Invest Like the Best with Patrick O'Shaughnessy
· Ben Horowitz
[00:00:00] S1: I would say one of the most different things is when you look at AI researchers, it is really a different kind of thing. If you haven't been at Google or Facebook or OpenAI or Anthropic and somebody gave you hundreds of millions of dollars to try and build a giant model and you weren't one of the main people, then you probably don't know how to do it. Because you can't learn it in school. You can't learn it in school because it's a little bit alchemistic in nature. It's a little bit of an art. And so if you've never done it before, the chance of on your very first try of building some kind of large model, that it's going to work well, isn't that great. People are coming up to speed more. There's more companies. People are learning it. But that's kind of why you got to this, which from the outside world probably looked absolutely bananas, that why is somebody paying $100 million for an AI researcher or a billion dollars for an AI researcher? Like, that's the craziest thing I've ever heard. Well, what if there are only 40 of them in the world? Then it kind of changes the math on it a little bit. And I think that's where we were because it's kind of the first time we've had a need for a technologist that academia can't produce. That is probably one of the bigger things that changed in the conversation is, like, who are all these people? And like, we track all of them and know what they're doing. But it's very different.
· Patrick O'Shaughnessy
[00:00:00] S0: Everyone talks in venture about the power law. The thing underneath the power law is a sort of inequality. It seems like so many of the things that are happening are just massive multipliers on the trend of inequality, in every way. The billion-dollar researcher, the size of the biggest companies, the wealth of the people creating those companies. I would argue that inequality is a feature, not a bug of the American system. But I'm curious for you to riff on the nature of growing inequality and the good and the bad associated with that.
· Ben Horowitz
[00:00:00] S1: What's happening in AI is, I would just say, an extension of the Kobe Bryant effect, which is, you know, a basketball player. There was a limited amount of money you could make because you basically played the game in front of the people who could show up for the game. And that was it. That's the whole market. Whereas once you add television and a global audience and these kinds of things, you can be LeBron James. You can become a billionaire. And that was not at all possible before. And I think that we kind of first saw that with the internet where, "Okay, now I can build a product. I can get to global distribution very fast. Then all of a sudden I can become extremely rich." And then AI is another layer on top of that in that, okay, now take that same product and make it just a more valuable thing. Whoever invents that is whatever the internet company was, plus, plus, plus. And so that's going to make them even richer. That's the bad part of it. But I think the good part of it is it's starting out day one completely democratized. Anybody gets access to very powerful AI. Most people in the world at this point have smartphones. And now you've got superintelligence in your phone. So that's a big equalizer of the opportunity in a lot of ways. I don't think we've ever seen a bigger opportunity equalizer than AI. Every child can have a super advanced, amazing tutor or teacher. Great education is accessible to all. So I think it's an equalizing technology. And there's some drive in inequality there. This is another thing I learned from my father when I was very young was, he said "Look, son, life isn't fair." That's extremely good advice because it's just not going to be fair. No matter what government or anything tries to do, it's not going to be fair. And the problem is if you create a system that tries to correct that, it doesn't make things more fair. It just transfers all the power to the person running the system. And that's what happened with Stalin. That's what happened with Ceaușescu. That's what happened with Pol Pot. That's what happened with Mao. Not an accident that every single system like that went bad because it really ends up just being a power transfer. When you think about, well, what do you want? You'd like everybody to have a chance. Don't give me no chance. Give me some chance.
· Ben Horowitz, Patrick O'Shaughnessy
It may not be as big a chance as the other guy. It may not be a perfect chance. But if I have the desire, if I've got some capability, give me a chance to be something, to make my imprint on the world. A system like that is going to end up with a lot of inequality. By the way, all systems end up with a lot of inequality. But you can try systematically to give everybody an opportunity. I think AI does a really good job of that. [00:00:00] S0: One of the memes that's very popular today is that you have a couple years to get some capital or you're going to be a part of the permanent underclass, is the phrase that’s used on Twitter. And I certainly agree that now everyone has the best lawyer, accountant, advisor in their pocket, and that's amazing. But what do you think about this notion that because of that, we need less labor? It's going to be harder if you don't have some capital to begin with to accumulate capital and break in. I don't necessarily believe that. I'm just curious what you think about the challenges we'll face because of AI societally.
· Ben Horowitz
[00:00:00] S1: I don't really think that's right. I don't think the door is going to close behind you. I think the opportunities tend to multiply when you kind of open up a new door and open up a new way of doing things. So many people who made money on crypto were people who literally didn't have much to start with. They just got into the technology early and they kind of parlayed it up. And so if you have something that grows really fast, that's actually the opportunity for somebody with a little bit of capital to make a lot of money, because it doesn't take much. You know, if you bought Bitcoin for a nickel, you did really well, and all you needed was a nickel. That's the nature of these things that go hyperbolic, and particularly if you create something. I also think the labor market stuff, people are acting as though it's very predictable when it's not at all predictable. If you look at the history of the world and automation – and this is what it is, it's a kind of like an automation technology. We've been automating things since the agricultural days. And in those days, I think 95% or 96% of all jobs in the US were agriculture. Almost all those jobs have been eliminated. And the jobs we have now, the people doing agriculture wouldn't even consider jobs. The idea that we could imagine all the jobs that are going to come, sitting here, that AI is going to enable, I think is low. I think the need for more creativity jobs is going to go way up and the need for jobs to process work for the creatives will probably go down in some ways. But I'm not even sure about that. We've had AI going – ImageNet was 2012, and then natural language stuff in BERT and all that was 2015. And then ChatGPT was 2022. And where's all the job destruction? Why hasn't it happened yet? And why are you so fucking sure it's going to happen next? And why are you so sure no jobs are going to be created? I don't think it's nearly as predictable as people are saying.
· Patrick O'Shaughnessy
[00:00:00] S0: How would you describe the nature and scope of your ambition over the next 10, 20 years?