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OpenEvolve: Teaching LLMs to Discover Algorithms Through Evolution

28 points

7 hours ago

| 4 comments

| algorithmicsuperintelligence.ai

| HN

6 hours ago

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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)

15 minutes ago

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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

5 hours ago

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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.

5 hours ago

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Very interesting that the LLM weights are co-evolved and reasoning skills improve!

4 hours ago

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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.

4 hours ago

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

12 minutes ago

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Yep, ShinkaEvolve described here: https://sakana.ai/shinka-evolve/ and available here: https://github.com/SakanaAI/ShinkaEvolve