The concept of neural networks first emerged more than 40 years ago when scientists experimented with mathematically modelling the functions of the brain. They worked out they could make a mechanical implementation of the neural network that could be trained to recognize patterns and classify data — for example recognizing whether a video contains a cat or a dog. Over the past decade, the complexity and capacity of neural networks has increased sharply. Coinciding with the extraordinary growth of cheap and easily accessible heavy-duty supercomputers and graphics processing units (GPUs), they have come to the fore as the de facto…
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How binarized networks work — and why they’ll be big for AI in 2020
Source: The Next Web
