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> I often wonder what Minsky would think about the current generation of AI.

I suspect he'd react similiarly to Chomsky who in, a recent interview (MLST), was highly critical of LLMs as "not even a theory" (of what, i'm not sure... language aquisition? language production? maybe both)

Minksy was more broadly critical of NNs because it wasn't clear how difficult the problems they solved actually were. Until we had a better measure of that, saying "I got a NN to do X" is kind of meaningless. He elaborates in this excellent interview from 1990, beginning at 45:00: https://youtu.be/DrmnH0xkzQ8?t=2700

It's interesting how it is almost as though if you don't understand something thoroughly that you can't pluck the fruits from it. But if that were really true we wouldn't be able to appreciate art either, nobody can point at the reasoning behind a work of art to a degree that would satisfy those criteria, you're either moved by it or you aren't regardless of how it came about.

Present day AI is much like that: we do not understand it in detail but we understand the general ideas well enough to keep improving on it. Maybe one day we'll understand it to the degree that would satisfy a Minsky or a Chomsky, but until then we'll be happy to use the results, regardless of what makes it all tick.

I suspect - but of course absolutely no way to prove this yet - that all that such understanding would do would be to result in massive optimizations, not necessarily new kinds of output. Though such an optimization may well be so strong that it will serve as a qualitative change. And if in the process we discover something about how our own minds work so much the better but that wasn't the goal to begin with, unless you want the specification for an implementation of the algorithm of consciousness. It may well simply be something messy rather than orderly.

>My guess is that he'd be critical, because while their accomplishments are pretty impressive on the surface, they do very little to explain the mechanics of how humans perform complex problem solving, or really any kind of psychological model at all, and that is what he was really interested in.

The success of machine learning/neural nets--in no small part because of the amount of computation resources we can throw at them--has really led to hogging the attention compared to fields like cognitive science, neurophysiology, and so forth. Work is certainly going on in other areas but I'm still struck that some of the questions that were being asked when I took brain science as an undergrad many decades ago (e.g. how do we recognize a face as a face?) are still being asked today.

Given that ML is the thing that's getting the flashy results, it's not surprising it's the thing in a limelight--even if there's a suspicion that it maybe (probably?) only gets you so far without better understanding how learning happens in people (and other animals) and other aspects of thinking and intelligence.

It's likely also the case that brains don't work the way LLMs do. After-all, we evolved to survive and reproduce in the real world, not generate text or images. I consider AI to be a kind of alien intelligence that approximates human intelligence in some ways, and supersedes it in others (where computing power can be fully leveraged such as AlphaGo being able to play itself a million times in a few hours).