“Edge computing also means less data travels long distances, lowering the load on main servers and networks,” says Neel ...

The potential of AI to transform businesses is undeniable. But modern companies now face a new challenge: how to take advantage of this complex concept. This is where the edge can be a catalyst for AI ...

Large language models (LLMs) such as GPT-4o and other modern state-of-the-art generative models like Anthropic’s Claude, Google's PaLM and Meta's Llama have been dominating the AI field recently.

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

In an economy driven by real-time data, the ability to make decisions at the edge, right where data is generated, has become ...

AI is being rapidly adopted in edge computing. As a result, it is increasingly important to deploy machine learning models on Arm edge devices. Arm-based processors are common in embedded systems ...

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.

Picture this scenario: At 2:37 a.m. during a storm, lightning strikes a distribution feeder line in rural Wisconsin. A massive power surge races through the distribution network. Instead of triggering ...

Adam Stone writes on technology trends from Annapolis, Md., with a focus on government IT, military and first-responder technologies. Cities and counties have started deploying servers and data ...