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- [00:00]
A
Welcome to Pablo Torre Finds out. I am Pablo Torre and today we're going to find out what this sound is. This will now be interpreted and has been interpreted for reasons that again are predictable and understandable. Fundamentally as a, a broad mandate, it's a narrow mandate. Right after this ad. You're listening to Giraffe Kings. Are you a caffeine person?
- [00:37]
B
Media? I'm trying. Not as bad as I used to be, but like, yeah, I mean I'm in the post election haze. It takes a little extra energy these days.
- [00:45]
A
How, how, how fun is the haze?
- [00:47]
B
It's not fun really because you're on this high, right? You're on this kick for like just really grinding and working hard and you have a lot of adrenaline and you wake up, you're like, I have a million things to do. And there's these news polls, new new polls that. So you're excited now. I'm like, oh, I can actually like fall back asleep, but I'm in like a hundreds of hours of sleep deficit.
- [01:05]
A
And so, yeah, yeah, I mean this as a compliment and truly I do. I was walking by a spirit Halloween and I was like, Nate Silver, I think can relate to the seasonality of this pop up Halloween store of like at a certain point in the calendar there are lines and there is stress and competition to get in to buy this costume. You are American politics for a certain amount of time. Yeah, that I think you're still, you're still in the halo, the outer glow of it sounds like you have to.
- [01:39]
B
Just own the fact that it is seasonal. And look, if you're going to do the election, then you're going to have your tourist season. Right, the tourist season where you're selling lobster rolls in Maine and in August there's a lot of demand for lobster rolls. And then Labor Day weekend, you're busiest yet and you're aware that your life's going to change and become more relaxed after that. But I'm used to the cyclicality of it.
- [02:03]
A
So this is Nate Silver in something resembling repose. Nate is 46 years old now, which means that he has been publishing and defending his statistical analysis of presidential elections for 16 years at this point. But I happen to be old enough to remember when he was publishing and defending statistical analysis of baseball for places like Baseball Prospectus and Sports Illustrated and ESPN.com I saw one of my articles.
- [02:32]
B
Someone had printed it out and had left it in the bathroom stall. And I'm like, I've really made it now, right? Some article about how good Barry Bonds was, I think, the highest compliment. Yeah, absolutely.
- [02:41]
A
Is to be printed out and taken into a toilet. But Nate wasn't just a Moneyball stat nerd, sort of a writer. Nate saw everything even more specifically in terms of odds, in terms of probability, which is why Nate also became a competitive poker player, which we'll discuss. But his rigorous simulations and nuanced descriptions of the likelihood of events and their expected value, all that stuff, is not what made his election analysis over at FiveThirtyEight so broadly compelling and so insanely popular, even more to the point. And that is despite the fact that his probabilistic way of thinking is now almost categorically embraced, by the way, by the richest people on earth. Now, as you'll see, in fact, I believe that there is a simpler way to describe the business of Nate Silver. I wonder if you object to this characterization, which is that you are fundamentally in the business of being right.
- [03:43]
B
I. I hope I'm in the business of describing probabilistic things. I think I was blessed and cursed in some ways by having this reputation early on. So 2008, you know, 49 of the 50 states we call correctly, and then it's 50 out of 50 in 2012. And, like, it's just basically random, right? There was like, only a 4% chance that would happen. We had Florida in 2012, back before Florida became a super red Desantis. Haven't you know, our final forecast had like, Obama with a 50.05 chance in Florida and he wins it. So therefore you get this reputation. But, like, yeah, because I want to, like, describe the uncertainties in the world. And. And that's a harder message to sell when I give a talk or something. Right? Like, it's literally in my bio, they call it 50 out of 50 states. But, like, it's kind of against my. Against my whole method and brand.
- [04:31]
A
And I've noticed. I've noticed the tension in being the guy who was praised for being in the business of being right and fundamentally buying by the way. You are actively and competitively trying to be right.
- [04:44]
B
I am, yeah.
- [04:45]
A
But also, but also fighting the framework, the box of. Wait a minute, we need to talk about what probability is.
- [04:52]
B
In high school, I did debate team, which if you have seen me on Twitter, you're probably not very surprised.
- [04:57]
A
I have notes about how you use Twitter, Nate, and all of this is adding up.
- [05:02]
B
But yeah, you want to. You want to prove yourself and you want to say, okay, let's actually bet on this. If you're going to, like, talk all this BS or whatever else. And like, and like there's just some intrinsic, some intrinsic part of me just wants to compete.
- [05:16]
A
Yeah. So all of which is to say that you reject the premise of your job being to be right, but your most inner desire is to want to be right.
- [05:28]
B
It's to want to prove people wrong, which is slightly different.
- [05:32]
A
Explain the difference.
- [05:33]
B
Like, if someone else is really wrong about something and I think they have a bad process and they're annoying, then, like, I probably take more pleasure than that from them being right. You know, it's like, it's like if you catch somebody's like, bluff in poker, that's an incredibly satisfying feeling. Right. Catching a bluff in a big pot is more satisfying than making a full house or something and winning big pockets. You didn't like, really have, you know, just the cards went your way. Right. And there's some skill and how you get the money in and things like that. But like, but calling out bull is like my favorite thing to do, basically.
- [06:03]
A
Right.
- [06:03]
B
Which makes people annoyed, which makes me annoy me.
