"AI means we can literally brute-force any scientific mystery by trying out millions of algorithms..." This is exactly wrong. If true, then AI could readily s

"AI means we can literally brute-force any scientific mystery by trying out millions of algorithms..." This is exactly wrong. If true, then AI could readily solve any human-level problem we could throw at it. But AI still can't master any of the basic skills inherent in human children, much less in adults working in construction crews, or health care aides, or janitors, or even just driving a car. AI's ability to build robots capable of even basic tasks like giving a haircut or climbing over broken objects littering a stair -- they're nonexistent, and even after a decade of deep learning, they're not getting appreciably better. Deep learning has shown us two things: 1) deep NNs can learn how to solve approximation problems astonishingly efficiently and capably. That's AlphaGo and AlphaFold. And 2) a lot of what humans assumed to be signs of intelligence, like playing go and chess, understanding voice and speaking, recognizing objects in images -- these are just "monkey see, monkey do" skills based in probabilistic pattern matching, which deep NNs can do very, very well. But cognitive skills that require reasoning -- deduction, induction, and the recognition and rejection of contradiction -- these must identify relevant domain knowledge (semantics) and the ability to reason about it, not just the efficient matching of a pattern in a matrix using a GPU. Alas, the effective and scaleable means of solving these problems still remain a total mystery. So if you can generate a zillion clueless hypotheses per second using the very best deep NN, it will still drive over a cop dressed like a clown who's waving his arms the path of your smartcar, nor will it ever invent general relativity.