Vivek Natarajan

Out of all the announcements at @Google I/O today, this is the one closest to my heart - our foundational research on Co-Scientist was published in @Nature and we announced its broad availability via @GeminiApp for Science. When you are suffering from a disease, time is everything. As our collaborator and @StanfordMed Professor Dr. Gary Peltz reminds us, there are thousands of diseases out there with zero treatments. There is simply so much left to solve. Our goal with Co-Scientist has been to give scientists superpowers and help them get to these answers faster - compressing the scientific process from months and years down to hours and days. Much like Galileo's telescope helped us look into the stars, Co-Scientist is designed to help us make sense of the vast complexity of biological and scientific data. It is among the first examples of a truly general-purpose multi-agent system for scientific discovery. The core research question behind it was: How can an AI system engage in the rigorous, structured thinking that’s the hallmark of science and scientists? To tackle this, Co-Scientist builds on the principles of self-play and self-improvement underpinning @GoogleDeepMind breakthroughs like AlphaGo, generalizing them to scientific reasoning through self-debates. Since our preprint last year, we have further improved its capabilities and have been validating it in collaborations with scientists across over 100 institutions globally, spanning both academia and industry. And we are thrilled to see the emergence of a new form of AI-human scientist collaboration that's already leading to important new insights, discoveries and peer reviewed publications - from understanding antimicrobial resistance (published in @CellCellPress) to decoding plant immunity, to identifying new treatments for liver fibrosis (Advanced Science), cancer, neurodegenerative diseases like ALS and the grand challenge of aging. I have always believed AI's greatest promise is accelerating scientific discovery and advancing human health. My genuine hope for the future is that AI tools like Co-Scientist help democratize science, giving anyone, anywhere the means to pursue their child-like curiosity and change the world. This work was done with stellar team mates spanning @GoogleDeepMind @GoogleResearch, @googlecloud and @GoogleLabs especially Juro Gottweis (@Mysiak ), who is the heart and soul of this effort. Special thanks also to all our wonderful collaborators: Gary Peltz, @CostaT_Lab, @jrpenades, @_e_d_v_ , @iambyronic, @OpsBug, @jgooten, @omarabudayyeh Ritu Raman, Ryan Flynn, Filippo Menolascina, Velia Siciliano, Clare Bryant, Matt Onsum, Katherine Labbé and more. Nature paper link - lnkd.in/e8qBEJFv Google DeepMind blog - lnkd.in/etYeahMy Gemini for Science - labs.google/science.

Out of all the announcements at @Google I/O today, this is the one closest to my heart - our foundational research on Co-Scientist was published in @Nature and we announced its broad availability via @GeminiApp for Science. When you are suffering from a disease, time is everything. As our collaborator and @StanfordMed Professor Dr. Gary Peltz reminds us, there are thousands of diseases out there with zero treatments. There is simply so much left to solve. Our goal with Co-Scientist has been to give scientists superpowers and help them get to these answers faster - compressing the scientific process from months and years down to hours and days. Much like Galileo's telescope helped us look into the stars, Co-Scientist is designed to help us make sense of the vast complexity of biological and scientific data. It is among the first examples of a truly general-purpose multi-agent system for scientific discovery. The core research question behind it was: How can an AI system engage in the rigorous, structured thinking that’s the hallmark of science and scientists? To tackle this, Co-Scientist builds on the principles of self-play and self-improvement underpinning @GoogleDeepMind breakthroughs like AlphaGo, generalizing them to scientific reasoning through self-debates. Since our preprint last year, we have further improved its capabilities and have been validating it in collaborations with scientists across over 100 institutions globally, spanning both academia and industry. And we are thrilled to see the emergence of a new form of AI-human scientist collaboration that's already leading to important new insights, discoveries and peer reviewed publications - from understanding antimicrobial resistance (published in @CellCellPress) to decoding plant immunity, to identifying new treatments for liver fibrosis (Advanced Science), cancer, neurodegenerative diseases like ALS and the grand challenge of aging. I have always believed AI's greatest promise is accelerating scientific discovery and advancing human health. My genuine hope for the future is that AI tools like Co-Scientist help democratize science, giving anyone, anywhere the means to pursue their child-like curiosity and change the world. This work was done with stellar team mates spanning @GoogleDeepMind @GoogleResearch, @googlecloud and @GoogleLabs especially Juro Gottweis (@Mysiak ), who is the heart and soul of this effort. Special thanks also to all our wonderful collaborators: Gary Peltz, @CostaT_Lab, @jrpenades, @_e_d_v_ , @iambyronic, @OpsBug, @jgooten, @omarabudayyeh Ritu Raman, Ryan Flynn, Filippo Menolascina, Velia Siciliano, Clare Bryant, Matt Onsum, Katherine Labbé and more. Nature paper link - lnkd.in/e8qBEJFv Google DeepMind blog - lnkd.in/etYeahMy Gemini for Science - labs.google/science.

Since joining @GoogleDeepMind I’ve dreamt for a decade that AI can give clinicians superpowers: amplifying reach as an always-available, trustworthy member of the care team. Delighted to share our strategic research initiative at @GoogleDeepMind towards this vision: AI co-clinician deepmind.google/blog/ai-co-cli… (1/n)

Protein structure prediction changed biology. Protein assembly discovery is next. We present SNI (Structural Novelty Index), a scalable framework for finding new protein complexes. We used it to uncover an unexpected resistosome assembly: 11-mer. 🧵👇🏻 biorxiv.org/content/10.648…

Since joining @GoogleDeepMind I’ve dreamt for a decade that AI can give clinicians superpowers: amplifying reach as an always-available, trustworthy member of the care team. Delighted to share our strategic research initiative at @GoogleDeepMind towards this vision: AI co-clinician deepmind.google/blog/ai-co-cli… (1/n)