Edge AI, which is the distributed computing procedure of running artificial intelligence (AI) models locally on devices out in the world closer to where the data is actually gathered, rather than on central servers, is a technique quickly gaining traction in different verticals. This is because Big Data, Internet of Things (IoT), and hardware innovations are increasingly pushing the limits of what’s possible and what’s required. Edge AI has a few distinct advantages over traditional cloud-based AI computation. In this article, AI Impact host Toni Witt runs through the most important ones.
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