Google DeepMind

We’re a team of scientists, engineers, ethicists and more, working to build the next generation of AI systems safely and responsibly. By solving some of the hardest scientific and engineering challenges of our time, we’re working to create breakthrough technologies that could advance science, transform work, serve diverse communities — and improve billions of people’s lives. AI has the potential to be one of the most important and beneficial technologies ever invented. The lab achieved early success by pioneering the field of deep reinforcement learning - a combination of deep learning and reinforcement learning - and using games to test its systems. One of its early breakthroughs was a program called DQN , which learned to play 49 different Atari games from scratch just by observing the raw pixels on the screen and being told to maximize the score. The team also invented WaveNet , a realistic text-to-speech model that was used as the voice of the Google Assistant and introduced a lot of the technology used in Generative AI systems today. Then in 2020, DeepMind launched AlphaFold , an AI system that accurately predicts 3D models of protein structures — catalyzing a new wave of progress in biology. Other breakthroughs include writing computer programs at a competitive level with AlphaCode , discovering faster sorting algorithms with AlphaDev , advancing weather predictions with unparalleled accuracy, and controlling plasma in nuclear fusion reactors. Google Brain started in 2011 at X, the moonshot factory , exploring how modern AI could transform Google’s products and services, and furthering its mission to organize the world's information and make it universally accessible and useful. The team has also advanced the state-of-the-art in robotics by using a large language model in a robotics system with PaLM-SayCan , and the creation of a more generalized visual-language-action model with RT-2 . Brain also pioneered the use of machine learning in the creative process with Magenta and text-to-image generation models like Imagen . The team’s work on the Universal Speech Model enables better understanding of more spoken languages around the world, while initiatives like Project Euphonia improve communication for people with speech impairments. A general purpose world model that can generate an unprecedented diversity of interactive environments. Revealing millions of intricate 3D protein structures, and helping scientists understand how life’s molecules interact.