High Performance Input Pipelines for Scalable Deep Learning
A production AI system is more than just training a deep learning model. It also includes 1) ingesting and running inference on new data, 2) transformation, processing, and cleaning new data to incorporate it into the training set, 3) continuously retraining to update and continue learning, and 4) experimental pipeline to test improvements to the AI models. This presentation focuses on the importance of highperformance and highlyscalable storage that is needed to take advantage of everlarger datasets in
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