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 ...

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 ...

Artificial intelligence chipmaker Axelera AI B.V. today announced Titania, the next generation of its low-power yet high-performance silicon for running generative AI and computer vision inference ...

Souped up industrial robots and smart devices will revolutionize how we use AI at the edge, and understand cloud and data centers. Humanoid robots, smart devices, and autonomous driving are often ...

Looking to enhance data-driven decision-making for customers in industrial internet of things (IoT) applications, Palantir Technologies has entered into a collaboration with Qualcomm Technologies to ...

The edge is a dynamic environment where data is created by a multitude of devices—sensors, cameras, IoT devices, and more. Managing and orchestrating applications across far-flung edge locations can ...

Despite advances in machine vision, processing visual data requires substantial computing resources and energy, limiting deployment in edge devices. Now, researchers from Japan have developed a ...