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I understand your point, and I'm having trouble articulating this thought, but I think with inductive bias you can structure your net such that it is primed to
by allovernow 7y ago
I understand your point, and I'm having trouble articulating this thought, but I think with inductive bias you can structure your net such that it is primed to naturally learn certain behaviors that are more complex than the Shannon entropy required in the encoding DNA. The minimal structural information combined with environmental interaction can produce far richer information content, past the limit of the original DNA, but from a design perspective your actual code is very compact because you gain the rest of the knowledge required for innate behaviors naturally from the environment.
- asdff 7y agoIt's interesting to think about all this. Everything DNA encodes is responses to the environment. On the molecular level, proteins are only functional at certain temperatures, pressures, and pH levels. On the cell level, certain proteins might only be found in specific areas, and essential amino acids might be harvested from the environment rather than produced by the cell itself. On the organism level, we are predisposed to shiver if it's too cold or sweat if it's too hot, an uncomfortable feeling, so innately we go to where the climate is milder and won't kill us. We clothe ourselves and that range is expanded, suddenly there is a selective advantage for being able to clothe yourself, just like there is to be a white beetle on a white sand beach instead of a green one visible to predators, or a cell that's able to just mooch someone elses amino acids rather than expend energy making their own.
- inimino 7y agoAs the article points out, Shannon information really is the wrong benchmark. Kolmogorov complexity and the busy beaver sequence should demonstrate that there's very little reason to argue for any sort of genetic bottleneck on gene count grounds.