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AI Improves at Improving Itself Using an Evolutionary Trick Critically, the DGMs outperformed an alternate method that used a fixed external system for improving agents With DGMs, agents’ improvements compounded as they improved themselves at improving themselves The DGMs also outperformed a version that didn’t maintain a population of agents and just modified the latest agent
How Self-Improving AI Like DGM is Transforming Software . . . Developed by Sakana AI, this new system uses evolutionary programming and recursive self-improvement to autonomously refine its capabilities Unlike traditional AI models that rely on static
The Darwin Gödel Machine: AI that improves itself by . . . DGMs leverage foundation models to propose code improvements, and use recent innovations in open-ended algorithms to search for a growing library of diverse, high-quality AI agents Our experiments show that DGMs improve themselves the more compute they are provided
World’s First Self-Improving Coding AI Agent: The Darwin . . . The Darwin Godel Machine is a self-improving AI system that uses evolutionary programming combined with frozen foundation models to iteratively modify and enhance its own code and workflows, particularly for coding tasks
The Dawn of Self-Evolving AI: How the Darwin Gödel Machine is . . . The Darwin Gödel Machine is an early but exciting step toward AI that keeps getting better By using real-world tests instead of hard proofs and mixing self-change with evolutionary variety, it makes self-evolving AI more practical The success of DGM on tough coding tasks shows that self-evolving agents can match or beat systems made by hand