limit to how low it can go, right? So if you short
something, you have infinite loss potential. And if the stock doubles overnight, like GameStop did,
you're putting a lot of stress on that hedge fund. And that hedge fund manager might have to say,
you know what? I have to get out of the trade. And the only way to get out is to buy the bad
stock that they don't want, like they believe will go down. So it's an interesting situation,
particularly because it's not zero sum. If you say, let's all get together and make a bubble in
watermelons, you buy a bunch of watermelons, the price goes up, comes down again, it's a zero sum
game. If someone's already shorted a stock and you can make them short squeeze, it's actually
a positive sum game. So yes, some redditors will make a lot of money, some will lose a lot,
but actually the whole group will make money. And that's really why it's such a clever thing
for them to do. And coupled with the fact that shorting, I mean, maybe you can push back. But
to me, always from an outsider's perspective, seemed, I hope I'm not using too strong of a word,
but it seemed almost unethical. Maybe not unethical. Maybe it's just an asshole thing to do.
Okay, I'm speaking not from an economics or financial perspective, I'm speaking from
just somebody who loves, I'm a fan of a lot of people, I love celebrating the success of a lot
of people. And this is like the stock market equivalent of like haters. I know that's not
what it is. I know that there's efficient, you want to have an economy efficient mechanism for
punishing sort of overhyped, overvalued things. That's what shorting is designed for. But it just
always felt like these people are just because they're not just betting on the loss of the company.
It feels like they're also using their leverage and power to manipulate media or just to write
articles or just to hate on you on social media. And you get to see that with Elon Musk and so on.
So this is like the man, so people like hedge funds that were shorting are like the
sort of embodiment of the evil or just the bad guy, the overpowerful that's misusing their power.
And here's the crowd, the people that are standing up and rising up. So it's not just that they were
able to collaborate on Wall Street bets to sort of effectively make money for themselves. It's
also that this is like a symbol of the people getting together and fighting the centralized elites,
the powerful. And that, you know, I don't know what your thoughts are about that in general.
At this stage, it feels like that's really exciting that people have power, just like
regular people have power. At the same time, it's scary a little bit because, you know,
just studying history, people could be manipulated by charismatic leaders.
And so like, just like Elon right now is like manipulating, encouraging people to buy Dogecoin
or whatever. There can be good charismatic leaders and there can be bad charismatic leaders.
And so it's nerve wracking. It's a little bit scary how much power subreddit can have to destroy
somebody because right now we're celebrating they might be attacking or destroying somebody that
everybody doesn't like. But what if they attack somebody that is actually good for this world?
So that, and that's kind of the, the awesomeness and the price of freedom is like it could destroy
the world or it can save the world. But at this stage, it feels like, I don't know,
overall, when you sit back, do you think this was just a positive wave of emergent behavior?
Is there something negative about what happened?
Well, yeah, the cool thing is that they weren't doing anything, the reddit people weren't doing
anything exotic. It was a creative trade, but it wasn't exotic. It was just buying the stock.
Okay, maybe they bought some options too. But it was the hedge fund that was doing the exotic
thing. So I like that. It was, it's hard to say, well, you know, we've got together and we've put
all pulled all our money together. And now there's a company out there that's worth more. What's
wrong with that? Yeah. Right. But it doesn't talk about, you know, the motivations, which is,
and then we destroyed some hedge funds in the process.
Is there something to be said about the, the humor and I don't know, the edginess,
sometimes viciousness of that subreddit. I haven't looked at it too much, but it feels like people
can be quite aggressive on there. So is there, what is that? Is that what, is that what freedom
looks like? I think it does. Yeah. You definitely need to let people, one of the things that people
have compared it to is the Occupy Wall Street, which is let's say, you know, some very sincere
liberals, like 23 years old, whatever, and they go out with signs and they, they have some kind of
case to make. But this isn't sincere. Really. It's like a little bit more nihilistic, a little bit
more YOLO. And therefore a little bit more scary, because who's scared of the, who's scared of the
Wall Street Occupy Wall Street people with the signs? Nobody. But these hedge funds really
are scared. I was scared of the, of the Wall Street bats people. I'm still scared of them.
Yeah. The anonymity is a bit terrifying and exciting. Yeah. I mean, yeah, I don't know what
to do with it. You know, I've been following events in Russia, for example, it's like, there's a
struggle between centralized power and the distributed. I mean, that's the struggle of
the history of human civilization, right? But this on the internet, just that you can multiply
people, like some of them don't have to be real, like you can probably create bots. Like
it starts getting me, me as a programmer, I start to think like, hmm, me as one person,
how much cash can, can I create by writing some bots? Yeah. And I'm sure I'm not the only one
thinking that there's, I'm sure that the hundreds, thousands of good developers out there listening
to this thinking the same thing. And then as that develops further and further in the next like
decade or two, what impact does that have on financial markets on just destruction of
reputations of just or politics, you know, the bickering of left and right political discourse,
the dynamics of that being manipulated by, you know, the people talk about like Russian bots or
whatever. We're probably in the very early stage of that, right? Exactly. And this is a good example.
See, do you have a, do you have a sense that most of Wall Street bets folks are actually individual
people, right? That's the feeling I have is they're just individual, maybe young investors,
just doing a little bit of an investment, but just on a large scale. Yeah, exactly. The reason I
found out, I've known about Wall Street bets for a while, but the reason I found out about GameStop
was this, I met somebody at a party who told me about it and he was like 21 years old and he's
like, it's going to go up a hundred percent in the next one day that we're talking about in last
year. This was probably, no, this was, yeah, a few days ago. I went out, yeah, it was like maybe,
maybe two weeks ago or something. So it was, it was already high GameStop, but it was just strange
to me that there was someone telling me at a party how to trade stocks. He was like 21 years old
and it started to, yeah, it started to look into it. And yeah, and he did make, he made, yeah,
he made 140% in one day. He was right. And now he's, you know, supercharged. He's a little bit
wealthy and now he's going to look, wait for the next thing. And this decentralized entity is just
going to get bigger and bigger. And they're going to together search for the next thing. So there's
thousands of folks like him and they're going to probably search for the next thing to attack.
People that have power in this world that sit there with power right now in government and
finance in any kind of position are probably a little bit scared right now. And honestly,
that's probably a little bit good. It's dangerous, but it's good. Yeah, it certainly makes you think
twice about shorting. It certainly makes you think twice about putting a lot of money into a short.
Like these funds put a lot into one, one or two names. And so it was very, very badly risk managed.
Do you think shorting is, can you speak at a high level just for your own as a person?
Is it good for the world? Is it good for markets?
I do think that the two kinds of shorting, evil shorting and chill shorting,
evil shorting is what Melvin Capital was doing. And it's like you put a huge position down,
you get all your buddies to also short it, and you start making press and trying to
bring this company down. And I don't think in some cases, you go out to like fraudulent companies
say, this company is a fraud. Maybe that's okay. But they weren't even saying games
up. They're just saying it's a bad company and we're going to bring it to the ground,
bring it to its knees. A quant fund like Numeri, we always have lots of positions and we never
have a position that's like more than 1% of our fund. So we actually have right now 250 shorts.
I don't know any of them except for one, because it was one of the meme stocks.
But we shorting them not to make them go, we don't even want them to go down necessarily.
That doesn't sound a bit strange that I say that. But we just want them to not go up as much as our
longs. So by shorting a little bit, we can actually go long more in the things we do believe in.
So when we were going long in Tesla, we could do it with more money than we had because we'd
borrow from banks who would lend us money because we had longs and shorts, because we didn't have
market exposure and have market risk. And so I think that's a good thing because that means
we can short the oil companies and go long Tesla and make the future come forward faster.
And I do think that's not a bad thing. So we talked about this incredible distributed system
created by Wall Street Bets. And then there's a platform, which is Robinhood,
which allows investors to efficiently, as far as you can correct me if I'm wrong, but there's
those and there's others and there's numeri that allow you to make it accessible for people to
invest. But that said, Robinhood was in a centralized way applied its power to restrict
trading on the stock that we're referring to. Do you have a thought on actually like
the things that happened? I don't know how much you were paying attention to sort of the shadiness
around the whole thing. Do you think it was forced to do it? Or was there something shady
going on? What are your thoughts in general? Well, I think I want to see the alternate history,
like I want to see the counterfactual history of them not doing that. How bad would it have gotten
for hedge funds? How much more damage could have been done if the momentum of these short
squeezes could continue? What happens when there are short squeezes, even if they're in a few stocks,
they affect kind of all the other shorts too. And suddenly brokers are saying things like,
you need to put a more collateral. So we had a short. It wasn't GameStop. Luckily, it was BlackBerry.
