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Two artificial synapses are better than one

Emerging nanoelectronic devices could revolutionize artificial neural networks, but their hardware implementations lag behind those of their software counterparts. An approach has been developed that tips the scales in their favour.
  1. Gina C. Adam

    1. Gina C. Adam is at the National Institute for Research and Development in Microtechnologies, Bucharest 077190, Romania.

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Inspired by the brain’s neural networks, scientists have for decades tried to construct electronic circuits that can process large amounts of data. However, it has been difficult to achieve energy-efficient implementations of artificial neurons and synapses (connections between neurons). In a paper in Nature, Ambrogio et al.1 report an artificial neural network containing more than 200,000 synapses that can classify complex collections of images. The authors’ work demonstrates that hardware-based neural networks that use emerging nanoelectronic devices can perform as well as can software-based networks running on ordinary computers, while consuming much less power.

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Nature 558, 39-40 (2018)

doi: https://doi.org/10.1038/d41586-018-05297-5

References

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