Co-Scientist: A multi-agent AI partner to accelerate research

Introducing a collaborative AI partner for researchers to develop new hypotheses in life sciences and beyond.

Every great scientific breakthrough begins with a single, transformative idea. The spark of discovery relies on a researcher's ability to connect disparate facts and formulate the right hypothesis to test. But in an era of information overload and increasingly complex challenges, the search for these needle-in-a-haystack ideas has become a significant bottleneck for progress.

We believe AI can help dramatically accelerate the pace of breakthroughs by serving as a dedicated partner in the generation and refinement of breakthrough scientific hypotheses.

We thank our teammates Ali-Cowen Rivers, Anna Trostanetski, Barnaby James, Bill Byrne, Boon Panichprecha, Charlie Taylor, Diego Ballesteros, Hussein Hassan Harrirou, Ieva Grublyte, Ivan Lee, Jakob Oesignhaus, James Walker, Jorge Barrios, Laurynas Tamulevičius, Luka Važić, Meet Shah, Mihai Ciorobea, Natasha Latysheva, Nicolas Stroppa, Nir Kerem, Saz Basu, Sebastian Nowozin, Taylor Applebaum, Team Rakket and, Thomas Wagner and Yaniv Carmel for their technical support.

Finally, we thank Ali Eslami, Andy Berndt, Ankur Jain, Anna Koivuniemi, Clemens Mayer, Dale Webster, Greg Corrado, Jason Freidenfelds, Jeff Dean, Joelle Barral, John Jumper, John Platt, Josh Woodward, Karen DeSalvo, Koray Kavukcuoglu, Michael Brenner, Michael Howell, Noam Shazeer, Oriol Vinyals, Parthasarathy Ranganathan, Ronit Levavi Morad, Royal Hansen, Scott Huffman, Srini Narayanan, Susan Thomas, Thomas Kurian, Zoubin Ghahramani and Sundar Pichai for their support of this work.

Today, in Nature we published our latest Co-Scientist research, introducing a new multi-agent AI system built with Gemini that iteratively generates, debates, and evolves novel hypotheses for complex scientific problems.

We are making the Co-Scientist system available to individual researchers through Hypothesis Generation , a new experimental tool jointly developed across Google DeepMind, Google Research, Google Cloud and Google Labs. We’ll begin rolling out in the coming weeks and researchers can register their interest at labs.google/science .

Since sharing our early research last year, we’ve been developing and testing Co-Scientist together with teams who are leveraging it to tackle challenging problems - from antimicrobial resistance and plant immunity to liver fibrosis . We’re excited to share some of the ways it is already being applied across fundamental biology, the natural sciences, and engineering.