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A Brain Built From Atomic Switches Can Learn

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Artist's impression of a self-organized mesh of artificial synapses.

Researchers at the California NanoSystems Institute are developing network of highly interconnected nanowires as a brainlike device for learning and computation.

Credit: Eric Nyquist/Quanta Magazine

Researchers at the University of California, Los Angeles are constructing a device the California NanoSystems Institute's Adam Stieg says is "inspired by the brain to generate the properties that enable the brain to do what it does."

The device is a mesh of highly interconnected silver nanowires that is self-configured out of random chemical and electrical processes. This network contains 1 billion artificial synapses for each square centimeter, and experiments found it can execute simple learning and logic operations, as well as filtering out unwanted noise from received signals.

Instead of using software, the researchers leverage the network's ability to distort an input signal in various ways, depending on where the output is quantified; this implies voice- or image-recognition applications.

Another implication is the mesh could support reservoir computing, enabling users to select or mix outputs in such a manner that the result is a desired computation of the inputs.

From Quanta Magazine
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