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 ...

Our latest and most advanced technologies — from AI to Industrial IoT, advanced robotics, and self-driving cars — share serious problems: massive energy consumption, limited on-edge capabilities, ...

Modern artificial intelligence systems rely on moving large amounts of data between memory and processors, a design that ...

A computing approach that requires up to 8,000 times less energy than conventional methods is emerging as a potential answer to one of technology’s most significant challenges: the unsustainable ...

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 ...

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 ...

This review first revisits the theoretical background and developmental history of neuromorphic computing. It then briefly introduces the working mechanisms of memristive devices and how they can ...

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 ...

Forbes contributors publish independent expert analyses and insights. Global Thought Leader in Cybersecurity and Emerging Tech Examining the mesh between humans and machines provides insight into the ...