Memristor based self organizing adaptive neural network chip could speed image and video processing by 1000 times
Loosely inspired by a biological brain’s approach to making sense of visual information, a University of Michigan researcher is leading a project to build alternative computer hardware that could process images and video 1,000 times faster with 10,000 times less power than today’s systems—all without sacrificing accuracy. DARPA has awarded up to $5.7 million to …