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 ...

The concept of edge-first intelligence entails embedding critical data and inference models directly into the application or ...

‘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 ...

Researchers from The University of Osaka's Institute of Scientific and Industrial Research (SANKEN) have successfully developed a "self-evolving" edge AI technology that enables real-time learning and ...

SAN JOSE, Calif.--(BUSINESS WIRE)--Edge Impulse, the leading platform for building, deploying, and scaling edge machine learning models, today announces Microchip Technology’s SAMA7G54 microprocessor ...

A major next step for artificial intelligence (AI) and machine learning (ML) innovation is moving ML models from the cloud to the edge for real-time inferencing and decision-making applications in ...

Large language models are powerful, but generally they require vast computing resources, which means they typically have to run on stacks of high-end GPUs in data centers. Now, startup Multiverse ...

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 ...

The hunt is on for anything that can surmount AI’s perennial memory wall–even quick models are bogged down by the time and energy needed to carry data between processor and memory. Resistive RAM (RRAM ...

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.