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DeepMind repurposes game-playing AIs to optimize code and infrastructure


DeepMind’s Alpha series of AIs has provided a few world-firsts, like AlphaGo beating the world champion at Go. Now these AIs originally trained around playing games have been put to work on other tasks, and are showing a surprising facility for them.
Originally, AlphaGo was trained using human gameplay, then AlphaGo Zero learned only by playing against itself, then AlphaZero did the same but also mastered Chess and Shogi. MuZero did all that and more without even being told the rules of the game, which if you think about it may limit the way it “thinks” about how to accomplish its task.
At Google, a system called Borg manages task assignment at data centers — basically parsing requests and allocating resources at light speed so …

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