Does anyone know the rough OOM of the “n” such that there are “n” technical AI researchers that would cause a 2x slowdown in frontier AI capabilities progress over the next year if they all quit?
Edit: I think my question was unclear. Let’s say that you know the history of every researcher at the top AI labs and have a really good idea of who the “best” ones are. You now get to pick “n” of them in order to maximally slow progress. They can be immediately replaced by additional hiring.
Thanks for this analysis. While it doesn’t directly answer the question I intended to ask, this is a surprising answer to the more practical question of “how much impact does a random researcher working on frontier AI have”, especially since it seems that you were, at every step, trying to make the impact as large as possible.
Is it reasonable to assume that contributions of the sample of researchers to software follow an 80⁄20 pareto distribution and that the population of the sample is about 10k? If so, I can make the relevant modifications here. The part I’m most curious about from people with a good understanding of these institutions is what the power law is like in contribution to research.