Researchers show AI models can "reproduce": mating by complementary strengths, no gradient descent
rvp · x · 2026-10-02
A new paper introduces a bottom-up way to evolve AI: the system starts with a population of random neural networks and applies rules of nature — pairing models with complementary strengths so they mix weights and pass traits to offspring, without a single line of gradient descent. A sharp contrast to the top-down training paradigm, described as turning AI development into literal biology.
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