Invest Like the Best with Patrick O'Shaughnessy
· Ben Horowitz
[00:00:00] S1: Policy. One of the things my father said – a bad government, no matter how many smart people you have, no matter how great a culture you have, no matter how great the country is, can ruin the whole thing. Venezuela was the fourth richest country in the world. Communism, and that's that. You know, if you look at how little comes out of so many of these countries in Europe that have so many smart people, you know, the ones that went into communism. There's so many genius Romanian entrepreneurs. John von Neumann and the number of great genius scientists that came out of Hungary, like, this little country. And then it was just gone once the communists took over. There was completely nothing. From inventing everything to nothing overnight. And I think that that can absolutely happen here. We could outlaw AI. There were pretty aggressive proposals. The last Biden administration executive order said that you could not sell a GPU without federal government approval. That was a real executive order, and it got reversed, but like, we were that close to being basically out of the global chip game. It is fragile. Technology solutions work much better than policy solutions. That's the other thing. Like, policy solutions, it's very hard to make anything work. So, if you think about COVID, we could tell everybody to stay in their house. Well, that's got some extremely bad side effects. Turned out not to work that well. Or we could invent a drug that cures it, or a vaccine that works. It's just hard to have a policy solution, like all the policy stuff on climate change. And Europe actually reduced emissions and all that, but it didn't do anything because China didn't reduce emissions. But if you build a technology, a safe nuclear fission or a nuclear fusion facility, that would have a big effect. And I think, in general, that's true. "Defund the police" did not make anybody safer. But technology does. If you really want to change the world, if you really want to make it a better place, I think you can build a solution for darn near anything. If you want to change the world for the better, it's never been a better time to be an entrepreneur.
· Patrick O'Shaughnessy
[00:00:00] S0: I was with a local restaurateur yesterday here in New York, one of the best, for a couple hours, having him describe to us how he is planning on using AI tooling to improve everything about his restaurant business. How do you think about the way all of this is changing the sort of potentially large attractive businesses that you want to invest in? Because many great companies that have been built in and around restaurant software businesses. It seems like this restaurant owner is going to be able to have his own spun-up operating system specific to him, not going to need any of that stuff. How is this changing the way in which you view investment opportunities?
· Ben Horowitz
[00:00:00] S1: On the positive, everything is up for grabs. I think people are kind of overreacting to that in the stock market and so forth, in that if you look at existing software companies, people think, "Oh, they're all dead." Some of these guys are extremely hard targets. It's not that easy to take out Salesforce or SAP. You would be surprised, even with AI, how much heavy lifting that is. Having said that, it is true that a lot of these things, you can just make your own, you can do it yourself. It's going to be a lot easier. The number of possible interesting companies, I think, went up a lot. The other thing we're seeing is the products work so much better than any technology products we've seen in the past. Revenue growth is so much faster for these AI companies. And there's many such cases of companies coming out. Cursor, which is ostensibly an IDE, like what's the biggest IDE before Cursor? I don't know, but it wasn't big. And it took probably 12 or 15 years to get to that revenue level. And yeah, they went over a billion dollars in revenue in no time. So that's super interesting. I would say though, from an investing standpoint, the laws of physics of company building changed, which is going to affect investing in what's currently, I would say, an unknown way. If you look at the one thing you knew, if you'd ever built a software company, is you cannot throw money at the problem. "What's a man-year? 700 IBMers before lunch." That phenomenon, everything was built on because you knew if somebody built a great product and it took them three years and they did it with a small team, Google's not going to hire 2,000 engineers and catch them. It's just not going to happen. That was a law of physics. Now, if you have the data and you have enough GPUs, you can solve damn near anything. And we've seen that with Elon catching the big models in no time. He just took a lot of money and a really good data center design and some smart engineers. And he got in the game very fast. That would have never happened in the past. The markets also seem to be much, much, much bigger than anything we've ever seen. It would cause you to think about valuations and long-term value and other sorts of things in a different way than we have in the past.
· Ben Horowitz, Patrick O'Shaughnessy
On the one hand, well, when you calculate the long-term value, what if this market wasn't $50 billion? What if it was $5 trillion? On the other hand, what if somebody could catch you? These are concepts we've not dealt with. [00:00:00] S0: So how would the conversations feel different to me if I came in – you've got all these great investors working at Andreessen Horowitz. The nature of the conversation amongst your teammates as they're debating this stuff versus four years ago or something – where does it feel most materially different internally?
· 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.