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> I wonder if this replicates to things like chess/go - for a computer trained on the same number of games that a human is, is the computer still able to outperform a human?

The first computers to beat (and completely surpass) the best human beings at chess were not trained on anything. Just efficient search techniques and human feedback through heuristics/opening books.

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red black and minmax algorithms were not really useful, and heuristics are a kind of laborious encoding of experts human knowledge into code, so they were still trained, in an hardcodes manner.

But overall, yes, the current state of machine learning relies on huge brute force compared to animal learning.

Experts Chess players need to play many games to acquire sufficient intuitive knowledge, but they converge orders of magnitude faster than current algorithms.

This weakness might be relevant later, for very dynamic and adaptable systems.

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