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, ...

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 ...

The perovskite-based platform combines high-efficiency solar energy conversion with advanced memory functions needed for AI ...

This review describes various types of low-power memristors, demonstrating their potential for a wide range of applications. This review summarizes low-power memristors for multi-level storage, ...

By Ben Aris in Berlin Russia has presented a domestically developed neuromorphic processor called “Altai”, a brain-inspired ...

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 ...

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 ...

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 ...

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 ...

Developed by the Indian Institute of Science, the neuromorphic computing platform is designed to work alongside existing AI hardware, rather than replace it. The Indian Institute of Science (IISc) has ...