(As usual for my questions, the focus here is “[advanced math]… that’ll be needed for technical AI alignment”.)
Could someone with good-but-not-great working memory, and infinite time, learn all any known math? Or is there some “inherent intuitive complex nuance” thing (involving e.g. mental visualization) they need?
Reductionism would suggest the former (with some caveats), but computational intractability in real life might require the latter anyway. Human brains, paper, and code may not be able to bridge the “gap” between (less-precise proofs backed by advanced intuition) and (precise proofs simple enough for basically anyone to technically “follow”).
And, for practical reasons, I wonder how “continuous” that gap is. E.g. how the tradeoff/tractability changes as one’s working memory increases, or how the gap changes for different subfields of math.
In my experience as a working mathematician, intuition is crucial.
But I don’t know if my experience is universal (e.g. there are mathematicians with different types of thinking, e.g. algebraic thinking vs geometric thinking is an often quoted dichotomy).
My priors do point towards intuition always being super-useful (and also towards intuition usually being somewhat easier to develop than purely mechanistic skills). But my mechanistic skills have always been so-so, people might differ from each other in a rather radical fashion...