Originally published on AI Tech Connect.
What AlphaEvolve actually does At its core, AlphaEvolve is an automated algorithm discovery system. You give it a problem — say, "write a faster implementation of this linear algebra kernel" — and it iteratively generates candidate solutions, evaluates them against an automatic scoring function, selects the best-performing variants, and uses those as the basis for the next generation of mutations. The loop runs until it converges on something that genuinely outperforms the prior best-known approach. The architecture relies on two Gemini 2.0 models playing complementary roles. Gemini 2.0 Flash handles breadth: it generates large numbers of candidate algorithm variants quickly, exploring the search space widely without dwelling on any single direction. Gemini 2.0 Pro handles depth: once…
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