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 (November 1) in Nature Communications, the research is a collaboration between scientists at the University of Sydney and the University of California at Los Angeles (UCLA).