Memristive devices for deep learning applications

Deep neural networks have become the flagship approach of Artificial Intelligence, and every week, new amazing achievements of such networks are announced. However they come with a challenge: their energy consumption. Deep neural networks running on central or graphical processors can consume thousands times more energy than the brain on similar tasks. Memristive devices are now considered as a fantastic opportunity to reduce the energy consumption of deep learning, and this chapter explains this. First we introduce the general principles of deep neural networks. This allows us to explore to what extent deep neural networks are similar and dissimilar to the brain. In particular we discuss the fundamental reasons for their difference in energy consumption. These considerations made us discuss the opportunities, but also the challenges of implementing deep neural networks with memristive devices, which serves as an introduction for the next two chapters.