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Neural networks have been called a “black box” because parts of their decision making are famously opaque as processing happens in hidden layers.…

Training Generative Adversarial Networks in Flexpoint With the recent flood of breakthrough products using deep learning for image classification,…

Stochastic Gradient Descent and its variants, referred here collectively as SGD, have been the de facto methods in training neural networks. These…

One of the most notable themes of NIPS 2017, against a backdrop of spectacular progress in AI on many fronts, was the fear of machine learning sys…

Teaching Machines to do Image Classification in Health and Life Sciences: Intel® Xeon® Scalable Processors in Lab Coats

This summer, Intel has been collaborating with the NASA Frontier Development Lab (FDL) , an AI R&D accelerator targeting knowledge gaps useful…

Quantized Neural Networks (QNNs) are often used to improve network efficiency during the inference phase, i.e. after the network has been trained.…

Today, Intel is announcing the release of our Reinforcement Learning Coach — an open source research framework for training and evaluating reinfor…

Shedding Light on Undermapped Areas With AI and the American Red Cross

As principal engineer and head of data science in Intel’s AI Products Group, Yinyin Liu offers Intel’s perspective on what it will take to fulfill…

WaveNet* is a deep neural network for generating raw audio. The model was first introduced by the Google DeepMind team [1]. Per the authors, WaveN…

Precision medicine is one of the most exciting and encouraging advances in healthcare today. It is moving us from one-size-fits-all healthcare to…