Our brains are great at knowing what to forget. We actually have to teach computers to do the same.

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.

High fidelity is a rich experience, and you'll put up with terrible convenience to get it - maybe it's high cost, waiting in line, jumping through hoops. High convenience is the opposite - it's a commodity, but it's cheap and easy and ubiquitous. A great exclusive boutique shop is high fidelity; Wal-Mart is high convenience. Both are hard to establish in their own way. The thing to remember about sustaining either is that you can't sit still. Some other entity will always find a way to challenge your fidelity position or your convenience position.

We learn more about how human brains work. And that leads us to ideas about how to make human brains work better.

I reluctantly signed up for a journalism major, thinking I needed a fall-back way to make money should my career as a novelist fail to take off. As I started to try on journalism, including doing internships and working at the campus paper, I found I actually liked it. So I started to want to be a journalist.

Our brains are great at knowing what to forget. We actually have to teach computers to do the same.

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.