World’s fastest optical neuromorphic processor

Dr Xingyuan (Mike) Xu with the integrated optical microcomb chip, which forms the core part of the optical neuromorphic processor. Credit: Swinburne University of Technology

This post is not directly linked to Quantum Computing but might be interesting to our readers.

An international team of researchers led by Swinburne University of Technology has demonstrated the world’s fastest and most powerful optical neuromorphic processor for artificial intelligence (AI), which operates faster than 10 trillion operations per second (TeraOPs/s) and is capable of processing ultra-large scale data.

Artificial Neural Networks (ANNs), a key form of AI, can ‘learn’ and perform complex operations with wide applications to computer vision, natural language processing, facial recognition, speech translation, playing strategy games, medical diagnosis and many other areas. Inspired by the biological structure of the brain’s visual cortex system, ANNS extract key features of raw data to predict properties and behavior with unprecedented accuracy and simplicity.

The team demonstrated an optical neuromorphic processor operating more than 1000 times faster than any previous processor, with the system also processing record-sized ultra-large scale images—enough to achieve full facial image recognition, something that other optical processors have been unable to accomplish.

While state-of-the-art electronic processors such as the Google TPU can operate beyond 100 TeraOPs/s, this is done with tens of thousands of parallel processors. In contrast, the optical system demonstrated by the team 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 breakthrough represents an enormous leap forward for neural networks and neuromorphic processing in general. (TechXplore)

The work has been published in the journal Nature.

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