If you spot a market where the only choices are at either one end or the other - high fidelity or high convenience - there's probably a big opportunity at the other end. That was the opening for Federal Express, for instance. When it started, there was only one mail service in America - the US Postal Service, which was high convenience. Fred Smith created a high-fidelity mail service.

Now companies tend to mine gigantic databases for insights into what might happen six months from now. That might always be valuable, but there's a different kind of value - and a competitive edge - in processing ongoing streams of data through a software model that can quickly and constantly make predictions about, say, whether a certain customer is going to defect, or an aircraft is going to run into trouble.

I knew I wanted to be a writer from as far back as I can remember. That was my talent. Lord knows it wasn't math.

A CD these days is not all that convenient, and it doesn't bring enough fidelity to make you put up with that inconvenience. So, nobody buys CDs anymore.

When someone is in a state of flow, that person's brain is not thinking about anything - it's just processing things through chunks at a total instinct level. Athletes in a state of flow describe knowing what will happen just before it does - knowing how a defender will react to a certain move an instant before doing it. Of course, if you know what will happen, you can succeed at doing it, so an athlete in flow has a stand-out game.

Eventually, we need to have computers that work differently from the way they do today and have for the past 60-plus years. We're capturing and generating increasingly massive amounts of data, but we can't make computers that keep up with it. One of the most promising solutions is to make computers that work more the way brains work.

Artificial intelligence uses a complex set of rules - algorithms - to get to a conclusion. A computer has to calculate its way through all those rules, and that takes a lot of processing. So AI works best when a small computer is using it on a small problem - your car's anti-lock brakes are based on AI. Or you need to use a giant computer on a big problem - like IBM using a room-size machine to compete against humans on Jeopardy in 2011.