I thought the point of the article wasn't that a particular approach to learning has intrinsic limits, but that underdetermination of the pattern to be learned

I thought the point of the article wasn't that a particular approach to learning has intrinsic limits, but that underdetermination of the pattern to be learned by the available data poses fundamental limits to what any learner could hope to discover. The example motivating the discussion in such; even a perfect learnenr would hardly have any criteria to prefer one solution to another. Guess simplicity arguments could play in this example, if they weren't so vague, but even that doesn't happen in the general case. That has to be true, for machines and humans alike. So ofc there's motivation to think about what comes after deep learning - but this isn't it, for that too, whatever it is, would be just as hopeless in examples such as there.