[manifestsilence]

This is interesting, as this appears to be similar to the difference between Daniel Kahneman's System1 and System2 modes of human thought. ML is perhaps beginning to approach our subconscious, associative intelligence. This shows up in its excellence for things like image processing, which we do instantly and automatically. Perhaps growing the tech equivalent of a prefrontal cortex is what's going to be hard, or require a different approach.

[_0ffh]

We're getting there. I have the feeling more an more people subscribe to the hunch that combining symbolic (GOFAI) with subsymbolic (PDP/NN) techniques is the way forward. Research is going on, an example is the Neuro-Symbolic Concept Learner described in this [1] paper.

[1] https://deepai.org/publication/the-neuro-symbolic-concept-le...

[Symmetry]

Yeah, that seems to be part of the reason that AlphaZero, which has its System2-like alpha-beta search seems so much smarter than AlphaStar which plays like a brilliant somnambulist.

Maybe if we had some way of abstracting out the things a machine learning system implicitly learns so we could deal with them in a more classical AI-like way?

[davidhowlett]

Instead of an alpha-beta search, AlphaZero uses a general-purpose Monte Carlo tree search (MCTS) algorithm. Source: https://science.sciencemag.org/content/362/6419/1140.full

I agree with your comment about System 2 like reasoning not being common right now. I am not an expert in the field but the closest thing I have seen to learned planning is: https://arxiv.org/pdf/1911.08265.pdf