Via Alex Knapp, here's an article about the X Prize, a privately-funded $10 million prize for the first privately-financed team to:

Build a spacecraft capable of taking three passengers 62.5 miles (101 kilometers) above the planet, then make a second successful suborbital trip within two weeks.

The prize was established in 1996, but some experts think it's going to be claimed this year. And the leading favorites, according to the article, are Scaled Composites of Mojave, California, and Armadillo Aerospace of Mesquite, Texas.

Mesquite, incidentally, is a suburb of Dallas, right next door. Here's Armadillo Aerospace's website. They aren't begging for money...under the investment section of the site it says: Armadillo Aerospace is fully self funded.

But you can buy a T-shirt with their mascot Widget, an armadillo in goggles and scarf.

Since they're the hometown team, I pretty much have to root for them.

These sorts of prizes are a great idea. The founder got the idea this way:

Maryniak recounted how space tourism advocate Peter Diamandis read Charles Lindbergh's "The Spirit of St. Louis" autobiography and realized how aviation contests, like the $25,000 Orteig prize awarded to Lindbergh for crossing the Atlantic in 1927, helped launch mainstream air travel.

Nothing, after all, spurs motivation like money. Bragging rights are nice, too.

It's a bit sad that there's not a comparable prize for the field of AI. For Go AI, there was the Ing Prize, a $1.4 million prize for the first programmer or team to develop an AI that could beat a professionally-ranked human Go player. But it expired in 2000, and no comparable prize is offered, as far as I know.

Addendum: Of course, there is the DARPA Grand Challenge, which I've blogged about before, which would technically qualify as an AI contest, and there are smaller competitions for things like robotic soccer and game play. But the DARPA challenge requires a very large amount of knowledge about mechanics and engineering, and the AI for these autonomous vehicles has more to do with accumulating and parsing sensory information than decision making.