Our latest and most advanced technologies — from AI to Industrial IoT, advanced robotics, and self-driving cars — share serious problems: massive energy consumption, limited on-edge capabilities, ...

The University of Michigan is collaborating with IBM to develop and deliver “data-centric” supercomputing systems designed to increase the pace of scientific discovery in fields as diverse as aircraft ...

This article was published in Scientific American’s former blog network and reflects the views of the author, not necessarily those of Scientific American For the past few years, tech companies and ...

Right now, AI is quickly transforming everything from content creation and cybersecurity to drug discovery and supply chains. But beneath all the buzz around ChatGPT ...

BUFFALO, N.Y. — It’s estimated it can take an AI model over 6,000 joules of energy to generate a single text response. By comparison, your brain needs just 20 joules every second to keep you alive and ...

Neuromorphic computing, inspired by the brain, integrates memory and processing to drastically reduce power consumption compared to traditional CPUs and GPUs, making AI at the network edge more ...

Every thought you have, every face you recognise and every memory you recall is powered by an organ that consumes roughly the ...

The neuromorphic chip market offers key opportunities in energy-efficient AI processing, real-time edge intelligence, and enhanced perception for autonomous systems. Rising AI energy demands, ...

This collection supports and amplifies research related to SDG 9 - Industry, innovation and infrastructure. The exploration of two-dimensional materials has garnered significant attention in recent ...