The promise of AI has tantalized computer scientists and the general public for a long time, with general human intelligence out of grasp even still, however, modern advances in approaches to implementing machine learning algorithms coupled with a dramatic growth in computational capacity have yielded powerful tools to address discrete problem domains. What machine learning isn't, is trying to build human-level general intelligence into machines. Instead, as the name connotes, it's about creating programs that enable computers to use example data or past experience to solve a given, discrete, problem.