Neuromorphic computing:
Neuromorphic engineering, also known as neuromorphic computing,[1][2][3] is a concept developed by Carver Mead,[4] in the late 1980s, describing the use of very-large-scale integration (VLSI) systems containing electronic analog circuits to mimic neuro-biological architectures present in the nervous system.[5] In recent times the term neuromorphic has been used to describe analog, digital, mixed-mode analog/digital VLSI, and software systems that implement models of neural systems (for perception, motor control, or multisensory integration). The implementation of neuromorphic computing on the hardware level can be realized by oxide-based memristors,[6] threshold switches, and transistors. [Wikipedia]
Noted in “Think on this,” Liesbeth Venema, NewScientist (5 August 2017, paywall):
But soon real action was happening on the neuromorphic computing scene. Shortly after Williams’s discovery, Wei Lu, an engineer at the University of Michigan, took the crucial step and showed that memristors can act as plastic synapses. He used a device made of several thin layers of silicon, one of them with a smattering of silver ions, and showed this can mimic that second feature of the brain. Lu later showed that memristors can simulate the third ingredient too; the memristor synapse could be strengthened or weakened depending on the exact timing of applied electrical spikes.