And it went up like 100% in a day. It was one of these meme stocks, super bad company. The AIs
don't like it. Okay. The AIs think it's going down. What's a meme stock? A meme stock is kind of a
new term for these stocks that catch memetic momentum on Reddit. And so the meme stocks were
GameStop, the biggest one, GameStunk, as Elon calls it, AMC, and BlackBerry was one, Nokia was one.
So these are high short interest stocks as well. So these are targeted stocks that some people say,
oh, isn't it adorable that these people are investing money in these companies that are
nostalgic? It's like, you go into the AMC movie theater, it's like nostalgic. It's like, no.
It's not why they're doing it. It's that they had a lot of short interest. That was the main thing.
And so there were high chance of short squeeze.
In saying, I would love to see an alternate history, do you have a sense that that
what is your prediction of what that history would have looked like?
Well, you wouldn't have needed very many more days of that kind of chaos to hurt hedge funds.
I think it's underrated how damaging it could have been. Because when your shorts go up,
your collateral requirements for them go up, similar to Robinhood, like we have a prime broker
that says, said to us, you need to put up like $40 per $100 of short exposure.
And then the next day they said, actually, you have to put up all of it, 100%. And we were like,
what? But if that happens to all the short, all the commonly held hedge fund shorts,
because they're all kind of holding the same things, if that happens, not only do you have to
cover the short, which means you're buying the bad companies, you need to sell your good companies
in order to cover the short. So suddenly, all the good companies, all the ones that the hedge
funds like are coming down, and all the ones that the hedge funds hate are going up in a
cascading way. So I believe that if you could have had a few more days of GameStop doubling,
AMC doubling, you would have had more and more hedge fund deleveraging.
But so hedge funds, I mean, they get a lot of shit, but do you have a sense
that they do some good for the world? First of all, Wall Street Bets itself is a kind of distributed
hedge fund. Numerize a kind of hedge fund. So like a hedge fund is a very broad category.
I mean, if some of those were destroyed, would that be good for the world?
Or would there be coupled with the destroying the evil shorting? Would there be just a lot of pain
in terms of investment in good companies? Yeah, a thing I like to tell people if they hate hedge
funds is I don't think you want to rerun American economic history without hedge funds.
So on mass, they're good. Yeah, they're good. Yeah, you really wouldn't want to.
Because hedge funds are kind of like picking up, they're making liquidity right in stocks.
And so if you love venture capitalists, they're investing in new technology, it's so good.
You have to also kind of like hedge funds because they're the reason venture capitalists
exist because their companies can have a liquidity event when they go to the public markets.
So it's kind of essential that we have them. There are many different kinds of them.
I believe we could maybe get away with only having an AI hedge fund.
But we don't necessarily need these evil billions type hedge funds that make the
media and try to kill companies. But we definitely need hedge funds.
Maybe from your perspective, because you run such an organization and Vlad, the CEO of Robinhood,
sort of had to make decisions really quickly, probably had to wake up in the middle of the
night kind of thing. And he also had a conversation with Elon Musk on Clubhouse,
which I just signed up for. It was a fascinating, one of the great journalistic
performances of our time with Elon Musk. Pulled a surprise for Elon.
How hilarious would it be if he gets a pull surprise? And then his Wikipedia would be like
journalist and part-time entrepreneur. Business Magnet.
I don't know if you can comment on any aspects of that. But if you were with Vlad,
how would you do things differently? What are your thoughts about his interaction with Elon?
How he should have played it differently? I guess there's a lot of aspects of this
interaction. One is about transparency. How much do you want to tell people about really
what went down? There's NDAs potentially involved. How much in private do you want to push back
and say, no, fuck you to centralize power, whatever the phone calls you're getting,
which I'm sure he's getting some kind of phone calls that might not be contractual,
like it's not contracts that are forcing him, but he was being what do you call it,
like pressured to behave in certain kinds of ways from all kinds of directions? What do you take
from this whole situation? I was very excited to see Vlad's response. I mean, it's pretty cool
to have him talk to Elon. And one of the things that struck me in the first few seconds of
Vlad speaking was like, I was like, is Vlad like a boomer? But here we are. He seemed like
a 55-year-old man talking to a 20-year-old. Elon was like the 20-year-old. And he's like
the 55-year-old man. You can see why Citadel are NMR buddies, right? Like you can. You can
see why. It's like, this is a nice, it's not a bad thing. It's like he's got a respectable,
professional attitude. Well, he also tried to do like a jokey thing. No, we're not being
ages here, boomer. But like a 60-year-old CEO of Bank of America would try to make a joke for
the kids. That's what Vlad's talking about. Exactly. Yeah. I was like, what is this? This guy's like,
what is he, 30? Yeah. And I'm like, this is weird. But I think, and maybe that's also what I like
about Elon's kind of influence on American business is like, he's super like anti-the
professional. Why say 100 words about nothing? And so I liked how he was cutting in and saying,
Vlad, what do you mean? Spill the beans, bro. Yeah. So you don't have to be courteous. It's
like the first principle is thinking. It's like, what the hell happened? Yes. And let's just talk
like normal people. The problem, of course, is for Elon, it's cost them, what is it, tens of millions
of dollars is tweeting like that. But perhaps it's a worthy price to pay because ultimately,
there's something magical about just being real and honest and just going off the cuff and making
the mistakes and paying for them, but just being real. And then moments like this, that was an
opportunity for Vlad to be that. And he felt like he wasn't. Do you think we'll ever find out
what really went down if there was something shady underneath it all? Yeah. I mean, it would be sad
if nothing shady happened. Right. But his presence made it shady. Sometimes I feel like that would
Mark Zuckerberg, the CEO of Facebook, sometimes I feel like, yeah, there's a lot of shady things
that Facebook is doing. But sometimes I think he makes it look worse by the way he presents himself
about those things. I honestly think that a large amount of people at Facebook just have a huge
unstable chaotic system and they're all, not all, but mass are trying to do good with this chaotic
system. But the presentation is like, it sounds like there's a lot of back room conversations
that are trying to manipulate people. And there's something about the realness that Elon has that
it feels like CEO should have and Vlad had that opportunity. I think Mark Zuckerberg had that
too when he was younger. Younger. And somebody said, you got to be more professional man. You
can't say, you know, lol to an interview. And then suddenly he became like this distant person
that was hot. I'd like you'd rather have him make mistakes, but be honest than be like professional
never make mistakes. Yeah. One of the difficult hires I think is like marketing people or like PR
people is you have to hire people that get the fact that you can say lol on an interview or
you know, take risks as opposed to what the PR, I thought to quite a few big CEOs and
the people around them are trying to constantly minimize the risk of like, what if he says the
wrong thing? What if she says the wrong thing? It's like, what, like, be careful. It's constantly
like, ooh, like, I don't know. And there's this nervous energy that builds up over time with
larger, larger teams where the whole thing, like I visited YouTube, for example, everybody I talked
at YouTube, incredible engineering and incredible system, but everybody's scared. Like, let's be,
let's be honest about this like madness that we have going on of huge amounts of video that we
can't possibly ever handle. There's a bunch of hate on YouTube. There's this chaos of comments,
bunch of conspiracy theories, some of which might be true. And then just like this mess that we're
dealing with, and it's exciting, it's beautiful. It's a place where like democratizes education,
all that kind of stuff. And instead, they're all like, sitting in like, trying to be very polite
and saying like, well, we're just want to improve the health of our platform. Like,
all right, man, let's just be real. Let's both advertise how amazing this freaking thing is,
but also to say like, we don't know what we're doing. We have all these Nazis posting videos on
YouTube. We don't know how to like handle it and just being real like that. I suppose that's just
the skill. Maybe it can't be taught. But over time, the whatever the dynamics of the company is,
it does seem like Zuckerberg and others get worn down. They just get tired. They get tired of
not being real. Of not being real, which is sad. So let's talk about Numeri, which is an incredible
company system idea, I think, but good place to start. What is Numeri and how does it work?
So Numeri is the first hedge fund that gives away all of its data. So this is like probably the
last thing a hedge fund would do, right? Why would we give away a data? It's like giving away your edge.
But the reason we do it is because we're looking for people to model our data. And the way we do it
is by obfuscating the data. So when you look at Numeri's data that you can download for free,
it just looks like a million rows of numbers between zero and one. And you have no idea what
the columns mean. But you do know that if you're good at machine learning or have done regressions
before, you know that I can still find patterns in this data, even though I don't know what the
features mean. And the data itself is a time series data. And even though it's obfuscated,
anonymized, what is the source data like approximately? What are we talking about?
