The memristor chip that powers the new reservoir computing system. Image credit: Wei Lu
ANN ARBOR-A new type of neural network made with memristors can dramatically improve the efficiency of teaching machines to think like humans. The network, called a reservoir computing system, could predict words before they are said during conversation, and help predict future outcomes based on the present. The research team that created the reservoir computing system, led by Wei Lu, a U-M professor of electrical engineering and computer science at the University of Michigan, recently published their work. Reservoir computing systems, which improve on a typical neural network's capacity and reduce the required training time, have been created in the past with larger optical components. However, the U-M group created their system using memristors, which require less space and can be integrated more easily into existing silicon-based electronics. Memristors are a special type of resistive device that can both perform logic and store data. This contrasts with typical computer systems, where processors perform logic separate from memory modules.
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