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 ...

(Nanowerk News) A novel device consisting of metal, dielectric, and metal layers remembers the history of electrical signals sent through it. This device, called a memristor, could serve as the basis ...

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 ...

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 ...

A December 10–12 working group met to bring together researchers from two fields — neuromorphic computing and stochastic thermodynamics — to think about ways our built computers might replicate the ...

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 ...

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