Researchers at Stanford University have demonstrated the ability to train artificial neural networks directly on an optical chip.
Neural network processing currently relies on conventional computers. The Optical Society's journal for high impact research, Stanford University researchers report a method for training these networks directly in the device by implementing an optical analogue of the ‘backpropagation’ algorithm, which is the standard way to train conventional neural networks.
“Using an optical chip to perform neural network computations more efficiently than is possible with digital computers could allow more complex problems to be solved,” said research team leader Shanhui Fan of Stanford University. “This would enhance the capability of artificial neural networks to perform tasks required for self-driving cars or to formulate an appropriate response to a spoken question, for example. It could also improve our lives in ways we can’t imagine now.”
https://www.osapublishing.org/optica/abstract.cfm?uri=optica-5-7-864
