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The first tensor processor chip based on carbon nanotubes could lead to energy-efficient AI processing

Artificial intelligence (AI) and machine learning tools have proved to be highly effective in tackling various tasks that entail analyzing data and making accurate predictions. Despite their advantages, these tools have significant computational demands, and when running on existing processing units, they can consume a lot of energy. Researchers at Peking University and other institutes in China recently developed a highly promising tensor processing unit (TPU) based on carbon nanotubes that could be used to run AI algorithms more energy-efficiently. This carbon nanotube-based tensor processing chip, presented in a paper in Nature Electronics, could be a key breakthrough on the path towards developing next-generation chips.