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One of the (many) ways in which AI is making waves is in its ability to analyze immense datasets. But training these AI programs is becoming increasingly computationally intensive, underscoring the need to more efficient ways to crunch data. In a study published 22 May in IEEE Transactions on Computers, researchers describe a novel approach, called Waterwave, to increase the efficiency of training multiple AI models simultaneously and efficiently on the same GPU.