Dan Hendrycks: evaluation

Transcript context

…Yeah. I mean, another thing that struck me is essentially right now, AI is not that difficult to make. Right? So the the algorithms are just doing stochastic gradient descent, and they're using transformers and data. And almost anyone, I mean, any nation state would be able to create this capability. Right? In 1 of your papers, you even said, I think, that there is I think it was a 96% correlation between comp you like the amount of compute and and the capabilities. So doesn't this, like how the hell can you I mean, obviously, you can, like, control supply chains and and whatnot, but what's to stop any nation state from just building this? Yeah. So I think that the critical mass currently is on the order of, if we're trying to build, like, a state of the art system that's on the order of, like, 10 k GPUs, China has that. The US has that. I don't think Iran has that, for instance. We're talking cutting edge GPUs. We're not talking iPhone GPUs or whatever. So I think you would try to have more responsible actors or states that respond to incentives better, being ones with GPUs and ones that are more rogue, like North Korea, not getting those. So you want ones that are more durable. I think Russia has that many GPUs, for instance. I think it'd be difficult for them to put together a competitive project. I think also competition is not just having the smartest model as well. There's deployment capabilities, not just model making capabilities. So we can see that the AI model providers limit the amount of videos that you can make. This is because of compute limitations in part. And or the amount of, yeah, the amount of videos and images. And I think with AI agents, they'll be running round the clock if they're sufficiently useful. So right now, maybe you use your AI systems for a few minutes a day, your chat bots. But then you'd be having it run constantly. So it's like, I don't know, tours of magnitude more compute required there and maybe the models are bigger as well. It's that's a lot and then more people are wanting it too. You're needing a lot more compute. And so your deployment capabilities, how many chips are owned by, say, US hyperscaler companies, Azure, AWS, etcetera, is a very relevant competitiveness variable because then are they able to serve the customers or not? China, if they have less than 100,000 GPUs, they can't really serve that many customers. So even if they can make somewhat capable models, that doesn't mean that they'll be necessarily capturing many of the economic benefits that AI may provide, provided there's a a catastrophe. So that that's a different important axis for competition. I think people are thinking of the smartest thing, but I think, having the smartest model is the most important thing. But for economic power, it's quite different. But I think you said that when the real Manhattan Project was undertaken around the time of the Second World War, it cost The US something like 4% of GDP because they they had to be first. Right? They had to control this technology. And for such a kind of generational technology, 4% of GDP doesn't seem that much. And and, of course, you can explain perhaps why Taiwan has such a moat around building these chips at the moment. But if if it is of such catastrophic importance, don't you think many nation states would be able to create this capability?…

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