So we are buying data from lots of different data vendors. And they would also never want us to
share that data. So we have strict contracts with them. But it's the kind of data you could
never buy yourself unless you had maybe a million dollars a year of budget to buy data.
So what's happened with the hedge fund industry is you have a lot of talented people
who used to be able to trade and still can trade. But now they have such a data disadvantage,
it would never make sense for them to trade themselves. But Numeri, by giving away this
obfuscated data, we can give them a really, really high quality data set that would otherwise be
very expensive. And they can use whatever new machine learning technique they want to find
patterns in that data that we can use in our hedge fund.
And so how much of a variety is there in underlying data? We're talking about,
I apologize if I'm using the wrong terms, but one is just like the stock price.
The other, there's options and all that kind of stuff like what are they called, order books or
whatever. Is there maybe other totally unrelated directly to the stock market data?
Natural language as well, all that kind of stuff?
Yeah, we were really focused on data that's specific to stocks. So things like every stock
has a PE ratio. For some stocks it's not as meaningful, but every stock has that. Every
stock has one year momentum, how much they went up in the last year. But those are very common
factors. But we try to get lots and lots of those factors that we have for many, many years,
like 15, 20 years history. And then the setup of the problem is commonly in quant called cross
sectional global equity. You're not really trying to say, I believe the stock will go up.
You're trying to say the relative position of this stock in feature space makes it not a bad
buy in a portfolio. So it captures some period of time and you're trying to find the patterns,
the dynamics, captured by the data of that period of time in order to make short-term
predictions about what's going to happen. Yeah, so our predictions are also not that
short. We're not really caring about things like order books and tick data, not high frequency
at all. We're actually holding things for quite a bit longer. So our prediction time horizon is
about one month. We end up holding stocks for maybe like three or four months. So I kind of
believe that's a little bit more like investing than kind of plumbing. To go long a stock that's
mispriced on one exchange and short on another exchange, that's just arbitrage. But what we're
trying to do is really know something more about the longer term future of the stock.
Yeah. So from the patterns, from these periods of time series data, you're trying to understand
something fundamental about the stock, not about deep value, about as big in the context of the
market as underpriced, overpriced, all that kind of stuff. So this is about investing. It's not about
just like you said, high frequency trading, which I think is a fascinating open question
for a machine learning perspective. But just to build on that, so you've anonymized the data
and now you're giving away the data. And then now anyone can try to build algorithms that
make investing decisions on top of that data or predictions on the top of that data.
Exactly. So what does that look like? What's the goal of that? What are the underlying
principles of that? So the first thing is, we could obviously model that data in-house.
Right? We can make an XGBoost model on the data and that would be quite good too.
But what we're trying to do is by opening it up and letting anybody participate,
we can do quite a lot better than if we modeled it ourselves. And a lot better on the stock market
doesn't need to be very much. Like it really matters the difference between if you can make
10 and 12% in an equity market neutral hedge fund because usually you're charging 2%
fees. So if you can do 2% better, that's all your fees. It's worth it. So we're trying to
make sure that we always have the best possible model. As new machine learning libraries come out,
new techniques come out, they get automatically synthesized. Like if there's a great paper
on supervised learning, someone on Numeri will figure out how to use it on Numeri's data.
And is there an ensemble of models going on or is it more towards one or two or three best
performing models? So the way we decide on how to weight all of the predictions together is
by how much the users are staking on them, how much of the cryptocurrency that they're putting
behind their models. So they're saying, I believe in my model. You can trust me because I'm going to
skin in the game. And so we can take the stake weighted predictions from all our users,
add those together, average those together. And that's a much better model than any one model
in the sum because ensembling a lot of models together is kind of the key thing you need to
do in investing too. Yeah. So you're putting, there's the kind of duality from the user from
the perspective of a machine learning engineer with your, it's both a competition, just a really
interesting, difficult machine learning problem. And it's a way to invest algorithmically.
But the way to invest algorithmically also is a way to put skin in the game that communicates to
you that you're the quality of the algorithm and also forces you to really be serious about the
models that you build. So it's like everything just works nicely together. Like, I guess one
way to say that is the interests are aligned. Exactly. Okay. So it's just like poker is not
fun when it's like for very low stakes, the higher the stakes, the more the dynamics of the system
starts playing out correctly. Like as a small side note, is there something you can say about
which kind, looking at the big broad view of machine learning today or AI, what kind of algorithms
seem to do good in these kinds of competitions at this time? Is there some universal thing you
can say like neural networks suck, recurrent neural networks suck, transformers suck, or they're
awesome, like old school, sort of more basic kind of classifiers are better. Is there some kind of
conclusions so far that you can say? There is. There definitely is something pretty nice about
tree models like XGBoost. And they just seem to work pretty nicely on this type of data. So out
of the box, if you're trying to come a hundredth in the competition or in the tournament, maybe you
would try to use that. But what's particularly interesting about the problem that not many
people understand, if you're familiar with machine learning, this typically will surprise you when
you model our data. So one of the things that you look at in finance is you don't want to be too
exposed to any one risk. Even if the best sector in the world to invest in over the last 10 years
was tech, it does not mean you should put all of your money into tech. So if you train a model,
it would say put all your money into tech. It's super good. But what you want to do is actually
be very careful of how much of this exposure you have to certain features. So on Numeri, what a lot
of people figure out is actually if you train a model on this kind of data, you want to somehow
neutralize or minimize your exposure to certain features, which is unusual because if you did
train a stop light or stop street detection on computer vision, your favorite feature,
let's say you have an auto encoder and it's figuring out, okay, it's got to be red and it's
got to be white, that's the last thing you want to reduce your exposure to. Why would you reduce
your exposure to the thing that's helping you model the most? And that's actually this counter
intuitive thing you have to do with machine learning on financial data. So reducing your
exposure would help you generalize the things that are, so basically financial data has a large
amount of patterns that appeared in the past and also a large amount of patterns that have not
appeared in the past. And so in that sense, you have to reduce the exposure to red lights,
to the color red. That's interesting, but how much of this is art and how much of it is science
from your perspective so far in terms of as you start to climb from the hundredth position to
the 95th in the competition? Yeah, well, if you do make yourself super exposed to one or two features,
you can have a lot of volatility when you're playing numerite. You could maybe very rapidly
rise to be high if you were getting lucky. Yes. And that's bit like the stock market. Sure. Take
on massive risk exposure, put all your money into one stock and you might make 100%, but it doesn't
in the long run work out very well. And so the best users are trying to stay high for as long as
possible and not necessarily try to be first for a little bit. So to me, a developer, machine
learning researcher, how do I, Lex Friedman participate in this competition and how do others,
which I'm sure there'll be a lot of others interested in participating in this competition,
what are, let's see, there's like a million questions, but like first one is how do I get started?
Well, you can go to numer.ai, sign up, download the data. And on the data is pretty small. In the
data pack you download, there's like an example script, Python script, that just builds a XGBoost
model very quickly from the data. And so in a very short time, you can have an example model.
Is that a particular structure? Like what, is this model then submitted somewhere? So there's,
there needs to be some kind of structure that communicates with some kind of API. Like how
does the whole, how does your model, once you build the ones that create a little baby Frankenstein,
how does it then live in it? We want you to keep your baby Frankenstein at home and take care of
it. We don't want it. Okay. So we, you never upload your model to us. You always only giving us
predictions. So we never see the code that wrote your model, which is pretty cool that our whole
hedge fund is built from models where we've never ever seen the code. But it's important for the
users because it's their IP, why they want to give it to us. That's brilliant. So they've got it
themselves, but they can basically almost like license the, the predictions from that part of
it. So what some users do is they set up a compute server and we call numeric compute,
it's like a little AWS kind of image. And you can automate this process. So we can ping you,
we can be like, we need more predictions now, and then you send it to us.
Okay, cool. So that's, is that described somewhere, like what the preferred is the AWS or
whether another cloud platform, is there, I mean, is there sort of specific technical
things you want to say that comes to mind that is a good path for getting started. So download
the data, maybe play around, see if you can modify the basic algorithm provided in the example. And
then you would set up a little server on the AWS that then runs this model and takes pings and then
makes predictions. And how does your own money actually come into play doing the stake of cryptocurrency?
Yeah, so you don't have to stake. You can start without staking. And many users might try for
months without staking anything at all to see if their model works on the real life data, right?
And is not overfit. But then you can get numerair many different ways. You can buy it on,
you can buy some on Coinbase, you can buy some on Uniswap, you can buy some on Binance.
