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There is little doubt that 2017 will be a dense year for deep learning. With a sudden new wave of applications that integrate neural networks into existing workflows (not to mention entirely new uses) and a fresh array of hardware architectures to meet them, we expect the space to start shaking out its early winners
Over the last two years, there has been a push for novel architectures to feed the needs of machine learning and more specifically, deep neural networks. We have covered the many architectural options for both the training and inference sides of that workload here at The Next Platform, and in doing so, started to notice
Intel has planted some solid stakes in the ground for the future of deep learning over the last month with its acquisition of deep learning chip startup, Nervana Systems, and most recently, mobile and embedded machine learning company, Movidius. These new pieces will snap into Intel’s still-forming puzzle for capturing the supposed billion-plus dollar market