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Whitepaper: Accelerate Training of Deep Neural Networks with MemComputing

“The paper addresses the inherent limitations associated with today’s most popular gradient-based methods, such as Adaptive Moment Estimation (ADAM) and Stochastic Gradient Descent (SGD), which incorporate backpropagation. MemComputing’s approach instead aims towards a more global and parallelized optimization algorithm, achievable through its entirely new computing architecture.”

New Study: Algorithms based on deep neural networks can be applied to quantum physics

A computer science research group from the Hebrew University of Jerusalem has mathematically proven that artificial intelligence (AI) can help us understand currently unreachable quantum physics phenomena. The results have been published in Physical Review Letters. “Our research proves that the AI algorithms can represent highly complex quantum systems significantly more efficiently than existing approaches,” said Prof. Amnon Shashua, Intel senior vice president and Mobileye president and CEO.”