MLOps for edge AI: Preparing AI models for deployment at the edge

When I started playing with AI models for edge computing use cases, everything went smoothly. But once I reached the "it works" point and started thinking about how to operationalize it, the whole thing became more complicated. I started to question how a trained model becomes something you can ship to the edge. How can I get the most out of edge devices while running AI models? How can I manage hundreds of distributed models? How can I maintain accuracy…

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