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 entering a new era – one where processing can be performed at the Edge and is no longer confined to a data centre.

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Performance enhancement, cost reduction, data security, and improved energy efficiency are the end goals for optimizing AI workloads at the edge.

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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 ...

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 ...