CES 2016: Deep learning proliferation

Neural networks, which have been academic exercises (but little more) for decades, are increasingly becoming mainstream success stories. Heavy (and growing) investment in the technology, which enables the identification of objects in still and video images, words in audio streams, and the like after an initial training phase, comes from the formidable likes of Amazon, Baidu, Facebook, Google, Microsoft, and others. So-called “deep learning” has been enabled by the combination of the evolution of traditional neural network techniques, with one latest-incarnation example known as a CNN (convolutional neural network), the steadily increasing processing “muscle” of CPUs (aided by algorithm acceleration via FPGAs, GPUs, and, more recently, dedicated co-processors), and the steadily decreasing cost of system memory and storage. And, while CNNs’ identification skills are increasingly (if not exceedingly) human-like in…


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