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 ...
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 ...
New eIQ Agentic AI Framework enables autonomous agentic intelligence at the edge, adding a new pillar to NXP’s edge AI platformBrings agentic AI ...
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 ...
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 ...
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.
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 ...
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 ...
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