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in 2016 deepmindamp;#39;s alphago surprised many people by beating a top-level professional at the game of go this achievement was a big step for artificial intelligence happening several years ahead of expert predictions the next year deepmind showed the algorithm behind alphago was able to learn the rules and strategy of go by only playing against itself it did not require a corpus of expert human play or go specific tuning in 2018 a more general version of this algorithm called alpha zero was able to obtain superhuman levels of play for two more classical board games shogi and chess the third iteration and the topic of this video is mew zero a mew zero agent can learn to play board games atari games and optimize video compression settings the authors claim mu zero agents are general purpose enough to learn the rules and constraints for many different environments like its predecessor alphago the core parts of mu0 are neural networks and tree search in this video we will dive into t