Every purchasing decision involves a trade-off between what I call fidelity and convenience. Fidelity is the total experience of something - how great the experience is. Convenience is how easy it is to get something. A live concert is a high fidelity way to experience music; an MP3 file is a high convenience way to experience music. Depending on the situation, one or the other is probably pretty appealing. What's not appealing is something that offers neither.

Fidelity is the total quality of an experience, including a sense of exclusiveness and aura. Convenience is simply how easy something is to get, which often means a low price and ubiquitousness. A super-fidelity product or service would lose its luster and quality if it's pushed too hard toward convenience. A super-convenient product or service would start to get expensive and exclusive if it moved toward higher fidelity, which would naturally undermine its convenience.

The explosion of the Web and digital media from 1995 to 2000 shook companies more profoundly in a shorter time than anything since the end of World War II.

Some people seem to have extreme natural wiring - a talent that seems to come out of nowhere. Like a music savant or prodigy. The uplifting news, though, is that many talented people don't have such natural wiring - but they forge a talent through thousands of hours of what's known as deliberate practice or deliberate performance.

Some of what we're learning suggests a balance between exposing children to new things, yet giving them a chance to repeatedly experience something they enjoy, which builds "chunks" of information in their brains.

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

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.