Neurophos is taking a crack at solving the AI industry's power efficiency problem with an optical chip that uses a composite material to do the math required in AI inferencing tasks.

“We must strive for better,” said IBM Research chief scientist Ruchir Puri at a conference on AI acceleration organised by ...

A novel stacked memristor architecture performs Euclidean distance calculations directly within memory, enabling ...

Given the rapidly evolving landscape of Artificial Intelligence, one of the biggest hurdles tech leaders often come across is ...

AMD researchers argue that, while algorithms like the Ozaki scheme merit investigation, they're still not ready for prime ...

From the UCSB The Current article "Innovative Hardware for Rapidly Solving High-order Optimization Problems" The rise of AI, graphic processing, combinatorial optimization, and other data-intensive ...

As artificial intelligence hardware advances toward higher efficiency and greater intelligence, enabling individual physical devices to perform more ...

A research team from Peking University has successfully developed a vanadium oxide (VO₂)-based “locally active memristive oscillator” that operates at the edge of chaos. Through simple signal ...

With Moore’s law approaching its end, traditional von Neumann architectures are struggling to keep up with the exceeding performance and memory requirements of artificial intelligence and machine ...

Abstract: A mixed-precision analog compute-in-memory (Mix-ACIM) is presented for mixed-precision vector-matrix multiplication (VMM). The design features an all-analog current-domain fixed-point (FxP) ...