Science Daily January 7, 2021
Convolutional neural networks have been central to the artificial intelligence revolution, but existing silicon technology increasingly presents a bottleneck in processing speed and energy efficiency. An international team of researchers (Australia, China, Canada) has demonstrated an optical neuromorphic processor for artificial intelligence which operates faster than 10 trillion operations per second (TeraOPs/s) and is capable of processing ultra-large scale data, enough to achieve full facial image recognition, something that other optical processors have been unable to accomplish. The system uses a single processor and was achieved using a new technique of simultaneously interleaving the data in time, wavelength, and spatial dimensions through an integrated micro-comb source. This processor can serve as a universal ultrahigh bandwidth front end for any neuromorphic hardware — optical or electronic based — bringing massive-data machine learning for real-time ultrahigh bandwidth data within reach. This breakthrough represents an enormous leap forward for neural networks and neuromorphic processing in general…read more. TECHNICAL ARTICLE
Operation principle of the TOPS photonic CA. Credit: Nature volume 589, pages44–51(2021)