AI in Production: the Final Frontier

Production is often viewed as the final frontier in the machine learning process. By now, your data scientists trained a model on your data, the machine learning and software engineers incorporated that model into an application, the DevOps team configured the automation that containerizes the application for use by the rest of the organization, and the IT department set up infrastructure to host your model's application. At this point, most program managers flip the proverbial switch, allow users to rely on the solution, and move on to the next thing. That's also the wrong thing to do. This blog in the ModelOps blog series covers the model production step in the ModelOps pipeline, or AI in production, and the active management required to successfully field a machine learning model.