MLOps for edge AI: Managing AI models across distributed fleets

Deploying AI at the edge is both rewarding and challenging. In previous articles, you've seen how to optimize and package your edge AI models and how to execute them to fulfill common use case requirements at the edge, but there's more.In this article, we'll switch our focus from model and service architecture to the management questions that affect our edge AI use case once a model runs across thousands of devices. We'll answer questions such as: How do you know…

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