Smaller models, lightweight frameworks, specialized hardware, and other innovations are bringing AI out of the cloud and into ...

As you prepare for an evening of relaxation at home, you might ask your smartphone to play your favorite song or tell your home assistant to dim the lights. These tasks feel simple because they’re ...

As drones survey forests, robots navigate warehouses and sensors monitor city streets, more of the world's decision-making is ...

From IoT and robotics to industrial automation and smart devices, AI is fundamentally changing how machines operate. But one of the biggest hurdles to widespread adoption has always been the ...

Overview: Edge AI processes data locally, cutting latency, boosting security, and enabling real-time decisions without ...

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 ...

What happens when intelligence moves off the cloud and onto the device? Edge AI Studio cuts latency, improves performance, ...

With ARM supporting on-device AI processing, energy use drops versus data centers, so you get faster responses and lower ...

Overview: Edge AI devices prioritize local inference to ensure user data remains stored on the physical hardware instead of ...

‘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 ...