- [06:07]
A
The best and truly the worst possible platform to consume you on 2016 for you was this. It sounds like this, this moment at which you realized I need to do a better job or at the very least devote a lot of time to articulating what this way of thinking is and who actually believes in it. Because 2016, in terms of Nate is in the business of being right, was publicly rough. So where does your forecast have the race right now?
- [06:54]
B
So we show about a three point lead nationally for Clinton and she's about a two to one favorite. The supporters there at Clinton headquarters listening intently as the results come in. Some of the people look almost crestfallen. As we were coming into the day, you had your projection above 70% for Hillary Clinton.
- [07:14]
A
Where is it right now?
- [07:16]
B
I mean, I would look at betting markets which say that Donald Trump is a narrow favorite to win the Electoral College.
- [07:21]
A
CNN can report that Hillary Clinton has called Donald Trump to concede the race. She has called Donald Trump to say that she will not be president. And I'm not sure the exact words, but probably to congratulate President Elect Donald Trump.
- [07:40]
B
I come from a world where literally before I ever made an election forecast, I played poker and built baseball models. Right. So for my kind of gambling mindset, we were long on Trump relative to the consensus. We had Trump with a 29 rounded up to 30 if you want percent chance of winning. And the betting market said 15% and the other models said as little as 1%. So from my point of view, it's like if you were heavy on, like, Leicester City or something the year they were 5,000 to 1 underdogs on the Premiership, then, like, if you were like, oh, they're only 100 to 1 against, like, that would be a good bet and it would be very positive. EV wager, but, you know, it's too mainstream and it's like, kind of not how. It's not how most people think, obviously.
- [08:17]
A
Oh. I mean, even the term EV A plus EV wager, I do want to spell out expected, because this is the key to what 2016 was for you, how you made sense of it, how, in fact it. It was a success according to this framework, while also being the opposite to people who don't speak the language of ev.
- [08:39]
B
Yeah. And expected value. I mean, I'm sure most of the audience knows, but this is the average outcome you would get over the long run, given the randomness and uncertainty. I mean, an election might not literally be random in the sense that, like, a game of craps is, but there are things that are unknowable and are easier to say after the fact. And by the way, some things are nearly random. In 2000, when Al Gore lost by 537 votes or something like that in Florida and there was a. A butterfly ballot in Palm beach county where it was kind of misprinted and people hanging Shannon and hanging chads and, like, basically random. Who won the 2000 election? Some events in this election were kind of random. The fact that, like, an assassin tried to shoot Trump and got Grace's ear, and if he had turned differently, then who knows what would have happened? Maybe a very dark turn in American history. But the point is, everyone acts like the answers are so obvious after the fact. Right? When it's. When it's not always clear. I mean, you know, this year, because it was so close, like I said, this was easier to explain than most years. Expressing things numerically in probabilities is a sign of humility, and people take it as a sign of hubris instead.
- [09:42]
A
Yes, Well, I want to get into that because the key thing you're doing, and I want to translate this to truly the people who don't speak this language fluently at all is you're talking about. Okay, if I'm going to make a bet on Trump winning, given the percentage chance that Nate Silver has outlined for me. Right. There is an upside in impact multiplied by the probability, the percentage chance that it would happen. And what you're saying is prevailing betting.
- [10:06]
B
Markets, you're getting 5 to 1 or 6 to 1 odds to bet on trump. And we thought the real chance is 3 to 1, let's call it or 2 to 1, right? So 3% of the time you win 600 bucks, and then 70 of the time you lose 100 bucks. And like, that's actually a very positive expected value wager. Now, play poker and you're thrilled to get the. The money in when you have the right odds, because over the long run, you're going to win out, right? And like, I know I'm kind of unflappable. I have one home game I play here in New York, and I had a hammer, I had pocket aces, the opponent had pocket kings, and we actually ran the board twice, right? Just a way to, like, hedge your risk and like. And I somehow lose both boards. Like a 1 in 25 chance. This is a fairly big pot. There's a lot of money. And, you know, this time I was playing this month, the guy's like, you're so inflappable. You weren't like, you weren't bothered by that? I'm like, that's because I'm winning money in the long run in that situation, and I. And I can't control the way that the dealer, like, shuffled the cards. I mean, maybe, maybe you don't give as much of a tip.
- [11:04]
A
The reason why people keep on demanding who you got is because they want. They want the answer. They want your prediction. And what you're doing all the time is trying to tell people. That's not what I do, actually. Yeah, you are. You are trying to explain people while also giving them, I guess, some sort of satiation about their curiosity that. Actually, what I'm trying to tell you is that the thing my model made is the answer. Here are the odds we've generated. We've run the simulation a zillion times. And what is so incompatible with maybe this is an American thing, I think it's probably just a human thing, is that that feels like somebody you trying to have his cake and eat it too.
- [11:45]
B
I mean, it's not so literally this election. The last time we ran the model at midnight on election day, we ran 80,000 simulations. And Harris won, I think, 40,012 simulations. So, like, a coin actually lands on heads 50.5% of the time. A coin is a little bit biased toward heads. Heads is heavier. And our simulation was like, more random than a coin flip. So, yes, it's true. On the one hand, I'm not really saying anything, although it's A guard against, think overconfidence on, on both sides. And it's not always that way. I mean, you know, part of what I think made the site very compelling in like 2012 is there was a lot of talk about how Romney's making this comeback and, and Obama's going to lose.
