The human brain has about 1011 neurons and 1015 synapses and needs just about ten watts. That degree of interconnection and power e ciency cannot be achieved with silicon electronics. A new disruptive technology made up of neural networks is required. The implementation of arti cial synapses and arti cial neurons remains however a big challenge. Our team has shown that neurons could be made with quantum materials known as Mott insulators. We aim at a decisive theoretical understanding of out-of- equilibrium physics governing the Mott insulators and how they can form neuromorphic networks.

J. del Valle, J.G. Ramírez, M.J. Rozenberg, I.K. Schuller.
Challenges in materials and devices for resistive-switching-based neuromorphic computing, Journal of Applied Physics 124, 211101 (2018).

KEYWORDS

  • Artificial Intelligence
  • Neural Networks
  • Resistive switching
  • Out-of-equilibrium Mottronics
  • Neuromorphic functionalities