As power and latency bottlenecks grow, engineers are exploring neuromorphic chips to deliver low-energy, real-time AI at the edge of embedded and IoT systems.

Neuromorphic engineering is an interdisciplinary field that combines principles from neuroscience, computer science, and electrical engineering to design artificial neural systems, often referred to ...

Neuromorphic computing is an area of engineering that seeks to emulate the biophysical architecture of our nervous system. Such models can take a variety of forms including hardware chips composed of ...

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 ...

Efforts to build brain-inspired computer hardware have been underway for decades, but the field has yet to have its breakout moment. Now, leading researchers say the time is ripe to start building the ...

Our existing computing systems were never intended to process massive amounts of data or to learn from just a few examples on their own.

SpiNNcloud Systems today announced that its cutting-edge supercomputing platform, built on the SpiNNaker2 architecture, has ...

Rochester Institute of Technology recently became one of the inaugural academic partners in the BrainChip University AI Accelerator Program. As part of the university-corporate partnership, RIT’s ...

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 ...

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 ...

Partnership will deliver ultra-low-power intelligence for next-gen consumer, IoT, and smart home devices ...