- [12:24]
A
Who could forget the era? Mitt Romney was making a comeback.
- [12:27]
B
Yeah. And like, I'm like, no, actually the electoral college is pretty good. He's a 90% favorite. So like, that's more intuitive for people. But sometimes the answer is we just, we don't know. Right. We don't know. Polling is very challenging these days. Harris had like better periods and worse periods in the polls. I mean, look, all things considered, this was actually a relatively decent election for, for the pollsters.
- [12:48]
A
Yeah.
- [12:49]
B
Like, I mean, you know, people were. If you were not prepared for Trump winning, then you weren't paying attention to. And by the way, before Harris got in the race, I mean, I think Biden would have lost in a, a true landslide. This is kind of a quasi landslide where Trump wins all the swing states, gets a popular vote. Impressive, but like not, he's going to win by one and a half points, not a, not a Reagan style landslide. I think against Biden, you would have had devastation up and down the ballot for Democrats.
- [13:13]
A
Right. But the interpretation even of the result. Right. This is about a one and a half percent chance difference. This is about, what is it, maybe 250,000 votes total across Michigan, Wisconsin, Pennsylvania, like that's the margin. This will now be interpreted and has been interpreted for reasons that again are predictable and understandable, fundamentally as a broad mandate. And to you, it's actually, what, what, what is your characterization of it then?
- [13:37]
B
It's a narrow mandate. I mean, winning the popular vote for the first time as a Republican since 2004, it is impressive. And the way in which Trump won, where you have big gains among Latino voters, among Asian American voters, by the way, technically speaking, I think Trump will get 49.8, 49.9. So he'll be just a hair short of majority. At the same time, if you are going into a room and 49.9% of people are wearing red hats and 48.4 are wearing blue hats and 1.5 are wearing Jill Stein hats or something. Right. You, you wouldn't be immediately obvious kind of whether they're more red hats or blue hats in the room. It's a very close election. But I think it's actually in some ways good for Democrats to lose by a tangible amount where they can't just blame the electoral college and they can't just blame turnout. Right. Where they actually I think, have to think about a new way forward for the party because it was a party that was kind of out of ideas.
- [14:33]
A
You know, I do want to broaden this out though to this way of thinking. Because when I think about why probability is hard to sell, I think it is in part because people are demanding a take and you are giving them a process, they're demanding a result, you are giving them a process for sure. Probability is the art of description more than it is prediction, frankly.
- [14:52]
B
You're trying to create kind of a three dimensional probabilistic landscape that's accurate. Right. But you're not saying kind of which square of that blueprint that you want wind up on in a given election. So this map that we got with Trump winning 312 electoral votes was the single most likely map in our simulations because the outcomes are correlated that if you beat your polls in one state by two or three points, then you tend to beat them in all the similar states. And so like this is like the most prominent point in the landscape, but it's a pretty flat landscape overall. Right. Wide ranging to the horizons of probability. And my job is to like describe this reality that if you simulate the world a hundred thousand times, you'll wind up in. But lo and behold, you know, I'm gonna have what, 20 elections in my lifetime if I live to 80, hopefully a little bit more than that. But yeah, I mean you're not gonna actually ever get to like the long run here. And so, and so it's kind of this. You have to be very Zen about it because you're never gonna. You're kind of, I mean you truly are gambling in some sense with your reputation where like you're not gonna hit the long run. And so you don't get this thing where you get to play 10000 poker hands.
- [15:56]
A
Well, I think there's a very reputation will be and how you actually did at generating the best model. Right. Like it's. You are. It's two different things. It is, here it is. The thing you've wanted is the thing I made. Check it out. And that's not actually what you're being graded on actually. It's whether the thing happened that made your percentage chance as described look like, oh wow, he was right and definitive the entire time while he was also trying to say this is not about being definitive.
- [16:28]
B
Sports fans are more rational by comparison, believe it or not because people recognize, like, the intrinsic randomness of, you know, in baseball, you have a line drive, perfectly hit, barrel right, that just finds the center fielder. Right. Or things like that, or a gust of wind knocks the field goal. I mean, it's just people. People get that a little bit more.
- [16:50]
A
Sometimes a bird flies in the path of Randy Johnson's fastball.
- [16:54]
B
Absolutely. I mean, it is different existentially, right? I mean, in theory, if you. If you. If you knew every American were able to, like, interview them honestly, then I guess you would have some deterministic aspect to it. But we don't have that luxury. Polling. I mean, it's amazing to me that polling isn't worse, actually. Like, almost somebody responds to polls, and yet somehow they kind of get sort of, kind of close. And like that, to me, is, you know, an underrated feat.
- [17:39]
A
But the other reason I wanted Nate in studio with me today is because I finally read the new book that he wrote this year titled on the Edge, which turns out to be an almost ethnographic study of the worldview to which he himself subscribes. And now that that worldview is eating the world, basically, which is also why it's crazy that we do not understand it better. I want to make the point here that sports and music and entertainment and most everything basically is downstream of this particular type of culture, which might be why Nate calls this group the River.
- [18:16]
B
The river is the world of, like, deeply skilled, analytical, degenerate gamblers, basically, which happens to be a skill set that is very rewarded in Silicon Valley, in Wall Street. And of course, if you are actually kind of a proper G gambler, like a poker player, it's people that are the cross between being very analytical and the important part, also very, very competitive.
