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Memristive synapses could reduce AI energy consumption

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A new highly stable and energy-efficient memristor based on a hafnium oxide material can emulate the behaviour of synapses in the brain. The neuromorphic device could help dramatically cut the energy consumed by artificial intelligence (AI) hardware, say its developers at the University of Cambridge in the UK.

Today’s AI systems rely on conventional digital computers. These have separate processing and storage units and consume huge amounts of energy when performing data-intensive tasks. As global AI use is exploding, this energy consumption has already become unsustainable, says materials scientist Babak Bakhit , who led this new study.

An alternative way to process information

Neuromorphic computers could provide an alternative way to process information. As their name suggests, they are inspired by the architecture of the human brain. The circuits in these computers are made up of highly connected artificial neurons and artificial synapses that simulate the brain’s structure and functions.…

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