Brownian reservoir computing allows to detect human hand gestures on the basis of diffusion and displacement of skyrmions.
Researchers have advanced Brownian reservoir computing by successfully recording and recognizing simple hand gestures using skyrmions, a type of magnetic whirl. This method proves not only to be as accurate as traditional neural network software but also significantly more energy-efficient. Their findings demonstrate potential for future applications in non-conventional computing and data storage.
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