going to be extremely funny if AI was solved in the 90s and the answer ends up being really inefficient versions of the mixture models we already had.

which is already partly true looking, as KANs are .. kinda related to what gaussian mixtures actually did, in the sense of 'learning' curves in to the mixture nodes and re-constructing functions that way.

there's even a paper from years ago where you can just use gradient descent on mixture models and it works better than the old EM algorithm did.