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, ...

A recent study published in npj 2D Materials and Applications explores hexagonal boron nitride (h-BN) atomristors, highlighting their notable memory window, low leakage current, and minimal power ...

Researchers developed an Ag/Sb2O3/Au memristor array that mimics brain-like computing, performing on-device image feature extraction with low power consumption, promising smarter and faster electric ...

In a recent article published in Nature Communications, researchers from China presented a significant advancement in neuromorphic computing through the development of ultra-low-power carbon ...

In recent years, power consumption by machine learning technologies, represented by deep learning and generative artificial ...

Because ARM licenses its designs, multiple companies can integrate ARM technology into a single system-on-a-chip, or SoC. A modern smartphone SoC combines CPUs, graphics processors, AI accelerators, ...

Scientists have discovered that electron spin loss, long considered waste, can instead drive magnetization switching in spintronic devices, boosting efficiency by up to three times. The scalable, ...

In a nutshell: The third keynote in the series of Computex CEO speeches was delivered by Arm's Rene Haas, along with Chris Bergey, the SVP and GM of the Client Business at the company. Their keynote ...

The staggering computational demands of AI have become impossible to ignore. McKinsey estimates that training an AI model costs $4 million to $200 million per training run. The environmental impact is ...

At Computex in Taipei, Lokwon Kim, founder and CEO of the Korean semiconductor company DEEPX, shed light on his company's robust capabilities in designing high-performance AI chips that prioritize ...