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I think Feynman’s was the best answer to the “why” question: https://www.lesswrong.com/posts/W9rJv26sxs4g2B9bL/transcript-richard-feynman-on-why-questions https

• skybrian 7y ago
  I think that's different, first because the neural network has an indirect relationship with the physics, and second because Feynman was operating under a handicap: he was asked to give an explanation in terms the listener (who didn't know any physics) would understand. In the case of folding, when we ask "why" we might be asking why it folds one way and not the other. Causation has consequences, like for example we might want to know whether a small change to one part of the protein will significantly change how it folds. We might say some amino acids cause the fold and others don't. If you understand the mechanism behind something, you can control it better. Or, if you're interested in machine learning, you could ask what changes to the neural network make prediction better or worse and which parts of it matter the most, when it might make mistakes, and so on.