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Memristors enabling probabilistic AI at the edge

By combining several probabilistic AI algorithms, a recent study demonstrates experimentally that the inherent noise and variation in memristor nanodevices can be exploited as features for energy-efficient on-chip learning.

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Fig. 1: Leveraging memristor stochasticity for Bayesian neural networks and active learning.

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  1. Université Paris-Saclay, CNRS, Centre de Nanosciences et de Nanotechnologies, Palaiseau, France

    Damien Querlioz

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Querlioz, D. Memristors enabling probabilistic AI at the edge.
Nat Comput Sci (2025). https://doi.org/10.1038/s43588-024-00761-x

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  • Published: 17 January 2025

  • DOI: https://doi.org/10.1038/s43588-024-00761-x

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