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

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).