AI agents trained to run experiments in wet labs
Google Research: Grounding AI agents in biological reality: Building blocks for autonomous wet labs
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AI agents are being trained to run experiments in physical laboratory settings by combining artificial intelligence with robotic lab equipment. This matters because frontier AI systems struggle with reasoning about three-dimensional physical spaces and real-world constraints, which limits their ability to navigate the enormous number of possible molecular designs needed for drug discovery. The research addresses this gap through a framework that gives AI agents live tracking of lab conditions and safety checks before executing experiments, then learns from actual experimental results across repeated cycles. In test cases with protein-binding molecules, agents improved their design accuracy significantly by analyzing wet-lab readouts and adjusting their strategies accordingly, demonstrating how AI can self-improve through real-world scientific feedback rather than simulation alone.
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