The Rise Of Client-Side Deep Learning

As chips become smaller and more powerful, and as new ways to accelerate deep learning are discovered, it’s not just large data centers that can run the “artificial intelligence” in your devices, but also small embedded chips can be put into anything from IoT devices to self-driving cars.Deep Learning Training There are two stages when working with deep neural networks. In the first stage, the neural network is “trained.” That’s when the parameters of the network are determined using examples of labeled inputs and a desired output. For instance, the network could be trained to “learn” how a human face looks by feeding it millions of pictures with human faces. In the past, machine learning engineers used to code these parameters manually, which was a highly complex task and produced…


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