Self-Learning AI: This New Neuro-Inspired Computer Trains Itself

A team of researchers from Belgium think that they are close to extending the anticipated end of Moore's Law, and they didn't do it with a supercomputer. Using an artificial intelligence (AI) algorithm called reservoir computing, combined with another algorithm called backpropagation, the team developed a neuro-inspired analog computer that can train itself and improve at whatever task it's performing. Reservoir computing is a neural algorithm that mimics the brain's information processing abilities. Backpropagation, on the other hand, allows for the system to perform thousands of iterative calculations that reduce error, which lets the system improve its solution to a problem. "Our work shows that the backpropagation algorithm can, under certain conditions, be implemented using the same hardware used for the analog computing, which could enhance the performance of these hardware systems," Piotr Antonik explains.