- [18:36]
A
And in Nate's ethnography, the river exists in conflict with another group, a group that embodies the old school institution full of social norms. And Nate, a former employee of the New York Times, calls this the Village.
- [18:51]
B
The Village is the east coast, progressive, educated, expert class establishment. So it's like the New York Times and Harvard when there's a Democrat in the White House. It's the kind of all the non profits and all the different branches of the government and things like that, as opposed to the river, which is very, very individualistic to the point of being contrarian. The Village is all about the collective good, right? It's collectivist, as opposed to the radically individualist river.
- [19:19]
A
But as much as the individualistic and contrarian river likes to define itself in opposition to the clustered groupthink of the village. It is worth noting here to me that the most influential real life street in Silicon Valley is itself an insulated and almost incestuous cluster. A kind of literal village actually, because what Wall street is to the stock market, Sand Hill Road is to the ingenious racket known as venture capital, which is dominated, it turns out, by like five or so VC funds. And the game here is not the stock market, it is to very patiently fund an array of bets instead an array of bets on privately held high growth startups. And so even though the odds of any given startup becoming a unicorn are extremely low, that individual improbability arrayed this way makes it so that it doesn't even really matter.
- [20:21]
B
The basic Silicon Valley venture capital equation is that if you invest in enough businesses that have a tangible shot to return 1,000 times your investment, then like that's a really positive set of investments you're making over the long run. And on the one hand the math is great where like number one, if you are able to be long term and make enough bets to invest in things that can give you a 100x or 1000x return is like a pretty good idea if you're patient enough to see that through.
- [20:50]
A
Right, right.
- [20:50]
B
They also though, like, they have these very profound like recruitment advantages where like the best talent anywhere in the world comes to Silicon Valley and they get kind of the pick of the litter. It's as though in the NBA if the team that won the championship got the number one pick every year instead of the reverse. Right.
- [21:09]
A
But what VCs have determined, and it sounds like in your book you did some modeling of your own to sort of establish how advantageous it is to be a venture capitalist right now who is doing this at the highest level. Because it sounds like early stage VC as you describe it, is not even that quantitative. Like it's not even so much a mathematical secret that Silicon Valley has. It is this larger understanding of we make these bets with this long a timeline that we grant ourselves and it's going to work out to what kind of advantage.
- [21:42]
B
There is, I think, pretty solid evidence that some of these firms routinely have a 20% annual return on investment and 20% compounding interest or profit. I mean they, you know, they grow bigger and bigger and like, and like, you know, I'm kind of unapologetically like a market sky. Right. I think the capitalist system has been good on net for society, but like, you know, at some point there has to be some limit or I don't know Right. But like you buy your fifth house and you buy, I don't know, your private jet and like you have too much money at some point.
- [22:14]
A
Yeah. So Sandhill Road, for those who don't know, is the, it's the, it's the street where all of these people live are. Right. I mean, you describe it, I didn't appreciate the fact that there is the one good restaurant at the Rosewood Hotel. Everybody goes, it is a small town, they're all syndicating into each other's deals.
- [22:33]
B
Silicon Valley is also kind of like an isolated place. Right. It's not somewhere like New York where you get this whole different cross section of people or London or something like that. Right.
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A
It's like there's not a subway on Sandhill Road.
- [22:47]
B
No, it's kind of aloof and, and you go and work really hard. But like it's not the most exciting place either. Right. And like 30% of like all the unicorn startups in the world are in this one small patch of land. It's kind of, kind of insane.
- [23:06]
A
But I do want to zoom back out on the map here because if you are thinking of which specific individuals, maybe which big names might personify the river and the world of probability, I think you might be imagining some of the most rich and powerful and for my money, odious billionaires like Elon Musk or Peter Thiel. And we should mention here that Nate is a part time consultant for polymarket, which recently became famous for letting people bet on the election. A company, a website that Thiel's company, his VC fund, has invested in. But Nate did not know these billionaires personally, it turns out, before writing the book, and he used his access to them to observe something interesting, I thought, because Musk and Thiel, who both happened to work as executives at PayPal in the 2000s, are not as representative of Nate's probabilistic worldview as I thought. Part of what your book does for me, which I did not have prior to reading it, was a crystallization of the ways in which Elon and Peter Thiel and lots of billionaires, who you talk to in the book, by the way, tremendous access, I think, because, as you say, because they detected that you were one of them in a sense, in this way of thinking, you actually subdivide this is how this person thinks, how Elon thinks, and this is how Peter Thiel thinks. And they're not the same thing.
- [24:34]
B
Right.
- [24:34]
A
And so Elon, just to stick with him for a second, in some ways he is the most famous tech Person, quant person. You'd presume he is the ultimate example of what you call the river. But what is he to you?
- [24:50]
B
I mean first of all, he has the highest risk tolerance of like anybody ever, except maybe Sam Makeman Freed. But like Elon, there's an anecdote in the Walter Isaacson biography of Elon where when he plays poker he'll literally just go all in every hand until he either goes broke or he wins everybody's chips. And like that's the way that he lives his life.
- [25:12]
A
And like that tracks as a psychological scouting report.
