Researchers from The University of Osaka's Institute of Scientific and Industrial Research (SANKEN) have successfully ...

A new technique enables on-device training of machine-learning models on edge devices like microcontrollers, which have very limited memory. This could allow edge devices to continually learn from new ...

Microsoft announced on-device training of machine language models with the open source ONNX Runtime (ORT). The ORT is a cross-platform machine-learning model accelerator, providing an interface to ...

Researchers focus on limiting data movement to reduce power and latency in edge devices. In popular media, “AI” usually means ...

A new technical paper titled “On-Device Training Under 256KB Memory” was published by researchers at MIT and MIT-IBM Watson AI Lab. “Our study enables IoT devices to not only perform inference but ...

This DIY AI Health Assistant Trained with Edge Impulse, the Edge ML model detects real-time anomalies in SpO₂ and heart rate, ...

Qualcomm is putting the pieces in place to shift edge AI systems from custom embedded mashups to scalable, AI-enhanced computing platforms. AI is expanding beyond the cloud, turbocharging industrial ...

The collaborative machine learning startup FedML Inc. said today it has closed on an $11.5 million seed funding round. The round was made up of two separate tranches. The first raised $4.3 million and ...

It can be done, but it requires the edge device vendor to work to optimize the model. A hybrid approach can also extend the applicability of LLMs by combining Cloud and Edge processing. When most ...