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 ...

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 ...

US researchers solve partial differential equations with neuromorphic hardware, taking us closer to world's first ...

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 ...

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 ...

Neuromorphic computers, inspired by the architecture of the human brain, are proving surprisingly adept at solving complex ...

QUT Centre for Robotics researchers have developed a new robot navigation system. Locational Encoding with Neuromorphic Systems (LENS) is set to transform how autonomous robots operate. At its core, ...

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 ...

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 ...

An interdisciplinary team of researchers are working on a radically new kind of computer called a neuromorphic computer, inspired by the human brain. Mock-up of a quantum photonic device, which could ...

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 ...

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 ...