Researchers at UCLA and Japan's National Institute for Materials Science developed a device with the ability to mimic certain characteristics of the brain. The work is described in "Emergent Dynamics of Neuromorphic Nanowire Networks," published in Scientific Reports.
James Gimzewski, a chemistry professor at UCLA, and Adam Stieg, associate director of the California NanoSystems Institute at UCLA, helped create the device, which spans 10 square millimeters.
The device's small size is possible because of the number of networks within the device, all of which are made from silver nanowires, which have an average diameter of 360 nanometers.
"Because [the networks] self-assemble on the nanoscale, we can achieve a very high density of synaptic-like connections that wouldn't be achievable using normal computer chip technology," Gimzewski says.
Kelsey Scharnhorst, who assisted in research for this project, says the growing popularity of machine learning has led to a scramble to develop an option that can produce computational outputs in a timely, more-energy-efficient fashion.
"Instead of doing everything with algorithms . . . [computations] can be sped up an insane amount [with machine learning], and that can make a huge difference for a ton of technology," Scharnhorst says.
From The Daily Bruin
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