Large Language Models (LLMs) have taken the world by storm since the 2017 Transformers paper, but pushing them to the edge has proved problematic. Just this year, Google had to revise its plans to ...

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 ...

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 ...

ROCKVILLE, Md.--(BUSINESS WIRE)--Ceva, Inc. (NASDAQ: CEVA), the leading licensor of silicon and software IP that enables Smart Edge devices to connect, sense and infer data more reliably and ...

SAN JOSE, Calif.--(BUSINESS WIRE)--Edge Impulse, the leading platform for building, deploying, and scaling edge machine learning models, today announces Microchip Technology’s SAMA7G54 microprocessor ...

At one time or another, nearly everyone has wished they could be in two places at once. Now, with help from advancements in computer vision and artificial intelligence (AI) at the edge, engineers may ...

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 ...

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 ...

Noting a growing demand for artificial intelligence (AI) that can run on edge devices with microcontrollers (MCUs) and microprocessors (MPUs), NXP Semiconductors has unveiled tools to enable ...

The latest trends in software development from the Computer Weekly Application Developer Network. This is a guest post for the Computer Weekly Developer Network written by Dr Juan Bernabe-Moreno in ...