The AI landscape is taking a dramatic turn, as small language and multimodal models are approaching the capabilities of larger, cloud-based systems. This acceleration reflects a broader shift toward ...

As drones survey forests, robots navigate warehouses and sensors monitor city streets, more of the world's decision-making is occurring autonomously on the edge—on the small devices that gather ...

From IoT and robotics to industrial automation and smart devices, AI is fundamentally changing how machines operate. But one of the biggest hurdles to widespread adoption has always been the ...

Overview: Edge AI devices prioritize local inference to ensure user data remains stored on the physical hardware instead of ...

TOKYO--(BUSINESS WIRE)--Mitsubishi Electric Corporation (TOKYO: 6503) announced today that it has developed a language model tailored for manufacturing processes operating on edge devices. The Maisart ...

‘Hey Google’ find me a suitable keyword spotting (KWS) model for edge devices. While voice control is essential for modern interfaces like Alexa, Siri, and Hey Google, building KWS models on edge ...

ExecuTorch 1.0 allows developers to deploy PyTorch models directly to edge devices, including iOS and Android devices, PCs, and embedded systems, with CPU, GPU, and NPU hardware acceleration.

With ARM supporting on-device AI processing, energy use drops versus data centers, so you get faster responses and lower ...

Nordic Semiconductor's new nRF54L Series SoC with NPU and Nordic Edge AI Lab make the on-device intelligence easily ...

Edge AI is a form of artificial intelligence that in part runs on local hardware rather than in a central data center or on cloud servers. It’s part of the broader paradigm of edge computing, in which ...