Neural Net Computing Explodes

Kim pointed to convolutional neural networks, recurrent neural networks, and Long Short Term Memory (LSTM) networks, among others, each of which is designed to solve a specific problem, such as image recognition, speech or language translation. Norm Jouppi, a Google distinguished hardware engineer, unveiled details of the company's several-year effort, the Tensor Processor Unit (TPU), an ASIC that implements components of a neural network in silicon--as opposed to using raw silicon compute power and memory banks and software on top of that, which is something that Google also does. In discussing the Google TPU, Jouppi highlighted one way that teams of researchers and engineers around the world can benchmark their work and the performance of the hardware and software they are utilizing: ImageNet. Arnold Smeulders and Theo Gevers, the general chairs of ECCV 2016, told Semiconductor Engineering that many of the attendees of ECCV do work in the area of semiconductor technologies (as opposed to software that runs on silicon) that enable computer vision.