- [25:18]
B
SpaceX and Tesla were both considered long shot ventures, right? OpenAI which he helped to co found was considered maybe a long shot venture. No clear profit model. I guess they're still losing money, but obviously very impressive business and like starlink. So I mean at some point you have to give credit for like his competitive streak crossed with a contrarian streak. I'm sure he's a fairly high IQ guy. I don't think he's like analytical in the sense that like a poker player is. Exactly. But just being unaligned with the rest of society. And like, I mean, you know, if you read that biography, the Walter Is book, the whole thesis is basically that you can't get the good without the bad. All the things that make Elon kind of crazy and annoying are part of the same personality traits that also lead him to be a very successful and impressive founder and to see things as a visionary in different ways. And you can't seem to like separate those out. Exactly.
- [26:11]
A
But is he probabilistic in the way that you are trying to articulate?
- [26:17]
B
I think he, I'm sure mentally understands probability, but I, I don't think he deep down feels a probability like a poker player would. Right. And in fact, if you talk to Peter Thiel about Elon and they're kind of frenemies. And by the way, I did not talk to Elon. I did talk to, to Peter and a lot of other people in the book. Yeah, he's like, yeah, Elon just ignored the probabilities. Right. It's like, oh, there are all these barriers to having a successful rocket ship company. If you do the math, it's like, okay, there's a 50 chance I trip over every hurdle and then. And by the way, Elon almost thought he was ruined. Right. You know, the fourth SpaceX test finally worked. Without that, no more funding and he probably has a much more minor, minor role in society. But he's like, I don't care about the Math. Right. Like, I think I have a good idea. I see no insurmountable barriers, and therefore, I'm just going to kind of charge a head forward. And what Peter Thiel thinks is that, like, now that everyone is so Moneyball about everything and so math driven, that the edges that you have are actually from the softer skills, potentially from the determination from understanding where the models are wrong. Now that Moneyball is the conventional wisdom, then being a contrarian might actually mean being more deterministic and being really stubborn about one idea and going all in on that idea.
- [27:31]
A
Right. There's a part of your book which I do want to just refer to here, because it is a story, and it's Peter Thiel talking about Elon, and it's a story he tells you about how they. About how they were in a car together.
- [27:43]
B
Yeah. So Elon sold his first company, made, like, $15 million or something like that, and spent $1 million on, like, a McLaren, basically. It could almost be, like, an F1 car. Right. And so he and Peter are founding what eventually be called PayPal. They're burning money really fast. They're on their way to a pitch meeting with Michael Moritz, who is at Sequoia Capital, one of the legendary kind of Midas touch investors in Silicon Valley. And Elon's like, hey, Peter, watch this. And, like, they. He floors accelerator, and the car, like, literally spins out of control on an embankment and, like, is helicoptering up in the air, and somehow it, like, lands on its four wheels and they're okay. And, like. And they hitchhike their way to the meeting. But, yeah, if that car lands differently, then these two people might be severely injured, and all of history is different. And so, like, I asked Peter, Peter, if you simulated the world a thousand times, how often do you think you'd be in a position like this? Right? And like most people, you ask him that question. Like, I asked Mark Cuban that question. He's like, oh, I'm very lucky. Of course. You know things. And that's like, the obvious, like, politically correct answer. But, like, Peter Thiel objected. He's like, look, either the world is deterministic, in which case it's predestined, and that's 100% chance, or then it doesn't really even make any sense, that question. Right. But he's someone, like, I think actually believes in predestiny and believes in fate and is a deeply religious person, I think.
- [29:04]
A
And that I sort of had read about here and there, but I didn't appreciate that. What is his Philosophy. What's his worldview, if you were to describe it? Because he too, despite being again, this ultimate example of Silicon Valley, is not quite the poker player archetype that again, you belong to. That is so much of the rest of his industry.
- [29:26]
B
No, he is oddly more kind of risk averse and I think kind of wanting to protect his downside outcomes a little bit more. Right. So he's kind of the yin and the yang to, to Elon, you know, in some way. You know, look, I know Nick Denton from Gawker and, and we're friends. Right. But like for, for Peter Thiel to spend hundreds of millions of dollars trying to basically bankrupt Gawker is like not like a, not a plus expected value investment.
- [29:54]
A
Thiel confirmed last week that he secretly spent about $10 million bankrolling lawsuits against Gawker. In one of them, a jury awarded retired pro wrestler Hulk Hogan $140 million.
- [30:06]
B
This dispute began in 2007 when a Gawker website outed the PayPal co founder as a gay man. Thiel told the New York Times, Gawker is a terrible bully. He called the lawsuits one of the, quote, greater philanthropic things that I've done. It's a little bit crazy to like say I'm just gonna ruin this guy's life and then have this like, kind of like called shot where it actually works out. And Gawker made all types of problems with, you know, the way the jury testimony went like that.
- [30:34]
A
But he uses Hulk Hogan.
- [30:36]
B
Yeah.
- [30:36]
A
To destroy a media company.
- [30:38]
B
That's a different skill. That's not the impulsive, I guess. Elon has long range planning facilities, obviously. Right. But like it's, it's, there's a meticulousness that's very unusual relative to everybody, including other people in, in the river. But like, yeah, he is not like the, a probabilistic gambler. He is somebody who like believes if I see the world in clear enough terms and things that might seem unlikely are actually not just likely, but kind of predestined to occur. Most of these people are. The irony is like, they're not super duper like rational necessarily.
