Science Published 31 October 2023 Authors Google DeepMind AlphaFold team and Isomorphic Labs team Progress update: Our latest AlphaFold model shows significantly improved accuracy and expands coverage beyond proteins to other biological molecules, including ligands Since its release in 2020, AlphaFold has revolutionized how proteins and their interactions are understood. Google DeepMind and Isomorphic Labs […]
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. Ensuring these systems are developed and deployed responsibly requires carefully evaluating the potential ethical and social risks they may
In this article, we will talk about classical computation: the kind of computation typically found in an undergraduate Computer Science course on Algorithms and Data Structures [1]. Think shortest path-finding, sorting, clever ways to break problems down into simpler problems, incredible ways to organise data for efficient retrieval and updates. Of course, given The Gradient’s
This essay first appeared in Reboot. Credulous, breathless coverage of “AI existential risk” (abbreviated “x-risk”) has reached the mainstream. Who could have foreseen that the smallcaps onomatopoeia “ꜰᴏᴏᴍ” — both evocative of and directly derived from children’s cartoons — might show up uncritically in the New Yorker? More than ever, the public discourse about AI
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 and create a way to train a general-purpose robot?
Once considered a forbidden topic in the AI community, discussions around the concept of AI consciousness are now taking center stage, marking a significant shift since the current AI resurgence began over a decade ago. For example, last year, Blake Lemoine, an engineer at Google, made headlines claiming the large language model he was developing
Science Published 19 September 2023 Authors Žiga Avsec and Jun Cheng New AI tool classifies the effects of 71 million ‘missense’ mutations Uncovering the root causes of disease is one of the greatest challenges in human genetics. With millions of possible mutations and limited experimental data, it’s largely still a mystery which ones could give
Science Published 29 August 2023 Authors Sven Gowal, Pushmeet Kohli New tool helps watermark and identify synthetic images created by Imagen AI-generated images are becoming more popular every day. But how can we better identify them, especially when they look so realistic? Today, in partnership with Google Cloud, we’re launching a beta version of SynthID,
Research Published 28 July 2023 Authors Yevgen Chebotar, Tianhe Yu Robotic Transformer 2 (RT-2) is 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 High-capacity vision-language models (VLMs) are trained on web-scale datasets, making these systems remarkably good at recognising visual
How we’re applying the latest AI developments to help fight climate change and build a more sustainable, low-carbon world AI is a powerful technology that will transform our future, so how can we best apply it to help combat climate change and find sustainable solutions? Our climate & sustainability lead, Sims Witherspoon, who recently spoke
