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 ...

Adding zinc ions to lithium niobate crystals cuts the energy needed for polarization switching by 69%, enabling visible-light programming of memristors for brain-inspired computing.

Tested against a dataset of handwritten images from the Modified National Standards and Technology database, the interface-type memristors realized a high image recognition accuracy of 94.72%. (Los ...

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 ...

Neuromorphic computing -- a field that applies principles of neuroscience to computing systems to mimic the brain's function and structure -- needs to scale up if it is to effectively compete with ...

Neuromorphic computing may be in its early days, but the hope it offers for smarter, more efficient machines is likely to stick around. Subscribe to stay connected to Tucson. A subscription helps you ...

For how powerful today’s “smart” devices are, they’re not that good at working smarter rather than working harder. With AI constantly connected to the cloud and the chip constantly processing tasks ...

An international team comprised of 23 researchers has published a review article on the future of neuromorphic computing that examines the state of neuromorphic technology and presents a strategy for ...

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.

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