Just talking out of my ass here but it feels likely to me that the natural algorithm would be randomly learn to parse n features, and then do a sort of multi ar

Just talking out of my ass here but it feels likely to me that the natural algorithm would be randomly learn to parse n features, and then do a sort of multi arm bandit process to determine which features to keep and also how to use them via positive and negative emotional/hormonal triggers. Neural nets use back prop to infer bottoms up what features define what features define what features which are eventually useful for a final prediction. But we don’t really see evidence of backstop in biology. That is to say, biology probably uses an algorithm to passively identify patterns arbitrarily, unlike neural nets which attempt to identify the patterns that solve for a given task. The latter just theoretically requires a lot of information before a space can be well defined. The former doesn’t.