Joel Orr's World

What idea? An innovation contest, like what Netflix did. Of course there are already "markets" out there that do this--most notably, Innocentive.com. Nonetheless, a good idea.

It's no surprise that Netflix has launched another contest to improve its
movie-recommendations system—the $1 million the company gave away for the
first Netflix Prize was the steal of the century. On Monday, three years
after the contest kicked off, Netflix awarded the jackpot to BellKor's
Pragmatic Chaos, a team of seven engineers, mathematicians, and computer
scientists who managed to improve the DVD-rental service's recommendations
by 10 percent. BellKor beat out another team—the Ensemble, with more than 30
members—that had achieved the exact same ratings improvement but lost by
turning in its method 20 minutes after BellKor.

Imagine if Netflix had paid all these math whizzes the prevailing wage—say,
$100,000 a year. The company would have had to shell out more than $3
million for just one year of the top performers' time, and that's assuming
it could've sussed out who the top performers were going to be. Of course,
many of the programmers worked far longer than a year, some of them setting
aside their primary occupations in order to work on the Netflix problem
full-time. As Netflix CEO Reed Hastings admitted to the New York Times, "You
look at the cumulative hours and you're getting Ph.D.s for a dollar an
hour."

But even that number discounts the contest's true benefits to Netflix. Had
the company simply put out a help-wanted ad for software engineers, it
probably wouldn't have been able to recruit many of the geniuses it found
through the competition. That's because most of them already have other
jobs. BellKor's members work for, among others, AT&T and Yahoo, and many
members of the Ensemble are employed by the data-consulting firm Opera
Solutions. The participants also spanned the globe. Netflix got submissions
from people in more than 100 countries, and the winning team's members
worked in New Jersey, Montreal, Israel, and Austria.

The Netflix Prize isn't entirely novel. Science prizes date back to at least
the 18th century, when the British government offered ₤20,000 to the first
person to come up with a way to determine a ship's longitude. Other notable
innovation-prize winners include Charles Lindbergh, who won the Orteig Prize
in 1927 for flying across the Atlantic, and SpaceShipOne, which won the 2004
Ansari X Prize, a contest to launch a privately funded manned craft into
space.

But the Netflix effort was unusual for a couple of reasons. First, it was
funded explicitly for the benefit of a private company; though many
participants were interested in finding better ways to predict fickle human
tastes, Netflix was looking for research that would help boost its bottom
line. The company has already folded some of what it learned from the
contest into its recommendations system, and that has helped increase its
customer-retention rate. The Netflix prize is also notable for what it was
after—not a feat of derring-do, like Lindbergh's, or one of engineering,
like SpaceShipOne, but rather a kind of mathematical recipe. Netflix was
looking for an idea—and it turns out that Internet-enabled collaboration is
particularly well-suited to fostering such abstractions.

Indeed, the Netflix Prize should serve as a model for other tech companies
working on hard problems, as it combines the best parts of open-source
development with the best parts of proprietary code. Just like an
open-source project, the prize was remarkable for its spirit of
cooperation—over the life of the contest, competitors frequently became
collaborators, joining one another's teams when they realized that they
could never win by going it alone. The winning team is actually a mélange of
three different teams; they joined up in June, and their winning algorithm
combines the best ideas of each group.

Open-source projects work similarly, but they can sometimes become unwieldy
and unfocused when they grow too large. What's more, the open-source model
can put off developers who—not unreasonably—are interested in some kind of
reward for their work. The prize model solves those problems. Because
there's a reward involved (not just money but also fame), teams have a
natural incentive to stay focused on a goal and to closely monitor each
participant's progress. The winning team—like several others that
participated—worked out a formula to determine each member's share of the
prize money. And, of course, the prize model works out much better for a
sponsoring company like Netflix. By awarding a prize, the company gets to
keep all the fruits of contestants' labors; if it had merely sponsored an
open-source project, Netflix would have had to share all the innovations
that resulted.

The Netflix Prize model will likely work a lot better in the software
business than in other industries that depend on intellectual property.
That's because programmers are used to collaborating with one another, even
when they work for companies that are competitors. Netflix can be considered
a rival to AT&T—both are working on ways to bring movies into people's
homes—but employees of the phone company apparently had no problem helping
out the DVD service. You'd be hard-pressed to find such cross-business
collaboration in, say, the pharmaceutical industry, where secrecy prevails.

So which tech firms can benefit from setting up prizes? My first candidate
is Microsoft. In trying to beat Google's search engine, the company faces a
clear hiring disadvantage—the world's best search engineers want to work for
the world's most committed search company, and that's not Microsoft. What's
more, search engines have proved impervious to open-source development;
Wikipedia's founder Jimmy Wales tried to take on Google with his wikilike
search project in 2007, but the plan foundered and was eventually shut down,
mainly for a lack of interest. How to spark that interest? Money. Microsoft
could offer $10 million to the first team that figures out a way to improve
its search engine by, say, 10 percent. The difficulty here would be in
deciding how to measure the "improvement"; one way of doing so would be to
discreetly test contestants' algorithms on a subset of search engine queries
and then to analyze whether users respond to the results.

Google itself could also do well with a prize. The company is heavily
invested in solving one of the world's hardest tech problems—machine
translation. A prize would be useful here because translation requires a
wide range of expertise—software engineering, linguistics, and a whole lot
of math—and a high-profile award could get people from different disciplines
to team up. Google could award $1 million for each 10 percent improvement in
its algorithm for translating large bodies of text across languages. The
improvements would be measured in accuracy—the team that writes code that
best translates, say, Proust's oeuvre into English would win big.

What else? When you start thinking of problems that could be solved through
competition, it's hard to stop. How about a prize for improving face
recognition in pictures or videos? Or what about one for improving speech
recognition, so that we'll finally get to talk to our computers instead of
type? After all, movies are important—but perhaps Netflix has stumbled on to
something much more useful than a way to tell whether you'll love Napoleon
Dynamite.



Farhad Manjoo is Slate's technology columnist and the author of True Enough:
Learning To Live in a Post-Fact Society. You can e-mail him at
farhad.manjoo@slate.com and follow him on Twitter.
Sept. 22, 2009
Copyright 2008 Washingtonpost.Newsweek Interactive Co. LLC
http://www.slate.com/id/2229225/