The field of Symbolic Artificial Intelligence which is still (for now…) a majority of what is taught in American AI courses IME. It’s also the de facto technical translation of Cognitive Science. There’s a long debate between the two “camps”, which were called the neats (Turing, Minsky, McCarthy, etc) and the scruffies (the people behind ML).
The scruffies spent decades being shit on by the other camp as being lazy and simple-minded (due to a perception of “brute forcing” problems), only to find more success than most of them had ever imagined. I think anyone who says they were confident that ML-based NLP models could one day not only predict text, but also perform intuition, is either a revisionist or a prophet.
The whole Neat field got kinda stuck when we translated the low hanging fruit to symbolic algorithms (Simon & Newell’s Problem Solving being the most interesting IMO), but we had no way to test them. As another commenter alluded to, these systems lacked any “intuitive”(aka subconscious, fuzzy, approximate) faculties, so their high-level strategies could never work in the messy real world, mostly because it’s pretty impossible to definitively tell what information is relevant and what information isn’t to any given problem. This is called the problem of contextual “attention and selection”, and the problem more generally “the frame problem”.
Now that we have systems that mimic human subconscious intuition AND systems that mimic human self conscious reason, of course the next step is… declare complete victory and abandon the latter group forever as trash, apparently.
This is all a super biased take from someone who only got into this specific debate last year, tho I promise I do have some relevant credentials and have been working full time on this for close to a year. I strongly believe that LLMs are about to unlock the first (true) Cognitive Revolution.