The human brain, fed on just the calorie input of a
modest diet, easily outperforms state-of-the-art supercomputers
powered by full-scale station energy inputs. The difference stems
from the multiple states of brain processes versus the two binary
states of digital processors, as well as the ability to store
information without power consumption—non-volatile memory. These
inefficiencies in today’s conventional computers have prompted
great interest in developing synthetic synapses for use in
computers that can mimic the way the brain works. Now, researchers
at King’s College London, UK, report in ACS Nano Letters an array
of nanorod devices that mimic the brain more closely than ever
before. The devices may find applications in artificial neural
networks.
