[killerstorm]

> Why is that a stupid thought? What is so preposterous about "just statistics"

Suppose you have N variables x_1, ..., x_10 and you want to predict y_1, ..., y_10. You know that each y_i depend on each x_i in a complex, non-linear way.

How many samples would you need to to make sense of distribution? How does number of samples grow with N?

[geophile]

I have no idea what that has to do with the points you are responding to.

[killerstorm]

Statistics has two meanings:

1. A way to interpret math. E.g. given a computation you might interpret some values as probabilities. 2. A particular set of methods which people use to analyze information as well results of such analysis.

The problem with "just statistics" is that 99% of people would understand it as #2. But deep learning is very much not like "normal" statistics.