MLOps and data centricity
Selecting what hardware to run AI workloads on can be thought of as part of the end-to-end process of AI model development and deployment, called MLOps — the art and science of bringing machine learning to production. To draw the connection with AI chips, standards and projects such as ONNX and Apache TVM can help bridge the gap and alleviate the tedious process of machine learning model deployment on various targets.
What we see as the most profound shift, however, is the emphasis on so-called data-centric AI.
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