Invest Like the Best with Patrick O'Shaughnessy
00:29:12 · Patrick O'Shaughnessy, Cliff Sosin
[00:29:12] S0: little from the frontier? Then the cost of making something comes way down. In that world, would your model be that physical and scale are the things that you'd want in a business that you were to back on the supply side of this equation? TSMC? [00:29:26] S1: I don't want to carry myself around as some sort of TSMC expert. I mean, certainly, what they do has better attributes, I think, that regard. They've also got this sort of interesting problem where they did this super hard thing that requires all this process power built over many years, and it's super hard to replicate, and much less amenable to AI just because it is so physical and because it's all these little things, many of which aren't even legible to an AI. It's like some guy who is in the system kinda knows that you have to do this. Because there's so much demand and because they have no immediate, they've basically caused everyone in the world to seek to copy their moat. That's not a great fact. But I think more generally, stepping outside the AI build out, if you think about businesses... We talked about the meta example. Just the idea of businesses that have physical proximity or physical scale might benefit if they can use intelligence to serve their customers better or have lower cost as a consequence.
00:30:14 · Patrick O'Shaughnessy
[00:30:14] S0: I want to go back through the natural complement to intelligence. Just have you explain why it's a complement to intelligence so that people can go away and think about, okay, what companies have this feature that might be interesting? Good example to go talk about physical proximity. How would you think about DoorDash or Uber or these businesses that have local density effects that matter a lot? Does intelligence being ubiquitous sort of naturally magnify all of the scale winners of this type where physical proximity is some sort of key advantage?
00:30:43 · Cliff Sosin
[00:30:43] S1: Well, so if you're the low cost producer of something, I'll give a sort of stylized example. So if everyone has an AI agent, then what happens is many decisions get offloaded to the AI agent because the AI agent helps you optimize, helps you pick up all the pennies and dollars and nickels and stuff that you were leaving on the ground. So I think about consumer choices in the spectrum. On the one hand is maximizing my bank deposit. This is something where I think I can almost entirely defer to the AI's judgment. As long as it's FDIC insured, I just want the highest rate. On the other hand, this end of the spectrum might be picking my favorite sweater. This is something where it's just all of my judgment. The AI can source me things to look at, but in the end, I need to decide it. I can't really delegate that judgment to it. And there's a spectrum. And so let's just pretend for a moment that garbage collection is something where I can defer the judgment. You might say, no, I really care about the guy, and I trust the service, and he's driving into my house or whatever. But let's just settle that aside for a second. So right now, if I'm in the waste collection business, I might be great at it. But it's still really hard to get people to bother to switch. I doubt you know what you pay for garbage collection off the top of your head. Many people do, but I doubt you do. And so what happens is you have to do all this work to get people to pay attention to bother to switch garbage collection companies, even if you're offering a better service at a lower price. You could imagine that their agent could talk to my agent and be like, hey, I'll save you 50¢ a month. And the agent will say, will the garbage go away? And I'm like, yes, the garbage will go away. And no problem, and I'll change. So the first order effect is that you move to the low cost provider. But the general market effects are actually sort of interesting too, because now let's say that there's a street. And before, it would be more efficient for society if all of the people on my street the same garbage collector, because the guy could drive up the street and pick up the trash, he could offer all of us lower price and make more money. But it's really hard for us to coordinate that because what happens is all of us are just lazy about switching garbage collectors, and so we all have one.
00:32:24 · Cliff Sosin, Patrick O'Shaughnessy
And the guy with two guys on the street can't call everyone else up and say, hey, I've got two guys on the street. Everyone else has just one. I'm the low cost producer. Let me roll this up. So a second order effect might be that the guy who has two people on my street can go to everyone else on the street and say, hey, I'll offer you a lower price in the garbage, and everyone will switch. And so everyone moves to the low cost producer who in turn gets to be the lower cost producer. That actually creates, in some sense, a better business, where the low cost guy wins a bunch more volume at much lower margins. As you study them, a lot of companies have mixed effects that point in different directions because of these things. [00:32:56] S0: What do you think the impact of agents is going to be on your world? What will be your role? How will it be different in five years? Yeah. Will the best agent be able to build a portfolio of Carvana and Hilton Grand Vacations and Meta in the same way that you would because you trained it how you think? [00:33:10] S1: Well, hopefully better. In terms of what I do, I think that in the long term, we'll probably get competed out. [00:33:16] S0: Right. Basic pricing risk as the thing you do?
00:33:16 · Patrick O'Shaughnessy, Cliff Sosin
[00:33:16] S0: Right. Basic pricing risk as the thing you do? [00:33:18] S1: Yeah. When computer aided chess came along, there was this long span of time where freestyle chess was better, where the human working with the computer program was able to outcompete either the human or the computer by itself. And this is just because humans thought about things differently and computers thought about things differently, they were synergistic. And I think in investing for a while... [00:33:37] S0: We're in that era now.
00:33:38 · Cliff Sosin
[00:33:38] S1: We're in that era. And that's because there are things that I understand in the world in ways that the model just doesn't, by virtue of being a person and having lived a life. And there's information I have about the world that just isn't in models, because as much information is on the internet, not everything is actually on the internet. While that's true, which is going to, I think, be a while, the ability of me to use models to assist me and then to make judgments will make better judgments working together. You could imagine a circumstance though, in the future, where that gap diminishes to the point where it doesn't matter anymore. And then I don't think models will able to predict the future. As we talked about, the future is in some ways very intrinsically unpredictable. But the model's distribution of outcomes may be the best that you can do. And that adding a human to the forecast would be kind of like adding my judgment to whether or it's gonna rain in seven days. He just kind of would be like, Cliff, I don't really care what you think. I'm using the forecast. This is gonna be better. However you fudge it, it's just gonna make it worse. That day may come. Instead of an interesting moment there, there's a lot to invest in. Think about judging management or something. But maybe the models will be able to judge management. They'll they'll be able to interview them. They'll be able to figure it out. And then it gets really interesting. How do you raise capital? You'll be like, you know, I'd like to run an amusement park and models it. Sure. Here are six locations that have a 51% chance of an amusement park working. And as long as you're really committed to it... And I've assessed you and you have a 51.2% chance of succeeding because you're actually slightly below average. You're like, okay, well, what can I do better than average? And I say, well, you know, have you thought about running a go karting park? Fortunately, I don't think it's gonna affect my career that much because I think it'll take a while.