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Edge computing’s rise will drive cloud consumption, not replace it

Successful edge AI deployments require deep integration between edge and cloud, complex orchestration and new approaches to data management.

As AI moves beyond centralized data centers, we’re seeing smartphones run sophisticated language models locally, smart devices processing computer vision at the edge and autonomous vehicles making split-second decisions without cloud connectivity. In fact, edge inference represents only the final step in a complex AI pipeline that depends heavily on cloud computing for data storage, processing and model training. The dramatic reduction in data transfer requirements, combined with strong accuracy preservation, demonstrated how cloud-edge systems could maintain high performance even in challenging network conditions.

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