Shock to the system: Using electricity to find materials that can learn

Scientists looking to create a new generation of supercomputers are looking for inspiration from the most complex and energy-efficient computer ever built: the human brain.

In some of their initial forays into making brain-inspired computers, researchers are looking at different nonbiological materials whose properties could be tailored to show evidence of learning-like behaviors. These materials could form the basis for hardware that could be paired with new software algorithms to enable more potent, useful and energy-efficient artificial intelligence (AI).

In a new study led by scientists from Purdue University, researchers have exposed oxygen deficient nickel oxide to brief electrical pulses and elicited two different electrical responses that are similar to learning. The result is an all-electrically-driven system that shows these learning behaviors, said Rutgers University professor Shriram Ramanathan. (Ramanathan was a professor at Purdue University at the time of this work.) The research team used the resources of the Advanced Photon Source (APS), a U.S. Department of Energy (DOE) Office of Science user facility at DOE’s Argonne National Laboratory.

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