- [31:13]
A
That is a big thing I found out in your book. It is a book about fundamentally a rigorous and quantitative and probabilistic rational way of thinking. And it's populated by people, the biggest winners arguably who are deeply not rational at times.
- [31:33]
B
No. And even in, even in poker, where the way you play out a poker hand is kind of in some ways a canonical like expected value, rational activity. But like these are People that are very, very skilled and very, very smart in quantitative ways. And, like, they could make a lot more money by working for a hedge fund or working in tech or things like that, right? And instead they kind of choose to have this, like, poker lifestyle, which. It's great when you win a tournament. It's great when you have a great night in the cash game. But, like, it's a grind most of the time, right? Most of the time. 85% of the time you enter a tournament, you lose without any cash prize, and you're up until midnight for days in a row, and then you take a bad beat. So they're kind of all deeply irrational in some sense, but they happen to be, like, narrowly rational in these domains that are now financially rewarded.
- [32:21]
A
When I look around, finance now, and the people who actually have power, right? So part of what's funny and dark about all of this is that everybody wants to feel like the underdog. Everybody wants to be David. And so you have a lot of Goliaths now in Silicon Valley who started off as underdogs that are not wanting to wear the actual responsibility that comes with winning. With winning the game.
- [32:46]
B
A lot of the people in the book are people who had. So I call it. It's like the mezzanine of privilege where you're in the stadium, right? Most of them are. Are white or Asian men, right. Who don't have anything that prevents them from being at the table, right? So they're like. They're in the stadium, they're in the arena, but they're not the people who are born on third base, right? They have to, like, hustle a little bit. And they usually had some, like, traumatizing event in childhood. I mean, Jeff Bezos was adopted, and Peter Thiel is gay and closeted. And Elon Musk had this very estranged relationship from his father, right? A lot of them were kind of, like, bullied as kids.
- [33:27]
A
Another through line is definitely being made fun of and using that to fuel a larger goal of conquest.
- [33:34]
B
So they always feel like they're the underdog and they will have that grievance for the rest of their life. And having a chip on your shoulder having that grievance, that gives you infinite fuel, basically. It's kind of crazy. But, yeah, like I said, I mean, the irony of the book is these people are on, on some level, deeply irrational, but they happen to be irrational in ways that leads them to make loads of money.
- [34:12]
A
When it comes to humility as this concept, right? So there is a humility to wanting to operate on the terms of probability. And this is presented by you as a contrast to hubris, actually, that people often get it wrong, that there is deep humility. I do think though, it's part of like the political messaging problem here, as I contemplate, like. But why isn't this really cutting through across the sort of cultural aisle here? It's because there is deep conviction in the way that you don't know something, such that it feels like you are saying, I know something.
- [34:48]
B
I, I guess you, I mean, you know, in the sense that like, you know, we had our election forecast at 50. 50. I wrote something in the New York Times, but having a, a gut instinct for Trump. And like, I tell people to ignore the gut instinct. That's the whole point. But people kind of, you know, I guess it worked out well on the. But like, but like, literally I thought I was 50, 50, which means that if you're willing to like, let me bet on Trump or Harris at like 2 to 1 odds and I would have like booked action on both sides of the bet. So like saying 5050 is not saying nothing. It's saying that if you're overconfident, then literally I'd bet on that. Right. But it was, I think particularly dissatisfying to people and people like always want to believe that I had some like, hidden belief that like was somehow separate from, from the model.
- [35:35]
A
Well, listen, I do want to ask you why people in this category in what you call the river, why they seem to like Donald Trump? What's your diagnosis of, of that kinship?
- [35:46]
B
I think it's a bunch of factors. Some of it is a pure economic calculation where they don't like Lena Khan at the ftc, they don't like the high taxes that you have in California. They think there's some pay to play where you'll be treated favorably by Trump if you're his buddy. Right. You know, if you look at Elon and when he had a falling out with Democrats, the first incident was actually when Biden would not invite Tesla to their EV initiatives because Tesla was not unionized in the same way.
- [36:15]
A
Infamously, infamously conspicuous that he wouldn't invite Elon.
- [36:19]
B
Yeah. So it's part of it, it's half pure economic calculation. And then half of it is they get, they get red pilled on other stuff. Right. I, I think, you know, to have this kind of very woke, I guess I'll use that term, workforce in Silicon Valley when the message is, hey, we don't like these, you know, these white male capitalists they're bad. I mean, they, they notice that after some period of time and it's, you know, for some people it was Covid. For some people it's trans rights issues and things like that. But like, it's really easy to kind of like fall in this trap and kind of get red pilled, I think. And it feels a little bit naughty, right? It feels kind of naughty when, like when you're told, oh, you can't orange man bad, you're not allowed to praise him. And then you start doing it and it's kind of, I'm sure it feels fun. Like if I were not, how do I put this? I'm gonna get myself in trouble. If I were not a politically knowledgeable person, I could see myself being, oh yeah, Trump, not that bad. Right? But you have to ignore January 6th and you have to ignore tariffs and a lot of things. But like, but you know, people are not these perfectly rational decision makers when it comes to politics. And I can understand why people in that world and other people voted for Trump. And I do think that like the liberal order is very like self serving in lots of ways. I could give examples if I want.
- [37:36]
A
But what does the liberal order mean?
