Gwern: prediction

Transcript context

…If intelligence is just search over Turing machines—and of course intelligence is tremendously valuable and useful—doesn't that make it more surprising that intelligence took this long to evolve in humans? Not really, I would actually say that it helps explain why human-level intelligence is not such a great idea and so rare to evolve. Because any small Turing machine could always be encoded more directly by your genes, with sufficient evolution. You have these organisms where their entire neural network is just hard-coded by the genes. So if you could do that, obviously that's way better than some sort of colossally expensive, unreliable, glitchy search process—like what humans implement—which takes whole days, in some cases, to learn. Whereas you could be hardwired right from birth. For many creatures, it just doesn't pay to be intelligent because that's not actually adaptive. There are better ways to solve the problem than a general purpose intelligence. In any kind of niche where it's static, or where intelligence will be super expensive, or where you don't have much time because you're a short-lived organism, it's going to be hard to evolve a general purpose learning mechanism when you could instead evolve one that's tailored to the specific problem that you encounter. You're one of the only people outside OpenAI in 2020 who had a picture of the way in which AI was progressing and had a very detailed theory, an empirical theory of scaling in particular. I’m curious what processes you were using at the time which allowed you to see the picture you painted in the “Scaling Hypothesis” post that you wrote at the time.…

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