Select your localized edition:

Close ×

More Ways to Connect

Discover one of our 28 local entrepreneurial communities »

Be the first to know as we launch in new countries and markets around the globe.

Interested in bringing MIT Technology Review to your local market?

MIT Technology ReviewMIT Technology Review - logo


Unsupported browser: Your browser does not meet modern web standards. See how it scores »

{ action.text }

Providing answers to tricky questions has become big business online. But community question-and-answer sites can get clogged up with outdated answers, and it’s fiendishly difficult to create software that can automatically understand a question and provide the best answer.

Damon Horowitz, chief technology officer and cofounder of the San Francisco-based Aardvark, will outline a different approach when he speaks at the Web 2.0 Expo in New York today. Horowitz believes that the real power of natural language processing can only be unlocked by acknowledging its limitations and filling in the gaps with human intelligence. The company launched its product to the public last month.

Aardvark has done extensive research into using artificial intelligence techniques to answer questions, but the company’s focus has shifted away from training machines to respond. “We wanted to let another human being answer and have the machine do the heavy lifting of indexing everybody–the tens of thousands of people who are in your extended network and all of the things that those people know,” Horowitz says.

The difficulty of having machines interpret meaning has forced many “semantic Web” companies to focus on niche areas, such as answers to questions about medicine. “There’s a reason why all of our artificial intelligence systems only do so well with language processing tasks,” Horowitz adds. “Language has much more to do with live interaction with another person–understanding context and forming a connection.”

When a new user signs up to use Aardvark, she is asked to enter her Facebook login information and list of topics she is knowledgeable about. When a she asks a new question–for example, “What’s the name of a good restaurant in Cambridge, MA?”–the system tries to find other users who can answer it.

Aardvark has to parse the question to determine its topic before hunting for users with related interests. But the system also looks for potential answerers who are connected socially. It does this by gathering data from Facebook connections, and searching Twitter messages and relevant blog posts. The result, Horowitz says, is artificial intelligence that facilitates a human connection, helping users find someone who “is going to look you in the virtual eye.”

9 comments. Share your thoughts »

Credit: Aardvark

Tagged: Business, Communications, social networks, data mining, social search, user-generated content, expertise search

Reprints and Permissions | Send feedback to the editor

From the Archives


Introducing MIT Technology Review Insider.

Already a Magazine subscriber?

You're automatically an Insider. It's easy to activate or upgrade your account.

Activate Your Account

Become an Insider

It's the new way to subscribe. Get even more of the tech news, research, and discoveries you crave.

Sign Up

Learn More

Find out why MIT Technology Review Insider is for you and explore your options.

Show Me