AI Architectures Must Change


Using existing architectures for solving machine learning and artificial intelligence problems is becoming impractical. The total energy consumed by AI is rising significantly, and CPUs and GPUs increasingly are looking like the wrong tools for the job. Several roundtables have concluded the best opportunity for significant change happens when there is no legacy IP. Most designs have evolved... » read more

How The Brain Saves Energy By Doing Less


One of the arguments for neuromorphic computing is the efficiency of the human brain relative to conventional computers. By looking at how the brain works, this argument contends, we can design systems that accomplish more with less power. However, as Mireille Conrad and others at the University of Geneva pointed out in work presented at December's IEEE Electron Device Meeting, the brain... » read more

Manufacturing Bits: Aug. 19


28nm brain chips DARPA-funded researchers have developed a 28nm chip that mimics the brain. The low-power chip is inspired by the neuronal structure of the brain. Designed by researchers at IBM under DARPA’s Systems of Neuromorphic Adaptive Plastic Scalable Electronics (SyNAPSE) program, the chip consists of 5.4 billion transistors. Built on Samsung’s 28nm foundry process, the chip has ... » read more