The intelligence explosion comes from speed and research taste, not headcount

From the conversation

I know they’re increasing headcount, but they don’t seem to treat this as the kind of bottleneck that it would have to be for millions of them in parallel to be rapidly speeding up AI research. There’s this quote that “one Napoleon is worth 40,000 soldiers” was commonly a thing that was said when he was fighting. But 10 Napoleons is not 400,000 soldiers. Right? So why think that these million AI researchers are netting you something that looks like an intelligence explosion? So previously I talked about three stages of our takeoff model. First is you get the superhuman coder. Second is when you fully automated AI R&D, but it’s still at basically human level, it’s as good as your best humans. And then third is now you’re in super intelligence territory and it’s qualitatively better. In our guesstimates of how much faster algorithmic progress would be going, the progress multiplier for the middle level, we basically do assume that you get massive diminishing returns to having more minds running in parallel. And so we totally buy all of that. Yeah. And then I think the addition to that is the question, then, why do we have the intelligence explosion? And the answer is: combination of that speed up and the speed up in serial thought speed. And also the research taste thing. Here are some important inputs to AI R&D progress today: research taste.…