Short bytes: Deep Learning has high computational demands. To develop and commercialize Deep Learning applications, a suitable hardware architecture is required. There is a huge ongoing competition to develop efficient hardware platforms for Deep Learning application deployment. Here, we shall discuss specific hardware requirements and how the future looks for Deep Learning hardware. Deep Learning is the hottest topic of this decade and may as well be for forthcoming ones too. Although it may seem on the surface, Deep Learning is not all about math, creating models, learning and optimization. The algorithms must run on optimized hardware and learning tens of thousands of data may take a long time, even weeks. There is a growing need for faster and more efficient hardware for Deep Learning Networks. It is easy to observe that not all processes run efficiently on a CPU. Gaming and Video processing requires dedicated hardware – the Graphics Processing Un...
