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Latest neuromorphic computing publications


Magnetic circuits could radically reduce AI energy consumption

The combination of AI and large data sets has profoundly improved our ability to model the world around us, predict its next move and recognize its images and patterns.

Underpinning all of this data-driven innovation, though, are servers and accelerators that can devour astronomical amounts of energy, depending on the task.

Last year, research indicated that training a single AI algorithm can require up to 284 tonnes of carbon dioxide – five times the lifetime emissions of an average car.