Dylan Patel: evaluation

Transcript context

…Well, it’s still private ownership, but how many firms are really involved in this share of the economy? It’s, what, maybe 2% of the economy right now? $1 trillion divided by 30. Nvidia is a huge share of it, and Anthropic and OpenAI and these hyperscalers. Obviously there are other firms involved, but a large share of the AI stuff is just happening from very few companies. So it could be private property, but very few companies are involved. I mean, this is what the structure of the market is doing. So what can prevent it? I don’t know. Unless AI progress slows down, unless governments regulate the fuck out of it, this is all that happens. In which case, we’re headed for a world where either we have super concentration of resources and we pray that that one company gets everything right, or we have governments slow everything down and people slow everything down, and you have a slowdown of progress somehow hopefully, and there is more of a balance of power. Even as we go towards AGI, ASI, RSI, everything along the way will still lead to someone capturing more resources. So it’s kind of hard to find a framework in which AI doesn’t lead to super concentration. Now, the one positive thing here is that today Anthropic does not capture most of the value. We can talk all we want about how they went from $20 million per megawatt to $100 million per megawatt, but they’re still paying $13 million for a lot of the compute they’re buying. But at the end of the day, the reason they’ve gone to $100 million per megawatt is because Jane Street is capturing $300 million per megawatt or $500 million per megawatt. Or Dwarkesh, from researching his podcast and learning about credit, is capturing how many dollars per megawatt? Now how much can you use? Tough. But I think that’s the one saving grace, that the rest of the economy maybe profits so much more from Anthropic— No, but the whole logic you were laying out earlier — them reallocating inference to AI R&D — the whole logic of that is that the returns to labor inside AI labs are much higher than the returns outside.…

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