Ryan Kidd: prediction

Transcript context

…It's funny that he's come up a couple of times in my mind just as sort of pattern matching on some of the things you've said. But the idea that somebody's going to go straight to super intelligence and then drop it on the rest of the world, I think he's kind of softened on that a little bit. But that general pattern is I think if there's one thing that OpenAI probably did have, the iterative deployment idea and giving people a sense of where we are and not keeping the whole thing under a basket somewhere, I think that was one of the things that seems like it's aged pretty well in my situation so far. My earliest perception of the person advocating for this was Paul Cristiano, his takeoff speeds post, pushing back against. I suppose what he saw is predominantly the MIRI perspective at the time, like, oh, we're going to We're going to build the thing in secret. Frankly, I don't want to comment on-- I don't know what Mary's objectives were, but I know that they were trying very hard to not leak any information about their alignment research in some areas. Other areas, they published great papers and so on. But Paul Cristiano at the time was pushing back against this kind of-- he thought that fast takeoff would happen if you had a bunch of dry tinder lying around. had tons and tons and tons of GPUs, and then we stopped research for a year and then started again. Well, you'd expect a steeper growth. We're seeing this in terms of very, very fast followers. This is not just a phenomenon in AI and economies. Epoch recently did a study where they showed the pace of new AI companies approaching the frontier is just so much faster than the pace of which the frontier moves because there's an abundance of chips, there's an abundance of data and methods. and so on. And it's the same with like, you know, catch up economies and so on in the world. So I think that Paul Cristiano, you know, he was right in the sense that like if society is to cope and adapt to AI, then having gradual release and diffusion of technologies is better from that perspective. There's another perspective which says like it's that very gradual release or something that ensures continual VC reinvestment to drive the engine to actually make the progress. Whereas in the other world actually you just wouldn't build AGI because like perhaps in that world, like no one can build it without hundreds of several hundred billion dollars, maybe, you know, a trillion or something. I don't know. I can't say. I certainly think that we're now in the world where it does seem better to have gradual release of models than to have it all kind of hit us at once. Well, I always value the opportunity to get perspective from someone like you who is such a connector and at such a central node with so many mentors and mentees and all the kind of flows of information and talent flows that you are so close to. But we should probably narrow focus a little bit and talk about what you guys are actually doing at MATS. And I'll put maybe a timestamp in the intro so people can also, if they want to get right to the core MATS stuff, they can Zoom ahead and join us, skipping over some of the higher level stuff. Why don't we do just kind of a quick rundown on like, what are the different tracks, I think you call them streams of work that are happening in the MATS program today? Maybe like a little waiting or sort of, you know, what you're most excited about. Then we can go into kind of your assessment of the AI safety labor market, which I think is really interesting and unique, and we'll take it from there.…

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