So what did you say? This is, how do you pronounce it? So this is the Numeri cryptocurrency.
Yeah, NMR. NMR. What's, you just say NMR?
It is technically called Numerair. Numerair? I like it.
Yeah, but NMR is simple. NMR, Numerair. Okay. So, and you could buy it,
you know, basically anywhere. Yeah. So it's a bit strange because sometimes
people were like, is this like pay-to-play? Right. And it's like, yeah, you need to put
some money down to show us you believe in your model. But weirdly, we're not selling you the,
like you can't buy the cryptocurrency from us. It's like, it's also, we never, if you do badly,
we destroy your cryptocurrency. Okay, that's not good, right? You don't want it to be destroyed.
But what's good about it is it's also not coming to us. Right. So it's not like we win when you
lose or something like, like we're the house, like we're definitely on the same team. Yes.
You're helping us make a hedge fund that's never been done before.
Yes. So again, interests are aligned. There's no, there's no tension there at all, which is
really fascinating. You're giving away everything and then the IP is owned by the sort of the
code. You never share the code. That's fascinating. So since I have you here, and you said a hundredth,
I didn't ask out of how many. So we'll just, but if I, if I then once you get started and you find
this interesting, how do you then win or do well, but also how do you potentially try to win if
this is something you want to take on seriously from the machine learning perspective, not from
a financial perspective? Yeah. I think the first of all, you want to talk to the community. People
are pretty open. We give out really interesting scripts and ideas for things you might want to
try. And, but you're also going to need a lot of compute probably. And so some of the best users
are, are, you know, actually the very first time someone won on Numeri, I would, I wrote them a
personal email. It's like, you know, you've won some money. We're so excited to give you $300. And
then they said, I spend way more on the compute. So this is fundamentally machine learning problem
first, I think, is this is one of the exciting things. I don't know if we'll, in how many ways
we can approach this, but really this is less about kind of no offense, but like finance people,
finance minded people, they're also, I'm sure, great people. But it feels like from the community
that I've experienced, these are people who see finance as a fascinating problem space,
a source of data, but ultimately they're machine learning people or AI people, which is a very
different kind of flavor of community. And I mean, I should say to that, I'd love to participate in
this and I will participate in this. And I'd love to hear from other people, if you're listening
to this, if you're a machine learning person, you should participate in it and tell me, give me
some hints how I can do all of this thing. Because this boomer, I'm not sure I still got it, but
because some of it is, it's like Kaggle competitions, like some of it is certainly set
ideas, like research ideas, like fundamental innovation. But I'm sure some of it is like
deeply understanding, getting like an intuition about the data. And then like a lot of it will
be like figuring out like what works, like tricks. I mean, you could argue most of deep
learning research is just tricks on top of tricks. But there's, some of it is just the
art of getting to know how to work on a really difficult machine learning problem.
And I think what's important, the important difference with something like a Kaggle competition,
where they'll set up this kind of toy problem, and then they will be out of sample tests like,
hey, you did well out of sample. And this is like, okay, cool. But what's cool with Nimera is
the out of sample is the real life stock market. We don't even know. We don't know the answer to
the problem. We don't like, you'll have to find out live. And so we've had users who've submitted
every week for like four years. Because it's kind of an interest, we say it's the hardest
data science problem on the planet, right? And it sounds maybe sounds like maybe
bit too much for like a marketing thing, but it's the hardest because it's the stock market.
It's like literally there are like billions of dollars at stake. And like no one's like letting
it be inefficient on purpose. So if you can find something that works on Nimera, you really have
something that that is like working on the real stock market. Yeah, because there's like humans
involved in the stock market. I mean, it's, you know, you could argue that might be harder data
sets that may be predicting the weather, all those kinds of things. But the fundamental statement
here is, which I like, I was thinking like, is this really the hardest data science problem?
You start thinking about that. But ultimately, it also boils down to a problem where the data is
accessible. It's made accessible made really easy and efficient at like submitting algorithms. So
it's not just, you know, it's not about the data being out there, like the weather, it's about
making the data super accessible, making the ability to community around it. Like, this is
what ImageNet did. Exactly. Like, it's not just there's always images. The point is, you aggregate
them together, you give it a little title, there's a community and that that was one of the hardest,
right, for a time. And most important data science problems in the world. Because it was
accessible because it was made sort of like, there was mechanisms by which like standards and
mechanisms by which to judge your performance, all those kinds of things. And numerize, I actually
just step up from that. Is there something more you can say about why from your perspective,
it's the hardest problem in the world? I mean, you said it's connected to the market. So if you
can find a pattern in the market, that's a really difficult thing to do because a lot of people
are trying to do it. Exactly. But there's also the biggest one is it's non-stationary time series.
We've tried to regularize the data so you can find patterns by doing certain things to the
features and the target. But ultimately, you're in a space where you don't, there's no guarantees
that the out-of-sample distributions will conform to any of the training data. And every single
era, which we call on the website, like every single era in the data, which is like sort of
showing you the order of the time, it's even the training data has the same dislocations.
And then there's so many things that you might want to try. There's unlimited possible number
of models, right? And so by having it be open, we can at least search that space.
It's zooming back out to the philosophical. You said that Numeri is very much like Wall Street
pets. I think it'd be interesting to dig in why you think so. I think you're speaking to the
distributed nature of the two and the power of the people nature of the two. So maybe can you
speak to the similarities and the differences in which ways Numeri more powerful, in which way
is Wall Street Bets more powerful? Yeah, this is why the Wall Street Bets story is so interesting
to me because it feels connected. And looking at the forum of Wall Street Bets, I was talking
earlier about how can you make credible claims? You're anonymous. Okay, well, maybe you can take
a screenshot. Or maybe you can upvote someone. Maybe you can have karma on Reddit. And those
kinds of things make this emerging thing possible. Numeri, it didn't work at all when we started.
It didn't work at all. Why? People made multiple accounts. They made really random models and
hoped they would get lucky. And some of them did. Staking was our solution to could we make it so
that we could trust, we could know which model people believed in the most. And we could weight
models that had high stake more and effectively coordinate this group of people to be like,
well, actually, there's no incentive to creating bot accounts anymore. Either I stake my accounts,
in which case I should believe in them because I could lose my stake, or I don't. And that's a very
powerful thing that having a negative incentive and a positive incentive can make things a lot
better. And staking is this really nice key thing about blockchain. It's something special
you can do where they're not even trusting us with their stake in some ways. They're trusting the
blockchain, right? So the incentives, like you say, it's about making these perfect incentives
so that you can have coordination to solve one problem. And nowadays, I sleep easy,
because I have less money in my own hedge fund than our users are staking on their models.
That's powerful. In some sense, from a human psychology perspective, it's fascinating that
Wall Street Bets worked at all, right? Amidst that chaos, emerging behavior,
like behavior that made sense emerged, it would be fascinating to think if
numerized style staking could then be transferred to places like Reddit. And not necessarily for
financial investments, but I wish sometimes people would have to stake something in the
comments they make on the internet. That's the problem with anonymity, is like anonymity is
freedom and power that you don't have to, you can speak your mind, but it's too easy to just be shitty.
Exactly. And so this, I mean, you're making me realize from like a profoundly philosophical
aspect, numerized staking is a really clean way to solve this problem. It's a really beautiful
way. Of course, it only with numerized currently works for a very particular problem, right?
Not for human interaction on the internet, but that's fascinating.
Yeah, there's nothing for to stop people. In fact, we've open sourced like the code we use
for staking in a protocol, we call erasure. And any, if Reddit wanted to, they could even use
that code to have enabled staking on our Wall Street Bets. And they're actually researching
now, they've had some Ethereum grants on how could they have more crypto stuff in there in
Ethereum, because wouldn't that be interesting? Like imagine you could, instead of seeing a
screenshot, like guys, I promise, I will not sell my GameStop. We're just going to go huge.
We're not going to sell at all. And here is a smart contract, which no one in the world,
including me, can undo. That says my, I have staked millions against this claim.
That's powerful. And then what could you do? And of course, it doesn't have to be millions.
It could be just very small amount, but then just a huge number of users doing that kind of stake.
Exactly. That, you know, that could change the internet.
It would change, and the man Wall Street, they would not, they would never have been able to,
they would still be short squeezing one day after the next, every single hedge fund collapsing.
If we look into the future, do you think it's possible that Numeri style infrastructure,
where AI systems backed by humans are doing the trading is what the entirety of the stock
market is, or the entirety of the economy is run by basically this army of AI systems with
high level human supervision? Yeah. The thing is that some of them could be,
could be bad actors. Some of the humans? No. Well, these systems could be tricky.
