2026-10-07 13:33 UTC
A recent journal article attempts extending biological evolution from #ML!
Here is a stylized diagram of "double descent" by the paper author Steve Frank. The first descent (decrease in error on out-of-sample data) occurs as you add input variables to machine training. Generalization error enhances due to overfitting as you continue. A second descent *may* occur if you add even more input variables to machine training.
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@maugendre@hachyderm.io 2026-10-07 13:38
Why would that be (according to Steven Frank)? "The excess dimensions create large subspaces of equivalent training performance but varying generalization ability. Within these subspaces, learning dynamics preferentially reach simple smooth solutions that capture the general structure of the problem rather than its idiosyncratic details". Similarly for proteins: https://bsky.app/profile/john-mcbride.bsky.social/post/3mpycngozbs2j