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Models

Foundation, generative, multimodal and specialised models.

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2019

  • Nov 19, 2019 MuZero

    MuZero is a DeepMind reinforcement-learning algorithm that pairs tree-based search with a learned model. It reached superhuman play in Atari, Go, chess and shogi without being given the environment's rules.

    Research historyDeep learningReasoning

  • Jan 2019 AlphaStar

    AlphaStar is a DeepMind system that plays StarCraft II. In 2019 it reached Grandmaster level with all three races, ranking above 99.8% of active players on Battle.net.

    Research historyDeep learningReasoning

2017

  • Dec 5, 2017 AlphaZero

    AlphaZero is a general game-playing system from DeepMind, described in a preprint in December 2017, that reached a superhuman level in chess, shogi and Go within 24 hours starting from random play, using only the rules of each game.

    Research historyDeep learningReasoning

  • Oct 18, 2017 AlphaGo Zero

    A DeepMind Go program that learned the game from scratch by playing against itself, using no human game records, and beat earlier versions of AlphaGo within days.

    Research historyDeep learningReasoning

2016

  • Jan 27, 2016 AlphaGo

    AlphaGo is a Go-playing program from DeepMind that combined deep neural networks with Monte Carlo tree search. In 2016 it beat top professional Lee Sedol in a widely watched match, a landmark for learned systems.

    Research historyDeep learningReasoning

2011

  • Feb 2011 IBM Watson

    IBM Watson is a question-answering computer system built by an IBM research team led by David Ferrucci; in February 2011 it defeated the two foremost all-time champions of the televised quiz show Jeopardy!

    Research historyEnterpriseReasoning