 Chaos is a term we used to introduce scientists to ideas that everybody knows. The scientists were the last people to know about chaos, because everybody knows that little changes in your life can make huge impacts. People have to know what to talk about, the words, they have to know the language in order to be able to describe the phenomena. See, so I think of it as telling physicists and mathematicians and engineers what they should be looking for. And that, in fact, is the role that chaos played, because you'll find no mentions of chaos in the engineering books of 1970, or the mechanics books or electrical engineering books. But now everybody knows about chaos in their own systems. An example of chaos is when you play billiards. Forget about friction of the billiard balls. They just bounce around and they bounce around. That's chaos, where the balls hit each other and then they can diverge into different directions. The balls bounce off the table. That's multi-chaos. It's chaotic in more directions. It's all about little changes growing and growing and growing in size. A butterfly flapping its wings causes some little change, a tiny change. And the tiny change causes a little bit bigger change, but maybe not all the time, maybe rarely, but then it can cause bigger changes. On behalf of the butterflies, I have to tell you also that a butterfly flapping its wings can prevent a tornado. Or it might shift the tornado from Texas to Florida. The machine learning can tell you with high accuracy what the state of the system is. And so if I know the initial condition, the state of the system more accurately, if I know more accurately where this billiard ball is, I can predict where it'll be for a longer time. One of the things about the chaos theory you learn is that you don't know what's going to be next. The machine learning that Edward Ott and his colleagues talk about was not something that anybody would predict. And so I like the most interesting areas of science are where I don't know what's going to happen next. And I really don't like to predict. Being a chaos theorist, I don't like to predict the future. Predicting the future is much less important than predicting the present.