Superconducting neurons could match the power efficiency of the brain

computer scientists want to build artificial neurons and connect them together in brain-like networks. That has the potential to be significantly more energy efficient, but nobody has come up with a design that comes close to the efficiency of the brain.

Until today. Enter Emily Toomey at MIT and a couple of colleagues, who have designed a superconducting neuron made from nanowires that in many ways behaves like a real one. They say their device matches the energy efficiency of the brain (at least in theory) and is the building block of a new generation of superconducting neural networks that will be vastly more efficient than conventional computing machinery.

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