Evolutionary algorithms

Solving the Wrong Problem Works Better - Robert Lange

Solving the Wrong Problem Works Better - Robert Lange

Robert Lange from Sakana AI discusses Shinka Evolve, a framework combining LLMs with evolutionary algorithms for open-ended program search. The conversation explores how Shinka Evolve addresses the limitations of systems like AlphaEvolve by co-evolving problems and solutions, its sample-efficient architecture using UCB bandits and quality-diversity search, and its applications in circle packing, competitive programming, and evolving MoE loss functions. The discussion also delves into the philosophical debate on whether these systems produce true novelty or are parasitic on their starting conditions, and the future role of the "AI Scientist" as a human co-pilot.

29.4% ARC-AGI-2 🤯 (TOP SCORE!) - Jeremy Berman

29.4% ARC-AGI-2 🤯 (TOP SCORE!) - Jeremy Berman

Jeremy Berman, winner of the ARC-AGI v2 public leaderboard, discusses his novel evolutionary approach that refines natural language descriptions instead of code. He explores the idea of building AI that synthesizes new knowledge by constructing deductive "knowledge trees" rather than merely compressing data into "knowledge webs," touching on the fundamental challenges of reasoning, continual learning, and creativity in current models.

No Priors Ep. 120 | With Google DeepMind’s Pushmeet Kohli and Matej Balog

No Priors Ep. 120 | With Google DeepMind’s Pushmeet Kohli and Matej Balog

Push Kohli and Máté Balog from Google DeepMind discuss AlphaDev, an AI agent that uses large language models and evolutionary search to discover novel, more efficient algorithms for fundamental computer science problems, marking a significant step in AI's ability to generate creative and practical solutions.