So actually, I once met a hedge fund manager, and this is kind of interesting. He said,
very famous one. And he said, we can see, sometimes we can see things in the market where we know
we can make money, but it will mesh it up. Yeah. We know we can make money, but it will
mess things up. And we choose not to do those things. And on the one hand, maybe this is like,
oh, you're being super arrogant. Of course, you can't do this, but maybe he can. And maybe he
really isn't doing things he knows he could do, but would change, be pretty bad. Would the Reddit
army have that kind of morality or concern for what they're doing? Probably not, based on what
we've seen. The madness of crowds. There'll be one person that says, hey, maybe, and then they
get trampled over. That's the terrifying thing, actually. A lot of people have written about
this is somehow that little voice that's human morality gets silenced when we get into groups
and start chanting. Yeah. And that's terrifying. But I think maybe I misunderstood. I thought that
you're saying AI systems can be dangerous, but you just describe how humans can be dangerous,
so which is safer. So I mean, one thing is,
Numeri, yeah, so Wall Street bets, these kinds of attacks, it's not possible to model
numerized data and then come up with the idea from the model, let's short-screen this game
stop. It's not even framed in that way. It's not possible to have that idea. But it is possible
for a bunch of humans. Numeri could get very powerful without it being dangerous,
but Wall Street bets needs to get a little bit more powerful and it'll be pretty dangerous.
Yeah. Well, I mean, this is a good place to kind of think about numerized data today,
and numerized signals, and what that looks like in 10, 20, 30, 50, 100 years. Right now,
I guess, maybe you can correct me, but the data that we're working with is like a window.
It's an anonymized, obfuscated window into a particular aspect, a time period of the market.
And you can expand that more and more and more and more potentially. You can imagine in different
dimensions to where it encapsulates all the things where you could include kind of human-to-human
communication that was available to buy a game stop, for example, on Wall Street bets.
So maybe to step back, can you speak to what is numerized signals and what are the different
data sets that are involved? So with numerized signals, you're still providing predictions to us,
but you can do it from your own data sets. So numerized all, you have to model our data to
come up with predictions. Numerized signals is whatever data you can find out there,
you can turn it into a signal and give it to us. So it's a way for us to import
signals on data we don't yet have. And that's why it's particularly valuable because
it's going to be signals, you're only rewarded for signals that are orthogonal to our core signal.
So you have to be doing something uncorrelated. And so strange alternative data tends to have
that property. There isn't too many other signals that are correlated with
what's happening on Wall Street bets. That's not going to be correlated with the price to
earnings ratio. And we have some users as of recently, as of a week ago, there was a user
that created, I think he's in India, he created a signal that is scraped from Wall Street bets.
And now we have that signal as one of our signals in thousands that we use at Numeri.
And the structure of the signal is similar. So is it just numbers and time series data?
It's exactly. And it's just like, you're providing a ranking of stocks. So you just say,
give a one means you like the stock, zero means you don't like the stock,
and you provide that for the 5,000 stocks in the world.
And they somehow converted the natural language that's in the Wall Street bet.
Exactly. So they've come, exactly. So they made, they open sourced this collab notebook.
You can go and see it and look at it. And so yeah, it's taking that making a sentiment score
and then turning it into a ranking. Sentiment score. Yeah.
Like this stock sucks, or this stock is awesome. And then converting that's fast,
just even looking at that data would be fascinating. So on the signal side, what's the vision?
What's the long term? What do you see that becoming?
So we want to manage all the money in the world. That's Numeri's mission.
And to get that, we need to have all the data and have all of the talent.
Like there's no way for the first principles, if you had really good modeling
and really good data that you would lose, right?
It's just a question of how much do you need to get, to get really good.
So Numeri already has some really nice data that we give out this year.
We are 10xing that. And I actually think we'll 10x the amount of data we have on Numeri
every year for at least the next 10 years. Wow.
So it's going to get very big, the data we give out and signals is more data.
People with any other random data set can turn that into a signal and give it to us.
And in some sense, that kind of data is the edge cases, the weirdness is the,
so you're focused on like the bulk, like the main data.
And then there's just like weirdness from all over the place that just can enter
through this back door of the process. Exactly.
And it's also a little bit shorter term.
So the signals are about a seven day time horizon and on Numeri, it's like a 30 day.
So it's often for faster situations.
You've written about a master plan and you've mentioned, which I love,
in a similar sort of style of big style thinking, you would like Numeri to manage
all of the world's money.
So how do we get there from yesterday to several years from now?
Like what is the plan?
You've already started to allure to it.
It's like get all the data and get all the talent, humans, models.
Exactly. I mean, the important thing to note there is what would that mean, right?
And I think the biggest thing it means is like, if there was one hedge fund,
you would have not so much talent wasted on all the other hedge funds.
Like it's super weird how the industry works.
It's like one hedge fund gets a data source and hires a PhD.
And another hedge fund has to buy the same data source and hire a PhD.
And suddenly a third of American PhDs are working at hedge funds.
And we're not even on Mars.
And like, so in some ways Numeri, it's all about freeing up people who work at hedge funds to
go work for Elon.
Yeah. And also the people who are working on Numeri problem,
it feels like a lot of the knowledge there is also transferable to other domains.
Exactly. One of our top users is, he works at NASA Jet Propulsion Lab.
And he's like amazing. I went to go visit him there.
And it's like, he's got like Numeri posters and it's like, it looks like,
you know, the movies, like it looks like Apollo 11 or whatever.
Yeah. The point is, he didn't quit his job to join full time.
He's working on getting us to Jupiter's moon.
That's his mission, the Europa Clipper mission.
Actually, literally what you're saying.
Literally. He's smart enough that we really want his intelligence to reach the stock market.
Because stock market's a good thing, hedge funds are a good thing.
Our kinds of hedge funds, especially.
But we don't want him to quit his job.
So he can just do Numeri on the weekends.
And that's what he does.
He just made a model and it just automatically submits to us.
And he's like one of our best users.
You mentioned briefly that stock markets are good.
For my sort of outsider perspective, is there a sense, do you think trading stocks
is closer to gambling or is it closer to investing?
Sometimes it feels like it's gambling as opposed to betting on companies to succeed.
And this is maybe connected to our discussion of shorting in general.
But from your sense, the way you think about it, is it fundamentally still investing?
I do think, I mean, it's a good question.
I've also seen lately, people say, this is like speculation.
Is there too much speculation in the market?
And it's like, but all the trades are speculative.
Like all the trades have a horizon.
Like people want them to work.
So I would say that there's certainly a lot of aspects of gambling math
that applies to investing.
Like one thing you don't do in gambling is put all your money in one bet.
You have bankroll management, and it's a key part of it.
And small alterations to your bankroll management might be better than improvements to your skill.
And then there are things we care about in our fund.
Like we want to make a lot of independent bets.
We talk about it.
We want to make a lot of independent bets because that's going to be a higher sharp
than if you have a lot of bets that depend on each other, like all in one sector.
The point is that you want the prices of the stocks to be reflective of their value.
Of the underlying value of the company.
Yeah, you shouldn't have there be a hedge fund that's able to say, well,
well, I've looked at some data and all of this stuff is super mispriced.
That's super bad for society if it looks like that to someone.
I guess the underlying question then is, do you see that the market often drifts away from
the underlying value of companies and it becomes a game in itself?
Would these derivatives options and shorting and all that kind of stuff,
it's like layers of game on top of the actual what you said, which is the basic thing that
the Wall Street Bets was doing, which is just buying stocks?
Yeah, there are a lot of games that people play that are in the derivatives market.
And I think a lot of the stuff people dislike when they look at the history of what's happened,
they hate credit default swaps or collateralized debt obligations.
Like these are the enemies of 2008.
And then the long-term capital management thing, it was like that 30 times leverage
or something just, no one, you could just go to a gas station and ask anybody at the gas station,
is it a good idea to have 30 times leverage?
And they just say, no.
It's a common sense just like went out the window.
I don't respect long-term capital management.
But Numerain doesn't actually use any derivatives unless you call shorting derivative.
We do put money into companies.
That does help the companies we're investing in.
It's just in little ways.
We really did buy Tesla and we played some role in its success.
Super small, make no mistake.
But still, I think that's important.
Can I ask you a podhead question, which is, what is money, man?
So if we just zoom out and look at, let's talk to you about cryptocurrency,
which perhaps could be the future of money.
In general, how do you think about money?
You said Numerain, the vision, the goal is to run, to manage the world's money.
What is money in your view?
I don't have a good answer to that.
But it's definitely in my personal life, it's become more and more warped.
