Evolving Code with A Large Language Model · HackerPapers discussions

Evolving Code with A Large Language Model — mentioned by _delirium

Thu, 15 May 2025 00:19:51 GMT

Genetic programming systems have periodically made improvements to algorithms (dating back decades). Whether LLM-powered GP, which is effectively what this is, will be a step change or an evolution of that is still an open question I think. I'm also a little wary of reading too much into the recursive self-improvement idea, because "the GP system can use GP to improve the GP system itself!" is a very old idea that just has never worked, although I realize that isn't proof that it won't eventually work. Some related work from a different company: https://sakana.ai/ai-cuda-engineer/ And some…

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Evolving Code with A Large Language Model — mentioned by dimatura

Mon, 07 Apr 2025 06:46:14 GMT

Note that genetic programming is a specific subset of genetic algorithms that focuses on searching for "programs" (hence the name), typically encoded in the form of a tree structure similar to an AST, though other representations exist. In theory, you could use GP for almost any situation where you'd want to synthesize a mathematical expression or piece of code for which you have a criteria to optimize (i.e. "fitness"). In practice, since GPs are basically just semi-randomly searching a huge combinatorial space, they tend to work best in low-dimensional problems, ideally with a fitness…

Paper and discussion history. A mention is not an endorsement.