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This is the simplest case. Upon creating a model CRD object, the edge part of the model controller should get notified and prepare the local workspace for the new model. By specifying the target model version to pull, the controller will download the corresponding model files (the whole directory can be compressed into a tarballtar ball) from the provided URL endpoint.
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Upon creating a model CRD object, edge needs to download the training scripts (running runs on edge) and initial model weights files from provided URL endpoint. Once the gradients have been calculated, they should be reported back to cloud worker.
It looks like the common behavior of the model CRD object is just to download and upload data and executable files (of different types) to a cloud location.The whole AI framework should not entail external , i.e. some storage service like AWS S3.