And you start to care about the real thing, what's really going on here.
Elon talks about things like this, what is the company?
Really, it's a bunch of people who show up to work together and solve a problem.
And there might not be a stock out there that's trading that represents what they're doing,
but it's not the real thing.
And being involved in crypto, I put in a crowd sale of Ethereum
and all these other things and different crypto hedge funds and things that I've invested in.
And it's just kind of like, it feels like how I used to think about money stuff is just totally warped.
Because you stop caring about the price and you care about the product.
But the product, you mean the different mechanisms that money has exchanged?
Money is ultimately a store of wealth, but it's also a mechanism of exchanging wealth.
But what wealth means becomes a totally different thing,
especially with cryptocurrency, where it's almost like these little contracts,
these little agreements, these transactions between human beings that represent something
that's bigger than just cash being exchanged at 7-Eleven, it feels like.
Yeah, maybe I'll answer what is finance.
It's what are you doing when you have the ability to take out a loan?
You can bring a whole new future into being with finance.
If you couldn't get a student loan to get a college degree, you couldn't get a college degree,
like if you didn't have the money.
But now, weirdly, you can get it with and like, yeah, all you have is this loan,
which is like, so now you can bring a different future into the world.
And that's how when I was saying earlier about if you rerun American history,
economic history without these things, like you're not allowed to take out loans,
you're not allowed to have derivatives, you're not allowed to have money,
it just doesn't really work.
And it's a really magic thing, how much you can do with finance by kind of bringing the future forward.
Finance is empowering. We sometimes forget this, but yeah, it enables innovation,
it enables big risk takers and bold builders that ultimately make this world better.
You said you were early in on cryptocurrency.
Can you give your high-level overview of just your thoughts about the past,
present, and future of cryptocurrency?
Yeah, so my friends told me about Bitcoin and I was interested in equities a lot.
And I was like, well, it has no net present value. It has no future cash flows.
Bitcoin pays no dividends. So I really couldn't get my head around it like that this could be valuable.
And then I, but I did, so I didn't feel like I was early in cryptocurrency in fact,
because I was like, it was like 2014, it felt like a long time off the Bitcoin.
And then, but then I really liked some of the things that Ethereum was doing.
It seemed like a super visionary thing.
Like I was reading something that was just going to change the world
when I was reading the white paper. And I liked the different constructs
you could have inside of Ethereum that you couldn't have on Bitcoin.
Like smart contracts and all that kind of stuff.
Exactly, yeah. And even spoke about different constructions you could have.
Yeah, that's the cool dance between Bitcoin and Ethereum of it's in the space of ideas.
It feels so young. Like I wonder what cryptocurrencies will look like in the future.
Like if Bitcoin or Ethereum 2.0 or some version will stick around or any of those,
like who's going to win out or if there's even a concept of winning out at all.
Is there a cryptocurrency that you're especially
find interesting that technically financially philosophically you think
is something you're keeping your eye on?
Well, I don't really, I'm not looking to like invest in cryptocurrencies anymore.
But I, they are, I mean, they're, and many are almost identical.
I mean, there's not, there wasn't too much difference between even Ethereum and Bitcoin
in some ways, right? But there are some that I like the privacy ones.
I mean, I was like, I like Zcash for its like coolness. It's actually, it's,
it's like a different kind of invention compared to some of the other things.
Okay. Can you speak to just briefly to privacy? What is there some mechanism of preserving some
privacy of the, so I guess everything is public. Is that the problem?
Yeah, none of the transactions are private. And so, you know, even like I have some of my,
I have some numeraire and you can just see it. In fact, you can go to a website and says like,
you can go to like Etherscan and it'll say like, numeraifounder. And I'm like,
how the hell do you guys know this? So they can reverse engine and then,
you know, whatever that's called. Yeah. And so they can see me move it too.
They can see me. Oh, why is he moving it? Yeah. So, so, but yeah, Zcash,
they also, when you can make private transactions, you can also play different games.
Yes. And it's unclear. It's like, what's quite cool about Zcash is I wonder what
games are being played there. No one will know. So, from a deeply analytical perspective,
can you describe why Dogecoin is going to win? Which it surely will. Like it very likely will
take over the world. And once we expand out into the universe, it will take over the universe.
Or on a more serious note, like what are your thoughts on the recent success of Dogecoin,
where you've spoken to sort of the meme stocks, the memetics of the whole thing,
that it feels like the joke can become the reality. Like the meme, the joke has power in
this world. Yeah. It's fascinating. Exactly. It's like, why is it correlated with Elon tweeting
about it? It's not just Elon alone tweeting, right? It's like Elon tweeting and that becomes
a catalyst for everybody on the internet kind of like spreading the joke, right? Exactly.
The joke of it. So, it's the initial spark of the fire for Wall Street Betts type of situation.
Yeah. And that's fascinating because jokes seem to spread faster than other mechanisms.
Like funny shit is very effective at captivating the discourse on the internet.
Yeah. And I think you can have, I like the one meme, like Doge, I haven't heard that name in a
long time. Like, I think back to that meme often. That's like funny. And every time I think back
to it, there's a little probability that I might buy some Dogecoin, right? And so I imagine you
should have millions of people who have had all these great jokes told them and every now and
then they reminisce, oh, that was really funny. And then they're like, let me buy some.
Wouldn't that be interesting if we travel in time, like multiple centuries,
where the entirety of the communication of the human species is like humor? Like,
it's all just jokes. Like, we're high on probably some really advanced drugs.
And we're all just laughing nonstop. It's a weird, like, dystopian future of just humor.
E-Line has made me realize how, like, good it feels to just not take shit seriously every once
in a while and just relieve, like, the pressure of the world. At the same time, the reason I don't
always like when people finish their sentences with lol is, like, that you don't, when you don't
take anything seriously, when everything becomes a joke, then it feels like that way of thinking
feels like it will destroy the world. It's like, I often think it like, well, me and
save the world to destroy because I think both are possible directions.
Yeah, I think this is a big problem. I mean, America, I always felt that about America.
A lot of people are telling jokes kind of all the time. And they're kind of good at it.
And you take someone aside, and American, you're like, I really want to have a sincere
conversation. It's like, hard to even keep a straight face because everything is so,
there's so much levity. So it's complicated. I like how sincere actually, like, your Twitter
can be. You're like, I am in love with the world. Yeah, I get so much shit for it. I'm
never going to stop because I realize, like, you have to be able to sometimes just be real
and be positive and just be, save the cliche things, which ultimately those things actually
capture some fundamental truths about life. But it's a dance. And I think Elon does a good job
of that from an engineering perspective of being able to joke, but everyone's, you know,
mostly to pull back and be like, here's real problems, let's solve them, and so on, and then
be able to jump back to a joke. So it's ultimately, I think, I guess, a skill that we have to learn.
But I guess your advice is to invest everything anyone listening owns into Dogecoin. That's
what I heard from this interaction. Yeah, no, exactly. Yeah. Our hedge fund is unavailable.
Just go straight to Dogecoin. You're running a successful company. It's just interesting because
my mind has been in that space of potentially being one of the millions other entrepreneurs.
What's your advice on how to build a successful startup? How to build a successful company?
I think that one thing I do like, and it might be a particular thing about America, but like,
there is something about like playing, tell people what you really want to happen in the world.
Like, don't stop. It's not, it's not going to make it, like, if you're asking someone to
invest in your company, don't say, I think maybe one day we might make a million dollars.
When you actually believe something else, you actually believe, you're actually more optimistic,
but you're toning down your optimism because you want to appear like low risk. But actually,
it's super high risk if your company becomes mediocre because no one wants to work in a
mediocre company. No one wants to invest in mediocre. So you should play the real game.
And obviously this doesn't apply to all businesses, but if you play a venture-backed startup kind of
game, like play for keeps, play to win, go big. And it's very hard to do that. I've always
feel like, yeah, you can start narrowing your focus because 10 people are telling you,
you got to care about this boring thing that won't matter five years from now.
And you should push back and do the real, play the real game.
It should be bold. So both, I mean, there's an interesting duality there. So there's the way
you speak to other people about like your plans and what you are like privately, just in your own
mind. And maybe it's connected with what you're saying about, yeah, sincerity as well. If you
appear to be sincerely optimistic about something that's big or crazy, it's putting yourself up
to be kind of ridiculed or something. And so if you say, my mission is to go to Mars,
it's just so bonkers that it's hard to say. It is. But one powerful thing, just like you said,
is if you say it and you believe it, then actually amazing people come and work with you.
