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We know how they are formed(and how to form them), we don't know why forming in that particular way solves the problem at hand.

Even this characterization is not strictly valid anymore, there is a great deal of research into what's going on inside the black box. The problem was never that it was a black box(we can look inside at any time), but that it was hard to understand. KANs help some of that be placed into mathematical formulation. Generating mappings of activations over data similarly grants insight.






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