For the first time, a physical neural network has successfully been shown to learn and remember "on the fly," in a way inspired by and similar to how the brain's neurons work.
The result opens a pathway for developing efficient and low-energy machine intelligence for more complex, real-world learning and memory tasks.
Published today in Nature Communications, the research is a collaboration between scientists at the University of Sydney and University of California at Los Angeles.
Lead author Ruomin Zhu, a Ph.D. student from the University of Sydney Nano Institute and School of Physics, said, "The findings demonstrate how brain-inspired learning and memory functions using nanowire networks can be harnessed to process dynamic, streaming data."
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