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This work proposes a generational genetic algorithm to coordinate specialized large language model agents that integrate mechanistic arguments, reconsider assumptions, and assess evidence and testability that advances a vision of autonomous science in which AI research teams achieve a capacity for discovery beyond that of individual models.
Models that excel in prediction often falter in mechanistic reasoning, revealing hidden flaws in their logic and understanding of cellular context.
PCN accelerators can get a 3x speedup just by intelligently partitioning point clouds and reusing features within localized "islands."