Exactly. It's not just skill, but the dreams. There's something about optimism that like that
fire that you have when you're optimistic of actually having the hope of building
something totally cool, something totally new, that when those people get in a room together,
like they can actually do it. Yeah. Yeah, there's, yeah, that's, and also makes life really fun
when you're in that room. So all of that together, ultimately, I don't know, that's what makes this
crazy ride of a startup really look fun. And Elon is an example of a person who succeeded at that.
There's not many other inspiring figures, which is sad. I used to be a Google and there's
there's something that happens that sometimes when the company grows bigger and bigger and
bigger, where that kind of ambition kind of quits down a little bit. Yeah. You know,
Google had this ambition still does of making the world's information accessible to everyone.
And I remember, I don't know, that's beautiful. I still love that dream of that, you know,
these to scan books, but just in every way possible make the world's information
accessible. Same with Wikipedia. Every time I open up Wikipedia, I'm just awe inspired by
how awesome humans are, man, and creating this together. I don't know what the meetings are
over there, but they, it's just beautiful. Like what they've created is incredible. And I'd love
to be able to be part of something like that. And you're right. For that, you have to be bold.
And there's, and strange to me also, I think you're right that there's
how many boring companies there are, right? Something I always talk about, especially
in fintech. It's like, why am I excited about this is so lame? Like, what is this isn't even
like important? Even if you succeed, this is going to be like terrible. This is not good.
And it's just strange how people can kind of get fake enthusiastic about like boring ideas.
When there's so many bigger ideas that, yeah, I mean, you read these things like this company
raises money and it's just like, that's a lot of money for the worst idea I've ever heard.
Some ideas are really big. So like, I worked on autonomous vehicles quite a bit. And
there's so many ways in which you can present that idea to yourself, to the team you work with,
to just, yeah, like to yourself when you're quietly looking in the mirror in the morning,
that's really boring or really exciting. Like if you're really ambitious with autonomous vehicles,
there, it changes the nature of like human robot interaction, it's changed the nature of
how we move, forget money, forget all that stuff. It changes like everything about robotics and AI,
machine learning. It changes everything about manufacture. I mean, the cars, the transportation
is so fundamentally connected to cars. And if that changes, it changes the fabric of society,
of movies, of everything. And if you go bold and take risks and go be willing to go bankrupt
with your company, as opposed to cautiously, you could really change the world. And it's
so sad for me to see all these autonomous companies, autonomous vehicle companies,
they're like really more focused about fundraising and kind of like smoke and mirrors,
they're really afraid. The entirety of their marketing is grounded in fear and presenting
enough smoke to where they keep raising funds so they can cautiously use technology of a previous
decade or previous two decades to kind of test vehicles here and there, as opposed to do crazy
things in bold and go huge at scale, do huge data collection. And yeah, so that's just an example.
Like the idea can be big, but if you don't allow yourself to take that idea and think
really big with it, then you're not going to make anything happen. Yeah, you're absolutely right in
that. So you've been connected in your work with a bunch of amazing people. How much interaction
do you have with investors? Like that whole process is an entire mystery to me. Is there
some people that just have influence on the trajectory of your thinking completely? Or is
it just this collective energy that they behind the company? Yeah, I came here and I was amazed
how, yeah, people would, I was only here for a few months and I met some incredible investors
and I'd almost run out of money. And once they invested, I was like,
I am not going to let you down. And I was like, okay, I'm gonna send them like an email update
every like three minutes. And then they don't care at all. So they kind of want to look, I don't
know, like so for some, I like it when it's just like they're always available to talk. But a lot
of building a business, especially a high tech business, there's little for them to add, right?
There's little for them to add on product. There's a lot for them to add on like business
development. And if we are doing product research, which is for us, research into the
market research into how to make a great hedge fund. And we do that for years.
There's not much to tell the investors. So that basically is like, I believe in you,
there's something I like to cut of your jib. There's something in your idea and your ambition
in your plans that I like. And it's almost like a pat on the back. It's like, go get them, kid.
Yeah, it is a bit like that. And that's cool. That's a good way to do it. I'm glad they do it that way.
Like the one and meeting I had, which was like really good with this was
I was meeting Howard Morgan, who's actually a co-founder of Renaissance Technologies in the 1980s
and worked with Jim Simons. And he was in the room and I was meeting some other guy and he was in
the room and I was explaining how quantitative finance works. I was like, so they use mathematical
models and then he was like, yeah, I started Renaissance. I know a bit about this. And then
I was like, oh my God. And then I think he kind of said, well, yeah, he said, well,
because he was working at first round capital as a partner and they kind of said they didn't want
to invest. And then I wrote a blog post describing the idea and I was like, I really think you guys
should invest and then they end up. Oh, interesting. You convinced them. Yeah, because they're like,
we don't really invest in hedge funds. And I was like, you don't see like what I'm doing. This is
something different. This is so a tech company, not a hedge fund, right? Yeah. Numerized billion.
When it caught my eye, there's something special there. So I really do hope you succeed. And
obviously it's a risky thing you're taking on the ambition of it, the size of it. But I do hope
you succeed. You mentioned Jim Simons. He comes up in another world of mine really often on the
he's just a brilliant guy on the mathematics side as a mathematician, but he's also a brilliant
finance hedge fund manager guy. Have you gotten a chance to interact with him at all?
Have you learned anything from him on the math, on the finance, on the philosophy,
life side things? I've played poker with him. It was pretty cool. It was like,
actually in the show, billions, they kind of do a little thing about this poker tournament thing
with all the hedge fund managers. And that's real life thing. And they have a lot of like world
series of bracelet, World Series poker bracelets holders, but it's kind of Jim's thing. And I
met him there. And yeah, it was kind of brief, but I was just like, he's like, oh, how do you,
why are you here? And I was like, oh, Howard sent me, you know, he's like, go play this tournament,
meet some of the other players. And then
Was it Texas Hold'em? Yeah, Texas Hold'em tournament. Yeah.
Do you play poker yourself? Or was it?
Yeah, I do. I mean, it was crazy. On my right was the CEO, who's the current CEO of Renaissance,
Peter Brown. And Peter Mueller, who's a hedge fund manager at PDT. And yeah, I mean, it was just
like, and then, you know, just everyone and then all these brace world series, like people I know
from like TV. And Robert Mercer, who's fucking crazy. He's the guy who donated the most money to
Trump. And he's just like, it's a lot of personality character. Yeah, geez, he's crazy.
So it's quite cool how yeah, like the, it was really fun. And then I managed to knock out Peter
Mueller. I have a, I got a little trophy for knocking him out because he was a previous champion. In
fact, I think he's won the most. I think he's won three times. Super smart guy. But I will say Jim
outlasted me in the tournament. And they're all extremely good at poker. But they're also,
so it was a $10,000 buy-in. And I was like, this is kind of expensive. But it all goes to charity,
Jim's math charity. But then the way they play, they have like rebies. And like,
they all do a shit ton of rebies for charity. Yeah. So immediately they're like going all in.
And I'm like, man, like, so I end up, you know, adding more as well. So you couldn't play at
all without doing math. Yeah, the stakes are high. But you're connected to a lot of these folks.
They're kind of titans of just economics and tech in general. Do you feel a burden from this?
You're a young guy. I did feel a bit out of place there. Like, the company was quite new. And
they also don't speak about things, right? So it's not like going to meet a famous
rocket engineer who will tell you how to make a rocket. They do not want to tell you anything
about how to make a hedge fund. It's like all secretive. And that part I didn't like.
And they were also kind of making fun of me a little bit. Like they would say,
like they'd called me like, I don't know, the Bitcoin kid or, and then they would say, even
things like, remember Peter, yeah, said to me something like, I don't think AI is going to have
a big role in finance. And I was like, hearing this from the CEO of Renaissance was like weird
to hear because I was like, of course it will. And he's like, but he can see, I can see it having
a really big impact on things like self-driving cars. But finance, it's too noisy and whatever.
And so I don't think it's like the perfect application. And I was like, that was interesting
to hear because it's like, and I think it was that same day that Libra, I think it is,
the poker playing AI started to beat like the human. So it's kind of funny hearing them like
say, oh, I'm not sure AI could ever get attacked that problem. And then that very day is attacking
the problem of the game we're playing. Well, there's a kind of a magic magic to
somebody who's exceptionally successful looking at you, giving you respect, but also saying that
what you're doing is not going to succeed. In a sense, like they're not really saying it.
