Nature Communications (Dec 2022)

Physical deep learning with biologically inspired training method: gradient-free approach for physical hardware

  • Mitsumasa Nakajima,
  • Katsuma Inoue,
  • Kenji Tanaka,
  • Yasuo Kuniyoshi,
  • Toshikazu Hashimoto,
  • Kohei Nakajima

DOI
https://doi.org/10.1038/s41467-022-35216-2
Journal volume & issue
Vol. 13, no. 1
pp. 1 – 12

Abstract

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Traditional learning procedures for artificial intelligence rely on digital methods not suitable for physical hardware. Here, Nakajima et al. demonstrate gradient-free physical deep learning by augmenting a biologically inspired algorithm, accelerating the computation speed on optoelectronic hardware.