Invest Like the Best with Patrick O'Shaughnessy
00:19:16 · Cliff Sosin
And if somebody had read all three papers and thought about it, they would have realized this, but nobody had. But it turns out the models read all the papers, and they'll figure that out. There's gonna be all kinds of great stuff that falls out of that. But at some point, we're gonna kinda finish that. And then it's gonna be about like, hey, there's some way to think about things that are outside of what we know. And we have a hypothesis. But a model, even a super smart model, won't be better at guessing that necessarily... Will be better at guessing that than the smartest person. But the smartest person's odds are super low anyway. So it'll be able to come up with great ideas for experiments to do, and they'll be worth doing. But that'll limit our ability to expand. The other thing I just think about is my own use of AI on a lot of levels. One, just to go back to the commoditization thing. I've totally commoditized my use of models for its worth. It's because I'm lazy about how I do a lot of my building for stuff. I'll tell your Grok bot to build things. And because I don't wanna use up all my Grok bot Weed tokens, I then have it run all of them. I subscribed to all the things. And I'll have it build using those subscriptions on a server. And so I actually don't know what model I'm using anymore. I used to know this model is better, this one's worse. I no longer know. All of this is being optimized on the back end for me and all I know is that stuff is getting built and it's not using up my subscriptions and so we're good.
00:20:31 · Patrick O'Shaughnessy
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00:22:16 · Cliff Sosin
[00:22:16] S1: Yeah. Super great idea. Closing the loop in the physical world is gonna be great, and it's gonna accelerate the process of learning. And this is a great idea. But again, there are speed limits. The thing I keep coming back to is some version of, this is amazing. And I'm super, in a sense, AI pilled in the sense of what I think these are things we're gonna do and they're useful for. But I'm also cognizant of the idea that things bump up against... The way I like to tell this to people is I said, look, you're really smart, so you must understand. Being smart has limits. Being smart has limits. And so the ability to just think your way to solutions is limited. And so if you're gonna build an automatic biology testing laboratory, and you're gonna connect it to a computer, and the computer's gonna come up with an idea, and then it's gonna run an experiment, and it's gonna iterate, that's awesome. But if that experiment requires breeding mice, and mice need a year to grow up and die, that experiment will take time. And it might be a great experiment, you might learn a lot, and that's great, still gonna take time. And the lab's only so big, and so you might have 5,000 great ideas, you're gonna pick 20, And the model may be better. Your odds of that experiment marketing might even be 1%. Turns out that might be 10 times better than the average researcher. And that's amazing. It's still 1%. None of this is to be pessimistic. This is super amazing. Discovering all the things that we should know because it's already in our corpus that we forgot is awesome. Discovering all the things and better directing our research is awesome. Automating that research to move faster is awesome. We will learn that will push the frontier. But this is not like suddenly the model looks around and says, you guys missed it. Here's some new world that you guys can't comprehend or whatnot. I don't think that's where
00:23:50 · Patrick O'Shaughnessy
[00:23:50] S0: we're headed. It seems like the market has been, especially in private markets and the leading edge of investors thinking about AI, very focused on investing in supply related stuff, like how are we gonna build and serve all the intelligence versus what I'll call demand related stuff. Someone watching their personalized TV on their meta app or whatever. What do you think about that first batch of companies as investments? Super
00:24:12 · Cliff Sosin
[00:24:12] S1: hard. I've joked I've been willfully ignorant about them and probably I'm sort of worse off for it, but there's this big build out. And then you're trying to forecast inference demand. I can't forecast supply or demand within several orders of magnitude. But this idea of how much more inference will people use as intelligence gets better and cheaper is a really, really hard thing. And equally hard is how much better and cheaper inference is gonna get. And then even if you could somehow guess at those things, then there's the whole value chain, and you need to be at the bottleneck in order to capture the rents. And then, of course, finally, you get to your actual competition with your competitors in that particular piece of the value chain. It's just a super hard thing. As I think about my use of AI as a consumer, increasingly, I'm doing stuff like, instead of having the AI chatbot talk to my daughter or text with my daughter about how to do math, now I have it make a three blue, one brown style video explainer so that she can see a nice five minute or ten minute video on powers or area or circumference or something. It's super cool. I don't think I would do that if it was gonna be $5. And so there's this thing where there's real price elasticity. The point I'm trying to make is I'll film myself working out with my Muse app, and it'll show me tip pointers on my form. And I'll do that for very little money. But I won't do that if the price point is real, and I'm probably much less sensitive to the price than most people. AI demand is gonna be really sensitive to the price, which intrinsically, I think, does limit in some sense, the amount in total consumers are going to be willing to spend on this.
00:25:39 · Patrick O'Shaughnessy
[00:25:39] S0: Maybe this is a time to talk about capital cycles or something. It sure does seem like the smartest people in the world, and many or most of the best entrepreneurs in the world are heavily personally invested in this supply build out thing. If you watch SpaceX's Investor Day yesterday, this is basically the theme of it. Arguably, maybe the greatest entrepreneur of all time is dedicated to effectively doing this, building out the data center supply, etcetera. This is just a historical question. If that's all true, and there's so much uncertainty about supply and demand, and there are other ways to go build businesses, products, make money, why do you think so many of the best entrepreneurs, the smartest people are so completely dedicating their lives to the build out of the supply?