We have heard about a great number of new architectures and approaches to scalable and efficient deep learning processing that sit outside of the standard CPU, GPU, and FPGA box and while each is different, many are leveraging a common element at all-important memory layer. …
Whether in the brain or in code, neural networks are shaping up to be one of the most critical areas of research in both neuroscience and computer science. …
Stanford University PhD candidate, Song Han, who works under advisor and networking pioneer, Dr. …
For Google, Baidu, and a handful of other hyperscale companies that have been working with deep neural networks and advanced applications for machine learning well ahead of the rest of the world, building clusters for both the training and inference portions of such workloads is kept, for the most part, a well-guarded secret. …
Even though the buzz around neural networks, artificial intelligence, and machine learning has been relatively recent, as many know, there is nothing new about any of these methods. …
Explaining the process of how any of us might have arrived to a particular conclusion or decision by verbally detailing the variables, weights, and conditions that our brains navigate through to arrive at an answer can be complex enough. …
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