The opposite of that is rule-based computing or rule-based expert systems. You can come up with 10, 20, 30 rules and so on, but you can never come up with enough rules to handle the exceptions. Sonal Chokshi: Exactly. Is machine learning for the exception handling then, or for everything? How does that work when you’re talking about computing? Christopher N.: In a very real sense it is. You can think of it as for exception handling, but I like to think of it in terms of analogy as wisdom. You do have the rules but then you know when the rules don’t apply. The reason you know when the rules don’t apply is because you’ve seen three or four or five corner cases before. Somehow “intuitively” you find that in this situation that rule doesn’t apply, but what we think of as intuition are actually, you can think of as parameters inside a machine-learning model. - https://medium.com/deep-learning-101/what-you-must-know-about-big-data-and-machine-learning-e6051a76ccd0