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I have a confession to make. I cried during the compiler class in college. I became a machine learning engineer so that I wouldn’t have to worry about compilers. However, as I learned more about bringing ML models into production, the topic of compilers kept coming up. In many use cases, especially when running an ML model on the edge, the model’s success still depends on the hardware it runs on, which makes it important for people working with ML models in production to understand how their mod...