I think lots of simple problems can serve as appropriate AI benchmarks (including chess) as long as we constrain them to measure *generalization power* and not *skill*.
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Similarly, I don't want to see a deep learning model beat humans at a MOBA (which of course it can, given enough data), I want to see a model trained on a few thousands of plays, given a *completely new* character, doing just as well as a human in the same situation
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To make progress on AI, we must measure abstraction strength and generalization power, not plain skill (while ignoring *how* that skill was obtained). Focusing on skill is a bit like looking only at the speed of a vehicle but ignoring its energy consumption.
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Intelligence is about efficiently turning experience into generalization power. Skill at a given task, given infinite resources to get there, has no correlation with intelligence.
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Bingo. Most industrial problems don’t provide me with the luxury of synthesizing more independent data from nothing (only have what’s happened empirically), so I certainly sense ludic fallacy in recent AI/RL advances.
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