The human brain is one of the most efficient computer systems known to mankind. As man-made computers have grown more and more powerful, scientists and researchers have turned to the human brain for inspiration on how to make computers better.
This brain-inspired field of computing is called neomorphic computing, and a team of Penn State University Engineers is using graphene field effect transistors to configure an artificial neural network the team is working on.
Current computers are limited in part because the computing processes occur in a separate place than where the memory is stored. The continuous need for these two functions to communicate requires a lot of energy and makes computing slower than it has to be, according to Penn State News.
“We are creating artificial neural networks, which seek to emulate the energy and area efficiencies of the brain,” Thomas Schranghamer, a doctoral student and first author on a paper recently published in Nature Communications explained in Penn State News. “The brain is so compact it can fit on top of your shoulders, whereas a modern supercomputer takes up a space the size of two or three tennis courts.”