- [37:39]
B
So it's this other community I call the Village. The Village is basically the establishment. It's government, it's the non profit sector and things like that. Right. And like, so look, I, I think, you know, one of the issues where I kind of had like a, something of a falling out with the left is over Covid where I thought that we had too many lockdowns and school closures for too long. I'm pro vaccine and, and wear a mask if you want, but I thought that was harmful in that to society. But those lockdowns are quite self serving, right. If you're a member of like the laptop class and you can work in your comfortable apartment or home and order doordash and, and use zoom and all that, but a lot of like working class Hispanic people and black people are essential workers, right? And, or have small businesses that are being greatly impacted negatively by these closures and, and, and in schools, you know, students in these rich districts that had parents at home who can attend to their child's learning, right. And are not working remotely during the pandemic, like they did fine. Whereas in working class districts, the students who like lost a year of school just kind of permanently like lost. Yeah, you know, a year of school. And like, so, so I do think that like, like Trump doesn't articulate the reasons correctly. No, no, he does. Right.
- [38:53]
A
But like, no, he's not talking about how, look, public health is the art of basically, I think you call it noble lying.
- [38:59]
B
Yeah.
- [38:59]
A
Of withholding information from a population that you don't necessarily trust to behave if given the truth. And that is such an. Again, at this moment, has there ever been a more unpopular ethos than we need to lie to the public?
- [39:15]
B
No, people don't play. I mean, this is one thing that like poker players are, are good at is they are concerned about like the long run. Right. They're like, if I, if I bluff in the situation, then in the long run I'm going to bluff too often and therefore I start losing money. And they are, I mean, I don't know if you'll get to like a poker strategy session, but like people, but they are thinking about like, what's the long term equilibrium when everybody is trying to compete and play their best game, then like, and, and so you're trying to avoid the short term noble lies that like, wind up like, catching up with you.
- [39:49]
A
Trump to you. River Village, where is he on the map?
- [39:55]
B
A friend of mine says he's from the wilderness. Like neither of these camps. I mean, Trump is a very weird figure in that. On the one hand he understands risk, maybe not in a deeply analytical way. Right. He also was in the casino business and like went bankrupt in the casino business, which is actually pretty hard to do.
- [40:13]
A
Incredible thing.
- [40:14]
B
Pretty hard to do. Right. When you kind of have a legal license to print money.
- [40:17]
A
Right. But he, what it was about, what was it about?
- [40:20]
B
The loans.
- [40:21]
A
Right, the loan.
- [40:22]
B
So you know the Trump Taj Mahal when it was built in Atlantic City, was actually like a beautiful, revolutionary casino. At first, yeah, you can't fault him. And it became a piece of later. But like, you can't fault him for like lacking a vision of like this great product. But like, yeah, he took out like loans at like a 13 interest rate. And if you know anything about the casino business, you know it's extremely capital intensive. Like literally the most expensive developments in the world are like airports and casino complexes. Literally. Right. But it pays off over a 20 to 40 year time horizon because you do have a license from the government to guarantee that you make money on gaming operations when people are there. Half the revenues are from restaurants, drinks, hotels, etc, so it's a great investment if you're in the long term, but not if you're taking out loans at like a 13 rate. And like, Trump clearly wanted to be part of the village, right? I mean, he Was, I mean, talk about grievance. Talk about grievance. Right. I mean, if you read the stories and baitly sense, which is true. But like he felt agreed that he was being made fun of at the White House correspondence.
- [41:23]
A
Yes. Which is the village made manifest.
- [41:26]
B
It's the wor. I mean, it's maybe the worst place I've ever been.
- [41:30]
A
It's like, oh, yeah, sure, I went.
- [41:32]
B
One year maybe I think just once. Right. And so like he, but he. Trump feels aggrieved. And, and, and look, there are some things you can say. I mean, I think Trump understands bargaining. He's too imp. He's too impulsive to be a Riverian.
- [42:03]
A
There is one question here that I need to ask you, which is simply about this. Is. This is what Peter Thiel was alluding to. I think some of it. Right. It was that we know who, who has won, you know, not merely the presidency, but also the way of thinking. It's clear that the probabilistic way of thinking, the quantitative way of thinking, Moneyball won. And that is a separate question from has it made the things we love better?
- [42:31]
B
Yep.
- [42:32]
A
I wonder how much you grapple with that as somebody who is perhaps instrumental in, in the way that this movement has been popularized.
- [42:41]
B
I mean, in the sports world, I think it's made basketball better and football better and baseball worse. Probably just from an aesthetic standpoint.
- [42:49]
A
You like the threes, you like the three pointers.
- [42:50]
B
I like the threes.
- [42:51]
A
I like the three true outcomes.
- [42:52]
B
Go watch, go watch the 1980s basketball game where you have like it. Trust me, the athleticism is much more on display now. Look, the fact that like we have all these elections come down to basically 50, 50, right. And it's so kind of ruthlessly efficient. You don't get these like landslides anymore. It's kind of so predictable that 85% of the states, you know, it's where they're going to vote every election. And so, so like, so one problem with Moneyball type thinking is that like, it's like easy to solve for like the short term equilibrium, but like, hard to know kind of what's best in the long term. Right. And generally speaking, Democrats are the party that is more skilled at like the analytics and building out the campaign tools. And you know, I, I kind of wonder all these campaigns where they just. Obama went by a big margin in 2008. Right. But the best are kind of like just getting over the finish line and like, and like, you know, so I think there's been like kind of a Lack of. Of long term vision in the party, which you can tie sometimes to being, to having all these short term metrics that you can, that you can optimize. Right.
