Brain-inspired computing promises cheaper, faster, more energy efficient processing, according to experts at a Beijing conference, who discussed everything from reverse engineering insect brains to ...

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 ...

Dhireesha Kudithipudi (second from right), founding director of MATRIX at UTSA, chats with students during the NSF AI Spring School at UTSA's San Pedro I building. The research is part of a broader ...

Large scale datasets and information processing requirements, within complex environments, are continuously reaching unprecedented levels of sophistication, especially in the advent of artificial ...

Catherine Schuman, a neuromorphic computing researcher and assistant professor in the Department of Electrical Engineering and Computer Science (EECS) at the University of Tennessee. Computers are ...

Explore how neuromorphic chips and brain-inspired computing bring low-power, efficient intelligence to edge AI, robotics, and IoT through spiking neural networks and next-gen processors. Pixabay, ...