Sublime

PA builds its power by combining dozens—or even hundreds—of predictors.

Bayesians are concerned above all with uncertainty. All learned knowledge is uncertain, and learning itself is a form of uncertain inference. The problem then becomes how to deal with noisy, incomplete, and even contradictory information without falling apart. The solution is probabilistic inference, and the

Knowing who your “good” customers are—the ones who will buy more—may be nice to know, but it takes second place.

once worked on an HP project that predicted the potential demand of its corporate clients—how many computers will the company need to buy, and how much of that need is currently covered by HP’s competitors?

EVER-SMARTER COMPUTERS: FRIEND OR FOE?

Armed with machine learning, a manager becomes a supermanager, a scientist a superscientist, an engineer a superengineer. The future belongs to those who understand at a very deep level how to combine their unique expertise with what algorithms do best.

“What I cannot create, I do not understand.”)

If you want to be tomorrow’s authority, ride the data, don’t fight it.