That's a good observation, though I'm not sure it's just a matter of longer range correlations, i.e. fixable by merely adding more computational power. The trut

That's a good observation, though I'm not sure it's just a matter of longer range correlations, i.e. fixable by merely adding more computational power. The truth problem is fundamentally different than what those neural networks are trying to solve. We got the learning part almost right, we have made no progress towards understanding. I might be completely off the mark, my knowledge of AI is very limited. But earlier today, while reading on Lisp's history and it's demise during the AI Winter, I very much enjoyed a Wikipedia article describing how symbolic AI, the main paradigm of AI research from the 60s to the 2000s, solves a completely different problem than the currently hyped neural networks—which are very good at learning, but not much more. We might need a complementary, unifying model of both approaches to reach AGI. https://en.m.wikipedia.org/wiki/Symbolic_artificial_intelligence#Controversies https://en.m.wikipedia.org/wiki/Symbolic_artificial_intellig...