Around 2000 I took an AI course at the University of Guelph. I don’t think I learned too much. We didn’t talk about neural networks, as far as I can remember. My end of term project was, I think, a pathfinding algorithm wearing an AI costume. There were certainly no discussions of transformers. No CUDA. No PyTorch. None of that existed.
But what I remember doing a lot of was coding in Lisp - a lot of Lisp in the dark University of Guelph CIS lab.
Yeah the intelligence is still in the model. The promise of symbolic AI is about logic programming/ formal semantics not recursive loops.
To a large extent the idea has failed because it proved too hard to get non-experts to represent systems formally.
I still think there’s potential value in a hybrid approach - e.g. get language models to do the representation then let them use formal reasoners/ verification instead of hallucinating.