[pilooch]

My take on intelligence over the past 20y has been it is high quality / efficient search of immense state spaces.

"Solving intelligence" as a famous corporation motto, might just be improving state-space search.

Humans are incredible at state space search, it's obvious as soon as you consider the potential data pointsnof any problem we face every day, from washing dishes to designing algorithms.

[Retric]

You can abstract basically anything to state space search + optimization. It’s essentially too wide a classification to be that useful.

[twofornone]

But that's literally what ML training does. Just like a human, neural nets learn heuristics to take advantage of the fact that of all the possible mappings of inputs to outputs, there are actually vanishingly few output states that are valid. Arguably all learning is indeed a reduction of state space, be it by human or machine.