While today's computing chips are incredibly complex and have the ability to perform thousands of tasks in the blink of an eye, they don't begin to approach the computing capabilities of the human brain, researchers at Boise State University said.
Funded by a 3-year, $500,000 National Science Foundation grant, they've set a goal of developing a new kind of computing architecture that can compute the way the human brain does, a university release reported Wednesday.
"By mimicking the brain's billions of interconnections and pattern recognition capabilities, we may ultimately introduce a new paradigm in speed and power, and potentially enable systems that include the ability to learn, adapt and respond to their environment," principle investigator Barney Smith said.
The team's effort will build on recent work from scientists who have developed mathematical algorithms to explain the electrical interaction between brain synapses and neurons, Smith said.
"By employing these models in combination with a new device technology that exhibits similar electrical response to the neural synapses, we will design entirely new computing chips that mimic how the brain processes information," he said.
The project's success in creating an artificial neural network rests on a memristor -- a resistor that can be programmed to a new resistance by application of electrical pulses and remembers its new resistance value once the power is removed.
First conceptualized 1972, memristors have been fully realized as nano-scale devices only in the last decade, the researchers said.
The Boise State lab was one of the first in the world to build a working memristor.