- [44:00]
A
And all of this, in the end, brings Nate Silver back to the poker table. Yes, he's still writing about politics over at Silver Bulletin, his substack. And he's still in the de facto business of being right, as much as he may that. And he's also still the worst and most impulsive version of himself over on Twitter where he's trying to call out bull or whatever it is that he, you know, justified it as. As we discussed before. But Nate also finished 87th at the 2023 World Series of Poker main event, which does sound, you know, pretty bad. 87th until you realize that there were more than 10,000 competitors there. And look, I have moderated plenty of panels at the Sloan Sports analytics conference. I've written about trusting all sorts of processes, but I am not any kind of poker expert. And so when I see a YouTube video, for instance, where the image screams, quote, nate Silver bluffs with dirty diaper. Three exclamation points, I am a bit confused.
- [45:14]
B
Oh, and he puts it into the muck. What a remarkable run out that was for Silver. The pair on the turn, the fourth spade, and he manages to get it through Savage.
- [45:28]
A
Savage bluff by Silver. Oh, my God.
- [45:32]
B
Oh, my goodness.
- [45:36]
A
In so many words. Nate had a horrible hand, but his opponents did not call him on his bull. But the good news for that opponent, I suppose, is that that guy can now relate to another one of Nate's opponents. Baby, from the World Series of poker in 2022, an opponent by the name of Neymar.
- [45:58]
B
He's picked out Neymar. Oh, what a finish.
- [46:03]
A
What a finish by Neymar. Yeah, him. What's your scouting report on Neymar? What happened in that.
- [46:11]
B
In that.
- [46:11]
A
In that game, too.
- [46:12]
B
Too aggressive. We were also playing like limit hold them and limit hold them. It's hard to get people to fold. I play against.
- [46:19]
A
So you wrecked Neymar is what I'm.
- [46:21]
B
Yeah, I played against Ryan Garcia, the boxer. Oh, yeah, yeah. Who was actually pretty good when you happen to be playing. It's like a random celebrity in poker. They don't give a really. Because they don't have any, like, ego loss. And so, like, they're very aggressive usually and have a lot of heart is a term that you'd use. And like, that actually goes a long way in these giant poker tournaments where you get to the World Series of Poker I made day six a couple years ago. And like, people get scared and they're scared of losing. And these guys tend to have, they're aggressive and they have heart. And like in poker, if you're bad and aggressive, it's actually still pretty hard to play against. If you're bad and weak, passive, then you're guaranteed to lose money and everyone wants you at your table. Right. But if you're aggressive and unpredictably aggressive, then you're not so far actually from being a dangerous opponent.
- [47:07]
A
There is a thing in your book that I also want, want to ask you about, which is that you say at a certain point, because again, you are a probabilistic thinker, of course, you write that you would not take a 1 in 6 chance of dying in exchange for a billion dollars, but that you would take a 1 in 38 chance of dying in exchange for much less than a billion dollars. That second bet of 1 in 38, you would actually, you would actually.
- [47:30]
B
138 is not that high. It's pretty low. Yeah, I, I, how much am I, how much did I say I would take? I, yeah, 1 in 38. I'd fade that risk. Although. Yeah.
- [47:40]
A
Would your partner, Nate, would he have anything to say?
- [47:44]
B
He would not be happy. He's like, what are you doing? No, he'd be very unhappy about that, hopefully. But no, I mean, so if you look, you know, there is something called the statistical value or value of a fiscal life, which is that it's set at $10 million, right? So, like, if you're trying to say, okay, we are going to like clean this asbestos out of this building at a cost of 100 million bucks, but it'll save 20 lives, then the government would say it's cost effective. Right. And so people get really annoyed by this. Like, how can you put a value on human life? Yeah, but where it comes from is how people value their own life. If you're taking like a dangerous job, if you're looking on like logging all these things in Alaska, like being a logger or like a lobster boat fisherman in Alaska, right. All these dangerous jobs, people are quite aware of the risks they present and like, how much additional compensation do they demand for those jobs? Or how much are you willing to pay for like safety features in a car, like airbags in the car that reduce your risk of dying by X small percentage. Right. And if you look at how people behave in the real world, they value their own lives at about, about $10 million. Right. I put I value my life. More than that, actually. I wouldn't gamble for. For 10 million, but there's some number at which I would.
- [48:59]
A
Yeah. So one in 38. What you're saying is you like your chances.
- [49:03]
B
I play the odds. Yeah.
- [49:05]
A
Nate Silver, I really enjoyed this. And the greatest compliment I guess I can give you at the very end here is that I genuinely on that question. I hope you are right.
- [49:15]
B
I appreciate that, man. Yeah. If. Yeah. I don't want to. I don't want to encourage people. A way to actualize.
- [49:23]
A
It's an important disclaimer.
- [49:24]
B
Yeah. Cool, man. Of course.
- [49:26]
A
Thank you, Nate.
- [49:27]
B
Absolutely.
- [49:36]
A
This has been Pablo Torre Finds Out a Meadowlark Media production and I'll talk to you next time. Sam.