Machine Learning From Streaming Data: Two Problems, Two Solutions, Two Concerns, and Two Lessons

Like most things that are over-hyped, what is actually meant by the term is often lost in the noise. In this case that's really a shame, because these terms refer to at least two different things, either or both of which may be important in a given context. This post forms the basis of a lightning talk I'm giving (remotely) at the Real-time Big Data Meetup in Menlo Park, California. Generally, when I hear people talking about "machine learning from streaming data", they may be talking about a couple of things. These two phenomena sound like the same thing, but they are potentially very different.