“What does it take to operationalize machine learning and AI in an enterprise setting?
Machine learning in an enterprise setting is difficult, but the market makes it seem easy. All you need is some smart people, some tools, and some data. It’s a long way from having an environment to build ML applications to the environment needed to run them in an enterprise.
Most of what we know about production ML and AI come from the world of web and digital startups and consumer services, where ML is a core part of the services they provide. These companies have fewer constraints than most enterprises do.
This session describes the nature of ML and AI applications and the overall environment they operate in, explains some important concepts about production operations, and offers some observations and advice for anyone trying to build and deploy such systems.”