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analog

Analog Ai Hardware Aims To Reduce Costs And Carbon Emission
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Could machine learning’s escalating costs and carbon footprint be reduced by using analog AI hardware instead of digital to tap into quick, low-power processing? Researchers Logan Wright and Tatsuhiro Onodera from Cornell University and NTT Research foresee a time when machine learning (ML) will be carried out using cutting-edge physical

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