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Substituting a photonic tensor core for existing digital processors such as GPUs, a pair of engineers from George Washington University (GWU) has introduced a new technique for performing high-level neural network computations. In the approach, light energy replaces electricity, processing optical data feeds at a performance rate two to three orders higher than with an electrical tensor processing unit (TPU) and supporting unsupervised learning and performance in AI machines.
Neural networks commonly perform and advance machine learning, meaning the discovery has potential to develop artificial intelligence for a variety of applications.
Neural networks in machine learning are trained to to classify unseen data and make…READ MORE