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Comment on Self-Adapting Language Modelsparent

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I just got sucked into this idea recently! After some success with using genetic algorithms to clone voices for Kokoro I wondered if it would be possible to evolve architecturers. So interested in the idea of self assembled intelligence, but do wonder how it can be made feasible. A hybrid approach like this might be for the best given how llms have turned out.

So the issue with genetic algorithms / genetic programming is you need a good way to handle the path the population takes. It is more reinforcement than y = f(x) for deep learning f() is what the nn is computing. X and y is the training data.

Finding a good scoring algorithm is hard as it is so easy for a GA to cheat...

Source: experience

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