We introduce a full evaluation of AlphaZero, published in the journal Science, which describes a single algorithm that taught itself from scratch how to master the games of chess, shogi (Japanese chess), and Go, convincingly beating a world champion program in each case. AlphaZero’s ability to learn each game by itself results in a distinctive, creative and dynamic playing style that has captured the attention of the chess community. The result also marks an important step towards creating a flexible, general-purpose system that could one day learn to solve many different important and complex scientific problems.
We founded DeepMind to make the world a better place by developing technologies that help address some of society's toughest challenges.Read more
Humans excel at solving a wide variety of challenging problems, from low-level motor control through to high-level cognitive tasks. Our goal at DeepMind is to create artificial agents that can achieve a similar level of performance and generality. Like a human, our agents learn for themselves to achieve successful strategies that lead to the greatest long-term rewards.Read more
We founded DeepMind to solve intelligence and use it to make the world a better place by developing technologies that help address some of society's toughest challenges. It was clear to us that we should focus on healthcare because it’s an area where we believe we can make a real difference to people’s lives across the world.Read more