Hmm, it's more that LLMs can be used for population -> candidate solution generation, e.g. operators in a GA.
The innovation is novelty search, e.g. divergent rather than convergent optimization, paired with the capability that LLM genetic operators and representations unlock.
At least, that's my high-level take. google's alphaevolve is the same kind of thing but focused on convergent ga's (i think).
The innovation is novelty search, e.g. divergent rather than convergent optimization, paired with the capability that LLM genetic operators and representations unlock.
At least, that's my high-level take. google's alphaevolve is the same kind of thing but focused on convergent ga's (i think).