Progress update: Our latest AlphaFold model shows significantly improved accuracy and expands coverage beyond proteins to other biological molecules, including ligands.

Introducing a context-based framework for comprehensively evaluating the social and ethical risks of AI systems

Generative AI systems are already being used to write books, create graphic designs, assist medical practitioners, and are becoming increasingly capable. To ensure these systems are developed and deployed responsibly requires carefully evaluating the p…

Robots are great specialists, but poor generalists. Typically, you have to train a model for each task, robot, and environment. Changing a single variable often requires starting from scratch. But what if we could combine the knowledge across robotics …

We are launching a new set of resources for general-purpose robotics learning across different robot types, or embodiments. Together with partners from 34 academic labs we have pooled data from 22 different robot types to create the Open X-Embodiment d…

New AI tool classifies the effects of 71 million ‘missense’ mutations.

We’ve released a catalogue of ‘missense’ mutations where researchers can learn more about what effect they may have. Missense variants are genetic mutations that can affect the function of human proteins. In some cases, they can lead to diseases such a…

Today, in partnership with Google Cloud, we’re beta launching SynthID, a new tool for watermarking and identifying AI-generated images. It’s being released to a limited number of Vertex AI customers using Imagen, one of our latest text-to-image models …

New tool helps watermark and identify synthetic images created by Imagen

Introducing Robotic Transformer 2 (RT-2), a novel vision-language-action (VLA) model that learns from both web and robotics data, and translates this knowledge into generalised instructions for robotic control, while retaining web-scale capabilities. T…