But I tend to believe for my interactions with people that it's a kind of prod to say,
like, prove me wrong. Yeah. That's ultimately that's that's how those guys talk. They see good
talent and they're like, yeah. And I think they're also saying it's not going to succeed
quickly in some way. They're like, this is going to take a long time. And maybe,
maybe that's good to know. And certainly AI in in trading, that's one of the most
so philosophically interesting questions about artificial intelligence and the nature of money,
because it's like, how much can you extract in terms of patterns from all of these millions
of humans interacting using this methodology of money? It's like one of the open questions
in the artificial intelligence in that sense, you converting it to a data set is one of like
the biggest gifts to the research community to the whole anyone who loves data science and AI.
This is kind of fascinating. I'd love to see where this goes, actually.
Thing I say sometimes, long before AGI destroys the world, a narrow intelligence will win all
the money in the stock market. Like, way, like just a narrow AI. And I don't know if I'm going
to be the one who invents that. So I'm building numeri to make sure that that narrow AI uses
our data. So you're giving a platform to where millions of people can participate and do build
that narrow AI themselves. People love it when I ask this kind of question about books, about
ideas and philosophers and so on. I was wondering if you had books or ideas,
philosophers, thinkers that had an influence on your life when you were growing up,
or just today that you would recommend that people check out blog posts,
podcasts, videos, all that kind of stuff. Is there something that just kind of had an impact on you
that you can't recommend? A super kind of obvious one that I really was reading zero to one
while coming up with numeri. I was like halfway through the book. And I really do like a lot
of the ideas there. And it's also about kind of thinking big. And also, it's like peculiar
little book. It's like, why, like there's a little picture of the hipster versus unabomber.
And it's a weird little book. So I like, there's kind of like some depth there.
Turns out a book on a, if you're thinking of doing a startup, that's a good book.
A book I like a lot is maybe my favorite book is David Deutsch's beginning of infinity. I just
found that so optimistic. It puts you, everything you read in science, it like makes the world
feel like kind of colder. Because like, it's like, you know, we're just, just coming from evolution
and coming from nothing has, nothing should be this way or whatever. And humans are not very
powerful. We're just like scum on the earth. And the way David Deutsch sees things and argues,
he argues them with the same rigor that the cynics often use, and then has a much better
conclusion. That's, you know, some of the statements are things like, you know,
anything that doesn't violate the laws of physics can be solved. Like.
So ultimately arriving on a hopeful, like a hopeful path forward.
Without being like a hippie. You've mentioned kind of advice for startups. Is there,
in general, whether you do a startup or not, do you have advice for young people today?
You're like an example of somebody who's paved their own path and were, I would say,
exceptionally successful. Is there advice, somebody who's like 20 today, 18, undergrad,
or thinking about going to college or in college and so on, that you would give them?
I think I often tell young people, don't start companies. Don't start a company unless you're
prepared to make it your life's work. Like that's a really good way of putting it. And a lot of
people think, well, you know, this semester, I'm going to take a semester off and in that one
semester, I'm going to start a company and sell it or whatever. And it's just like,
what are you talking about? It doesn't really work that way. You should be like super into the idea,
so into it that you want to spend a really long time on it.
Is that more about psychology or actual time allocation? Like is it literally
the fact that you need to give 100% for potentially years for it to succeed?
Or is it more about just the mindset that's required?
Yeah, I mean, I think, well, I think, yeah, you certainly don't want to have a plan to sell the
company quickly or something. Or it's like a company that has a very, it's like a big fashion
component. Like it'll only work now. It's like an app for something. So yeah, that's a big one.
And then I also think something I thought about recently is I had a job as a quant at a fund
for about two and a half years. And part of me thinks if I had spent another two years there,
I would have learned a lot more and had even more knowledge to be where numer, to basically
accelerate how long numer I took. So the idea that you can sit in an air conditioned room
and get free food or even sit at home now in your underwear and make a huge amount of money and
learn whatever you want and get, it's just crazy. It's such a good deal.
Yeah. Oh, that's interesting. That's the case for, I was terrified of that. Like a Google,
I thought I would become really comfortable in that air conditioned room. And that I was afraid
of the quant situation is, I mean, what you present is really brilliant that it's exceptionally
valuable, the lessons you learn because you get to get paid while you learn from others. If you see
that, if you see jobs in the space of your passion that way, that it's just an education.
It's like the best kind of education. But of course, you have, from my perspective,
you have to be really careful on that to get comfortable. Again, in a relationship, then you
buy a house or whatever the hell it is. And then you get, you know, and then you convince yourself
like, well, I have to pay these fees for the car for the house, blah, blah, blah. And then,
and there's momentum and all of a sudden you're in your deathbed and there's grandchildren.
And you're drinking whiskey and complaining about kids these days. So I, you know, that,
I'm afraid of that momentum, but you're right. Like, there's something special about the education
you get working at these companies. Yeah. And I remember on my desk, I had the,
like a bunch of papers on quant finance, a bunch of papers on optimization. And then the
paper on, on Ethereum, just on my desk as well, and the white paper. And it's like, it's amazing
how much, how kind of, and you can learn about, so that, I also thought, I think this like idea
of like learning about intersections of things. I don't think there are too many people that know
like as much about crypto and quant finance and machine learning as I do. And that's a really
nice set of three things to know stuff about. And that was because I had like free time in my job.
Okay. Let me ask the perfectly impractical, but the most important question. What's the meaning
of all the things you're trying to do so many amazing things? Why? What's the meaning of this
life of yours? Or ours? I don't know. Humans. Yeah. So I have yet had people say asking what
meaning of life is, is like asking the wrong question or something. The question is wrong.
Yeah. No, usually people get too nervous to be able to say that because it's like your question
sucks. I don't think there's an answer. It's like the searching for it. It's like sometimes asking
it. It's like sometimes sitting back and looking up at the stars and being like, huh, I wonder if
there's aliens up there. There's a useful like a palette cleanser aspect to it because it kind of
wakes you up to like all the little busy, hurried day to day activities, all the meetings, all the
things you'd like a part of. We're just like ants, a part of a system, a part of another system. And
then when this asking this bigger question allows you to kind of zoom out and think about it, but
there's ultimately, I think it's an impossible thing for a limited capacity, like cognitive
capacity to capture. But it's fun to listen to somebody who's exceptionally successful, exceptionally
busy now, who's also young like you to ask these kinds of questions about like death,
you know, do you consider your own mortality kind of thing and life, whether that enters your mind
because it kind of almost gets in the way? Yeah. It's amazing how many things you can
like that are trivial that could occupy a lot of your mind until something bad happens or
something flips you. And then you start thinking about the people you love that in your life.
Then you started thinking about like, holy shit, this right ends. Exactly. Yeah. I just had COVID
and I had it quite bad. It wasn't, what wasn't really bad is just like, I also got a simultaneous
like lung infection. So I had like almost like bronchitis or whatever. I don't even, I don't
understand that stuff, but I started and then you're forced to be isolated. Right. And so it's
actually kind of nice because it's very depressing. And then I've heard stories of, I think it's
Sean Parker, he had like all these diseases as a child and he had to like just stay in bed for years
and then he like made Napster. It's like pretty cool. So yeah, I had about 15 days of this recently,
just last month and it feels like it did shock me into a new kind of energy and ambition.
Were there moments when you were just like terrified at the combination of loneliness?
And like, the thing about COVID is like, there's some degree of uncertainty. It feels like it's
a new thing, a new monster that's arrived on this earth. And so dealing with it alone,
a lot of people are dying. It's like wondering like... Yeah, you do wonder. I mean, for sure.
And then there are even new strains in South Africa, which is where I was. And maybe the
new strain had some interaction with my genes and I'm just going to die. But ultimately it was
liberating somehow. I loved it. Oh, I loved that I got out of it. Because it also affects your mind,
you get confusion and kind of a lot of fatigue and you can't do your usual tricks of psyching
yourself out of it. So you know, sometimes it's like, oh man, I feel tired. Okay, I'm just going
to go have coffee and then I'll be fine. It's like, now it's like, I feel tired. I don't even want to
get out of bed to get coffee because I feel so tired. And then you have to confront, there's no
like quick fix cure and you're trapped at home. So now you have this little thing that happened
to you that was reminded that you're mortal and you get to carry that flag in trying to
create something special in this world, right? When you're Mariah. Listen, this was like one of
my favorite conversations because you're the way you think about this world of money and just
this world in general is so clear and you're able to explain it so eloquently. Richard,
it was really fun. Really appreciate you talking to it. Thank you. Thank you. Thanks for listening
to this conversation with Richard Crabe and thank you to our sponsors, Audible Audio Books,
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And now let me leave you with some words from Warren Buffett. Games are won by players who
focus on the playing field, not by those whose eyes are glued to the scoreboard. Thank you for
listening and hope to see you next time.