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 ...

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 ...

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 ...

As large language models (LLMs) like ChatGPT and machine learning (ML) generate seemingly endless media and industry buzz around the promise of generative AI, the growth of these technologies brings ...

From smartwatches for health monitoring to hearing aids with AI-driven noise cancellation, these products are redefining how we live our lives. However, the growing complexity of these devices ...

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 ...