EurekAlert!

Low-power memristor for neuromorphic computing: From materials to applications

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, ...

From ‘Optical Synapses’ to a ‘Photonic Brain’ — Integrated Photonic Neural Networks Toward Low-Power General-Purpose

SHANNON, CLARE, IRELAND, February 5, 2026 /EINPresswire.com/ -- A new publication from Opto-Electronic Technology; DOI ...
techtimes

Neuromorphic Chips and 'Brain‑Like' Computing: How Next‑Gen Chips May Change Phones, Robots, and IoT Devices

Explore how neuromorphic chips and brain-inspired computing bring low-power, efficient intelligence to edge AI, robotics, and IoT through spiking neural networks and next-gen processors. Pixabay, ...
Nasdaq

Fujitsu and Yamaguchi University develop low-power edge computing technology for near real-time image processing on small satellites

Kawasaki and Yamaguchi, Japan, Nov 27, 2025 - (JCN Newswire) - - Fujitsu Limited and Yamaguchi University today announced the successful development of a low-power edge computing technology that ...
Hosted on MSN

Turning spin loss into energy: New principle could enable ultra-low power devices

A research team has developed a device principle that can utilize "spin loss," which was previously thought of as a simple loss, as a new power source for magnetic control. Subscribe to our newsletter ...
Business Wire

The Global Market for Low Power/High Efficiency AI Semiconductors, 2026-2036 - Neuromorphic Computing and In-Memory Architectures Pave the Way for AI Semiconductor Market ...

DUBLIN--(BUSINESS WIRE)--The "The Global Market for Low Power/High Efficiency AI Semiconductors 2026-2036" has been added to ResearchAndMarkets.com's offering. The market for low power/high efficiency ...
Science Daily

Scientists turn spin loss into energy, unlocking ultra-low-power AI chips

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, ...
AZoNano

Hexagonal Boron Nitride Atomristors: A Low-Power Solution for Neuromorphic Computing

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 ...