Powering AI at the edge: A robust, memristor-based binarized neural network with near-memory computing and miniaturized solar cell

Powering AI at the edge: A robust, memristor-based binarized neural network with near-memory computing and miniaturized solar cell

Abstract Memristor-based neural networks provide an exceptional energy-efficient platform for artificial intelligence (AI), presenting the possibility of self-powered operation when paired with energy harvesters. However, most memristor-based networks rely on analog in-memory computing, necessitatin...

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Bibliographic Details
Main Authors: Fadi Jebali, Atreya Majumdar, Clément Turck, Kamel-Eddine Harabi, Mathieu-Coumba Faye, Eloi Muhr, Jean-Pierre Walder, Oleksandr Bilousov, Amadéo Michaud, Elisa Vianello, Tifenn Hirtzlin, François Andrieu, Marc Bocquet, Stéphane Collin, Damien Querlioz, Jean-Michel Portal
Format: Article
Language:English
Published: Nature Portfolio 2024-01-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-024-44766-6

Internet

https://doi.org/10.1038/s41467-024-44766-6

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