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Optical AI Could Feed Voracious Data Needs
When scientists developed a 3D-printed, multiplexing optical neural network, they calculated it could handle as many as 2,000 data channels simultaneously.
Credit: Ozcan Research Group/UCLA
A brain-imitating neural network that employs photons instead of electrons could rapidly analyze vast amounts of data by running many computations simultaneously using thousands of wavelengths of light, a new study finds.
Artificial neural networks are increasingly finding use in applications such as analyzing medical scans and supporting autonomous vehicles. In these artificial-intelligence systems, components (also known as neurons) are fed data and cooperate to solve a problem, such as recognizing faces. A neural network is dubbed "deep" if it possesses multiple layers of neurons.
As neural networks grow in size and power, they are becoming more energy hungry when run on conventional electronics. Which is why some scientists have been investigating optical computing as a promising, next-generation AI medium. This approach uses light instead of electricity to perform computations more quickly and with less power than its electronic counterparts use.
From IEEE Spectrum
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