Neuromorphic computers, inspired by the architecture of the human brain, are proving surprisingly adept at solving complex mathematical problems that underpin scientific and engineering challenges.

New research shows that advances in technology could help make future supercomputers far more energy efficient. Neuromorphic computers are modeled after the structure of the human brain, and researche ...

Researchers developing next-generation computer systems at Rochester Institute of Technology are designing brain-inspired computer architectures using memristors that will have increased processing ...

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 ...

Dr. Joseph S. Friedman and his colleagues at The University of Texas at Dallas created a computer prototype that learns patterns and makes predictions using fewer training computations than ...

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 ...

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 ...

When you buy through links on our articles, Future and its syndication partners may earn a commission. Although neuromorphic computing was first proposed by scientist Carver Mead in the late 1980s, it ...

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 cognitive. That ...

Sandia National Labs today released an update on its neuromorphic computing research, reporting that these systems, inspired by the architecture of the human brain, are surprisingly adept at solving ...

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 ...