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Google Research

How governments and organizations are leveraging Google’s AI breakthroughs for crisis resilience Three new satellites join the fight against wildfires. The latest AI news we announced in June 2026 Towards a world where no one is surprised by a natural disaster New research shows how AMIE, our medical AI, could help manage health conditions. The latest AI news we announced in May 2026 A new experiment brings better group meetings to Google Beam Gemini for Science: AI experiments and tools for a new era of discovery Evolving expectations of what’s possible Quantum frontiers may be closer than they appear Building superconducting and neutral atom quantum computers Our new study explores how AI can reduce the climate impact of air travel. Broadening advanced AI education across Africa Groundsource: using AI to help communities better predict natural disasters Honoring the art of the possible this International Women’s Day How our open-source AI model SpeciesNet is helping to promote wildlife conservation The latest AI news we announced in February The quantum era is coming. Are we ready to secure it? Natively Adaptive Interfaces: A new framework for AI accessibility How we’re helping preserve the genetic information of endangered species with AI We’re announcing the 12 recipients of our AI for Science fund Google's year in review: 8 areas with research breakthroughs in 2025 4 highlights from Google Beam in 2025 The 7 finalists in the XPRIZE Quantum Applications competition Deepening our AI research partnership with Tel Aviv University At our Research@ Poland event we shared how AI is helping us solve big challenges.
4 ways researchers are collaborating with Co-Scientist to solve big problems
Joel Meares · 2026-06-10 · via Google Research

Learn more about Co-Scientist and the impact it’s already making.

General summary

Researchers are now using Co-Scientist, an artificial intelligence system designed to help solve complex problems in the life sciences. The tool uses specialized agents to generate, debate, and refine new hypotheses, acting as a virtual partner for scientific discovery. You can explore how this technology accelerates research by visiting the Google DeepMind blog or testing the new experimental tool.

Summaries were generated by Google AI. Generative AI is experimental.

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This content is generated by Google AI. Generative AI is experimental

[[duration]] minutes

We recently published our latest research on Co-Scientist, a collaborative AI designed for structured scientific thinking to help researchers develop new hypotheses in life sciences and beyond.

The system is made up of a coalition of specialized agents that work together in three distinct phases. First, Co-Scientist generates ideas through agents that propose hypotheses and explore a wide variety of research avenues. Next, it debates ideas, with one agent that acts as a virtual peer reviewer before another pits vetted ideas against each other in an “idea tournament.” Finally, it evolves ideas, with agents that refine, combine and improve the best hypotheses, as well as agents that synthesize the research for a human scientist. A supervisor agent ties the system together, breaking down high-level research goals into individual tasks, allocating resources and coordinating specialized agents to work in parallel.

Since sharing early research last year, we’ve been developing and testing the system with scientists and research teams globally tackling complex scientific problems. Read about just a few ways it’s already having an impact:

Co-Scientist will be available to researchers through Hypothesis Generation, a new experimental tool developed across Google DeepMind, Google Research, Google Cloud and Google Labs. Learn more about Co-Scientist and how researchers are using it on the Google DeepMind blog.

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