Ke Jie is a master of the game and we were honoured by his words. We were also inspired by them, because they hint at a future where society could use AI as a tool for discovery, uncovering new knowledge and increasing our understanding of the world. With machine-aided science in particular, we hope that AI systems could help make progress on challenges from climate change and drug discovery, to finding complex new materials or helping ease the pressure on healthcare systems.

This potential for societal benefit is why we set up DeepMind, and we’re excited to have made continued progress on some of the fundamental scientific challenges as well as on AI safety and ethics.

The approach we take at DeepMind is inspired by neuroscience, helping to make progress in critical areas such as imagination, reasoning, memory and learning. Take imagination, for example: this distinctively human ability plays a crucial part in our daily lives, allowing us to plan and reason about the future, but is hugely challenging for computers. We continue to work hard on this problem, this year introducing imagination-augmented agents that are able to extract relevant information from an environment in order to plan what to do in the future.

This neuroscience-inspired approach also created one of the most popular demonstrations of our work, when we trained a neural network to control a variety of simplified body shapes in a simulated environment. This kind of sophisticated motor control is a hallmark of physical intelligence, and is a crucial part of our research programme. Although the resulting movements were wild and - at times - ungainly, they were also surprisingly successful and made for entertaining viewing.