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Training AIs remains very processor-intensive, in part because traditional processing architectures are poor matches for the
Hydrogen-soaked crystal lets neural networks expand to match a problem
Enlarge (credit: Getty Images)
Training AIs remains very processor-intensive, in part because traditional processing architectures are poor matches for the