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Spiking neural networks

The best of both worlds

Neuromorphic computing could unlock low-power machine learning that can run on edge devices. A new algorithm that implements an artificial neuron emitting a sparse number of spikes could help realize this goal.

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Fig. 1: Representing information in spikes.

References

  1. Stöckl C. & Maass, W. Nat. Mach. Intell. https://doi.org/10.1038/s42256-021-00311-4 (2021).

  2. Ray, T. ZDNet http://go.nature.com/2OhlH1f (2019).

  3. LeCun, Y. in IEEE International Solid State Circuits Conference (IEEE, 2019); https://doi.org/10.1109/ISSCC.2019.8662396

  4. Davies, M. Nat. Mach. Intell. 1, 386–388 (2019).

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Correspondence to Tara Hamilton.

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Hamilton, T. The best of both worlds. Nat Mach Intell 3, 194–195 (2021). https://doi.org/10.1038/s42256-021-00315-0

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