Google DeepMind's Co-Scientist Achieves Full Loop in Physical Labs
AI寒武纪 · wechat · 2026-08-29
Google DeepMind, in collaboration with multiple universities, launched the Co-Scientist system, achieving a full automated closed loop from theoretical hypotheses and physical experiments to paper writing, with validated breakthroughs in materials science, synthetic biology, and computer science.
Materials Science (2D Material Synthesis):
- The system proposed replacing toxic gases with solid hexachloroethane to synthesize MXene via kinetic reasoning.
- Following AI instructions, humans performed 25 iterations in a tube furnace, successfully synthesizing the target 2D crystal with matching XRD and TEM data.
- The system also generated machine code to control CVD equipment, successfully preparing monolayer semiconductors like MoS2 in a zero-shot setting.
Synthetic Biology (Colony Morphology Prediction):
- The system built an end-to-end visual prediction pipeline, accurately predicting E. coli colony morphology changes under different inducer concentrations.
- Prediction curves matched wet lab results closely on metrics like radius and eccentricity, correctly distinguishing non-reactive control groups.
Computer Science (Autonomous Architecture Evolution):
- The system autonomously designed the medical consultation architecture AgentH, outperforming mainstream models like GPT-4.1 and Claude Opus on HealthBench.
- Doctor double-blind reviews indicated significantly lower potential for clinical harm compared to baseline models.
Academic Integrity:
- Introduced mathematical penalties and mandatory log verification, reducing severe result hallucination rates from 90% to 4% and plagiarism from 60% to 16%.
Related event: Google DeepMind's Co-Scientist Extension Brings AI into Real-World Labs(30 posts)→
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