François CholletVerified account

A good model isn't a description, it's an explanation. An accumulation of observations does not explain anything.

Here's a simple example to capture the difference between a set of observations and an explanation. Consider Google search.

You can type up some keywords and write down what results you get. Then repeat this for thousands (or millions) of queries. At the end of the exercise, you'll have a description of a (tiny) slice of the behavior of the system.

But you will still have no idea that these results are produced via the PageRank algorithm. In fact, you won't have learned anything useful about the system at all. You won't be able to create your own search engine. You won't even know what makes a search engine good.

You will also have gained no context about what surrounds the system -- what search engines are for, or what kind of cultural, technological and economic forces shape the company that developed this one

You will have accumulated terabytes of data about the system, and yet you will still be infinitely far away from what you could learn from a 3-paragraph explanation written by someone who actually understands the system.