We’ve always been fascinated by human intelligence – it shaped the modern world we live in today.
Intelligence allows us to learn, imagine, cooperate, create, communicate, and so much more. By better understanding different aspects of intelligence, we can use this knowledge as inspiration to build novel computer systems that learn to find solutions to difficult problems on their own.
Like the Hubble telescope that helped us look deeper into space, these tools are already expanding human knowledge and making positive global impact.
Our long term aim is to solve intelligence, developing more general and capable problem-solving systems, known as artificial general intelligence (AGI).
Guided by safety and ethics, this invention could help society find answers to some of the world’s most pressing and fundamental scientific challenges.
Where we began
When we started DeepMind in 2010, there was far less interest in the field of AI than there is today. To accelerate the field, we took an interdisciplinary approach, bringing together new ideas and advances in machine learning, neuroscience, engineering, mathematics, simulation and computing infrastructure, along with new ways of organising scientific endeavour.
We achieved early success in computer games, which researchers often use to test AI. One of our programs learned to play 49 different Atari games from scratch, just from seeing the pixels and score on the screen. Our AlphaGo program was also the first to beat a professional Go player, a feat described as a decade ahead of its time.