Marc Andreessen: prediction

Transcript context

…It feels like 2025 is when the race for dominance in AI will see some winners. It’s a big year. So, who do you think wins the race? OpenAI, Meta, Google, xAI… Who do you think wins the AI race? I would say, I’m not going to predict, I’m going to say there’s questions all over the place. And we have this category of question we call the trillion-dollar question, which is literally, depending on how it’s answered, people make or lose a trillion dollars, and I think there’s, I don’t know, five or six trillion questions right now, that are hanging out there, which is an unusually large number. And I’ll just hit a few of them and we can talk about them. So, one is big models versus small models, another is open models versus closed models, another… … Small models. Another is open models versus closed models. Another is whether you can use synthetic data or not. Another is chain of thought. How far can you push that? And reinforcement learning. And then another one is political trillion dollar questions, policy questions, which the US and the EU have both been flunking dramatically and the US hopefully is about to really succeed at. Yeah. And then there’s probably another half dozen big important questions after that. And so these are all just like, say, this is an industry that’s in flux in a way that I even more dramatic, I think, than the ones I’ve seen before. And look, the most obvious example of the flux is sitting here less than three years ago, sitting here in December of ’22, we would’ve said that Open Ai is just running away with everything. And sitting here today, it’s like there’s at least six world-class God model companies and teams that are, by the way, generating remarkably similar results. That’s actually been one of the most shocking things to me is it turns out that once you know that it’s possible to build one incredibly smart Turing Test-passing large language model, which was a complete shock and surprise to the world, it turns out within a year you can have five more. There’s also a money component thing to it, which is to get the money to scale one of these things into the billions of dollars. There’s basically right now only two sources of money that will do that for you. One is the hyperscalers giving you the money which you turn around and round trip back to them, or foreign sovereigns, other country sovereign wealth funds, which can be difficult in some cases, for companies to access. So there’s maybe another trillion-dollar question is the financing question. Here’s one. So Sam Altman has been public about the fact that he wants to transition OpenAI from being a non-profit to being a for-profit. The way that that is legally done is that … And there is a way to do it, there is a way in US law to do it. The IRS and other legal entities, government entities, scrutinizes this very carefully because the US takes foundation non-profit law very seriously because of the tax exemption. y in US law to do it. The IRS and other legal entities, government entities, scrutinizes this very carefully because the US takes foundation non-profit law very seriously because of the tax exemption. And so historically, the way that you do it is you start a for-profit and then you raise money with the for-profit to buy the assets of the non-profit at fair market value. And the last financing round at OpenAI was 150 some billion dollars. And so logically, if the flip is going to happen, the for-profit has to go raise 150 billion out of the chute to buy the assets. Raising 150 billion is a challenge. So is that even possible? If that is possible, then OpenAI maybe is off to the races as a for-profit company. If not, I don’t know. And then obviously the Elon lawsuit. So just because they’re the market leader today, there’s big important questions there. Microsoft has this kind of love-hate relationship with them. Where does that go? Apple’s lagging badly behind, but they’re very good at catching up. Amazon is primarily hyperscalar, but they now have their own models.…

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