Dario Amodei: prediction

Transcript context

…What about the limits of compute, meaning the expensive nature of building bigger and bigger data centers? So right now, I think most of the frontier model companies, I would guess, are operating in roughly 1 billion scale, plus or minus a factor of three. Those are the models that exist now or are being trained now. I think next year we’re going to go to a few billion, and then 2026, we may go to above 10 billion. And probably by 2027, their ambitions to build hundred billion dollar clusters. And I think all of that actually will happen. There’s a lot of determination to build the compute, to do it within this country, and I would guess that it actually does happen. Now, if we get to a hundred billion, that’s still not enough compute, that’s still not enough scale, then either we need even more scale, or we need to develop some way of doing it more efficiently of shifting the curve. I think between all of these, one of the reasons I’m bullish about powerful AI happening so fast, is just that if you extrapolate the next few points on the curve, we’re very quickly getting towards human level ability. Some of the new models that we developed, some reasoning models that have come from other companies, they’re starting to get to what I would call the PhD or professional level. If you look at their coding ability, the latest model we released, Sonnet 3.5, the new or updated version, it gets something like 50% on SWE-bench. And SWE-bench is an example of a bunch of professional real-world software engineering tasks. At the beginning of the year, I think the state of the art was 3 or 4%. So in 10 months we’ve gone from 3% to 50% on this task. And I think in another year we’ll probably be at 90%. I mean, I don’t know, but might even be less than that. We’ve seen similar things in graduate-level math, physics, and biology from models like OpenAi’s o1. So if we just continue to extrapolate this in terms of skill that we have, I think if we extrapolate the straight curve, within a few years, we will get to these models being above the highest professional level in terms of humans. Now, will that curve continue? You’ve pointed to, and I’ve pointed to a lot of possible reasons why that might not happen. But if the extrapolation curve continues, that is the trajectory we’re on. So Anthropic has several competitors. It’d be interesting to get your sort of view of it all. OpenAI, Google, XAI, Meta. What does it take to win in the broad sense of win in this space?…

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