OpenEvolve: Teaching LLMs to Discover Algorithms Through Evolution

(algorithmicsuperintelligence.ai)

52 points | by codelion 1 day ago

4 comments

  • jasonjmcghee 1 day ago
    It doesn't mention it in the article, but guessing this is based on / inspired by AlphaEvolve?

    Though I'm not sure the public can access AlphaEvolve yet.

    (https://arxiv.org/abs/2506.13131)

    • gerdesj 1 day ago
      If AlphaEvolve is: "a quality-diversity search framework for algorithm discovery" then maybe.

      At the moment I'm mildly skeptical and uncertain of whether to twist or stick.

    • jasonb05 1 day ago
      Agreed, not mentioned.

      Nevertheless, I see a link to github for the OpenEvolve project [1] that in turn states:

      > Open-source implementation of AlphaEvolve

      [1] https://github.com/algorithmicsuperintelligence/openevolve

  • DoctorOetker 1 day ago
    Very interesting that the LLM weights are co-evolved and reasoning skills improve!
    • viraptor 1 day ago
      What do you mean by this? I can't find anything there about modifying the used LLMs and the hosted ones wouldn't be possible to change. Do I misunderstand the convolved part you mentioned?
      • DoctorOetker 23 hours ago
        you are correct, on re-reading they only evolved the prompts ...
  • N_Lens 1 day ago
    Some cool optimisations here: MAP elites, island models to prevent premature convergence & fast rejection of bad candidates.

    What's particularly interesting is the meta level insight: The system discovered scipy.optimize.SLSQP for circle packing - a completely different algorithmic paradigm than it started with. It's genuinely discovering new approaches, not just parameter-tuning.

  • quantbagel 1 day ago
    Sakana.ai improved on this by honing in on sample efficiency iirc with shinkaevolve (which is open source and not an ai slop project)