An extension of the Gemini model designed a safe precursor route for 2D MXene synthesis and predicted the swarming morphology of engineered E. coli. Developed by Google DeepMind, Co-Scientist proposed lab recipes that produced 3 atom thin semiconductors on the first attempt and created an inference architecture that outperformed six frontier models on the HealthBench Hard and Professional benchmarks.

The tool transitions AI agents from simulations to closed-loop science by interfacing with physical hardware. In tests of AI-generated research, the system reduced serious fabricated results in papers from 90% to 4% and validated its biological predictions against unpublished wet-lab morphological measurements.

Sign in to suggest edits

Key sources

  1. SOURCE@timstro“beating six frontier models on length-adjusted HealthBench”x.com
  2. SUPPORT@_philschmid“cut serious fabricated results in AI-written papers from 90% to 4%”x.com
  3. SUPPORT@deployedmind“A striking glimpse of closed-loop science”x.com
Markdown