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One of the first attempts to use machine learning in chess computing yielded interesting results. The AI that was fed hundreds of thousands of historic grandmaster matches immediately sacrificed the queen, smashing it over a random pawn. The reason? When a grandmaster sacrifices the queen, it is usually a hard, calculated decision that leads to winning. So, AI assumed that the best way to win is to sacrifice the queen as quick as possible.
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