I see. Given this, I think “zero-shot learning” makes sense but “zero-shot reasoning” still doesn’t, since in the former “zero” refers to “zero demonstrations” and you’re learning something without doing a learning process targeted at that specific thing, whereas in the latter “zero” isn’t referring to anything and you’re trying to get the reasoning correct in one attempt so “one-shot” is a more sensible description.
I was imagining something like “zero failed attempts”, where each failed attempt approximately corresponds to a demonstration.
Are you saying that in the slow-takeoff world, we will be able to coordinate to stop AI progress after reaching AGI and then solve the full alignment problem at leisure? If so, what’s your conditional probability P(successful coordination to stop AI progress | slow takeoff)?
More like, conditioning on getting international coordination after our first AGI, P(safe intelligence explosion | slow takeoff) is a lot higher, like 80%. I don’t think slow takeoff does very much to help international coordination.
I was imagining something like “zero failed attempts”, where each failed attempt approximately corresponds to a demonstration.
More like, conditioning on getting international coordination after our first AGI, P(safe intelligence explosion | slow takeoff) is a lot higher, like 80%. I don’t think slow takeoff does very much to help international coordination.