"One of the most interesting aspects of the world is that it can be considered to be made up of patterns" - Norbert Wiener (1940s) We are entering a new and long-tail phase of software development with Machine Learning (ML). ML, a subset of AI, is the ability of a machine to produce accurate results for a particular problem without any explicit programming. These predictive results are derived from recognizing patterns in large data sets. We are effectively giving machines the ability to gain experience. This megatrend affects our applications, software tools, data structures, systems architecture, new hardware approaches, business processes, organizational interactions, enterprise strategies, government behavior, geopolitical strengths, ethics, data privacy, etc. In essence, ML is an inflection point for computing, enterprises, countries, humanity, and civilization. We’ll explore some basic ML use cases, take a look at JSR #381 (Visual Recognition for Java), and then dive into issues, strategies, and the near-term and long-term directions of ML.