Cory Merkel, assistant professor of computer engineering at Rochester Institute of Technology, will represent the university as one of five collegiate partners in the new Center of Neuromorphic ...

Neuromorphic computing, inspired by the neural architectures and functions of biological brains, is revolutionizing the development of highly efficient, adaptive computing systems. In robotics, this ...

Computers have come so far in terms of their power and potential, rivaling and even eclipsing human brains in their ability to store and crunch data, make predictions and communicate. But there is one ...

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 ...

July 10, 2024 — The U.S. Department of Energy’s Advanced Scientific Computing Research (ASCR) program has announced a Monday July 22 deadline (11:59 pm ET) for position papers for a workship on ...

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, ...

Joseph Friedman, associate professor of electrical and computer engineering at the University of Texas at Dallas, uses a probe station to test small neuromorphic devices. Friedman has developed a ...

As modern manufacturing increasingly relies on artificial intelligence (AI), automation, and real-time data processing, the need for faster and more energy-efficient computing systems has never been ...

An international team comprised of 23 researchers has published a review article on the future of neuromorphic computing that examines the state of neuromorphic technology and presents a strategy for ...

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 ...