  Neuromorphic computing takes inspiration from the brain to create energy
efficient hardware for information processing, capable of highly sophisticated
tasks. In this article, we make the case that building this new hardware
necessitates reinventing electronics. We show that research in physics and
material science will be key to create artificial nano-neurons and synapses, to
connect them together in huge numbers, to organize them in complex systems, and
to compute with them efficiently. We describe how some researchers choose to
take inspiration from artificial intelligence to move forward in this
direction, whereas others prefer taking inspiration from neuroscience, and we
highlight recent striking results obtained with these two approaches. Finally,
we discuss the challenges and perspectives in neuromorphic physics, which
include developing the algorithms and the hardware hand in hand, making
significant advances with small toy systems, as well as building large scale
networks.
