Consider this: It takes today’s state-of-the-art supercomputers eight-and-a-half minutes to simulate just five seconds of human brain activity. And to perform the function, supercomputers consume 140,000 times as much electricity as the brain—1.4 million watts to 10 million watts.
In a recent paper in the online edition of the journal Nano Letters, a team of Stanford engineers has demonstrated a new nanoelectronic device that emulates human synapses—the brain’s computing mechanism. It is touted as a breakthrough, which may one day lead to portable, energy-efficient, adaptable and interactive computer systems that can learn, rather than respond to given programmes, according to a release.
The team, led by professor H S Philip Wong, post-doctoral scholar Duygu Kuzum and graduate students Rakesh Jeyasingh and Byoungil Lee, has been working in a new field known as 'brain-inspired computing', which seeks to imitate in computer chips the neurological signaling mechanism of the human synapse. Other researchers have done similar work, but this team is the first to succeed at creating small synaptic devices, with a low-enough energy consumption. The device has also been created with a technology to anticipate commercial viability in the future.
“This development could lead to electronic devices that are so small and energy efficient that we might be able to make nanoelectronic versions of certain parts of the brain to study how they work,” said Wong, a professor of electrical engineering. “While you can't alter a biological brain, a synthetic device like this would allow researchers to change the device parameters to reveal how brains function.”
With enough transistors packed into each chip, programmers can manipulate electrical circuits, turning billions of transistors on or off as necessary to store and process information to compute.