This fascinating article by Chris Anderson (of Long Tail fame) in Wired talks about the End of Theory. The End of Models. The End of Hypotheses. The End of Science. There is no need for a theory because the data reveal the story. Some excerpts:

“All models are wrong, but some are useful.”

So proclaimed statistician George Box 30 years ago, and he was right. But what choice did we have? Only models, from cosmological equations to theories of human behavior, seemed to be able to consistently, if imperfectly, explain the world around us. Until now. Today companies like Google, which have grown up in an era of massively abundant data, don’t have to settle for wrong models. Indeed, they don’t have to settle for models at all.

At the petabyte scale, information is not a matter of simple three- and four-dimensional taxonomy and order but of dimensionally agnostic statistics. It calls for an entirely different approach, one that requires us to lose the tether of data as something that can be visualized in its totality. It forces us to view data mathematically first and establish a context for it later. For instance, Google conquered the advertising world with nothing more than applied mathematics. It didn’t pretend to know anything about the culture and conventions of advertising — it just assumed that better data, with better analytical tools, would win the day. And Google was right.

Google’s founding philosophy is that we don’t know why this page is better than that one: If the statistics of incoming links say it is, that’s good enough. No semantic or causal analysis is required.

Speaking at the O’Reilly Emerging Technology Conference this past March, Peter Norvig, Google’s research director, offered an update to George Box’s maxim: “All models are wrong, and increasingly you can succeed without them.”

This is a world where massive amounts of data and applied mathematics replace every other tool that might be brought to bear. Out with every theory of human behavior, from linguistics to sociology. Forget taxonomy, ontology, and psychology. Who knows why people do what they do? The point is they do it, and we can track and measure it with unprecedented fidelity. With enough data, the numbers speak for themselves.

There is now a better way. Petabytes allow us to say: “Correlation is enough.” We can stop looking for models. We can analyze the data without hypotheses about what it might show.

What does this have to do with martial arts or sports? Every style is founded on a model with hypotheses, assumptions, observations, that eventually turn into beliefs that are clung to, ridiculed, whatever. For example, all fights go to the ground so let’s just cut to the chase and focus there. By analyzing video data, jiujitsu365, who admittedly prefers bjj, was able to look at the data and let it tell the real story. With more and more data, especially video data, more interesting findings will emerge in arts, sports, any kind of human behavior. What will that do to the simple models, the simple boxes we draw around reality to make sense of it, and use to focus on training specific areas?

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