One example that hints at the potential of such systems is KnowItAll, a project by a group of
University of Washington faculty members and students that has been financed by Google. One sample system created using the technology is Opine, which is designed to extract and aggregate user-posted information from product and review sites.
One demonstration project focusing on hotels “understands” concepts like room temperature, bed comfort and hotel price, and can distinguish between concepts like “great,” “almost great” and “mostly O.K.” to provide useful direct answers. Whereas today’s travel recommendation sites force people to weed through long lists of comments and observations left by others, the Web. 3.0 system would weigh and rank all of the comments and find, by cognitive deduction, just the right hotel for a particular user.
“The system will know that spotless is better than clean,” said Oren Etzioni, an artificial-intelligence researcher at the University of Washington who is a leader of the project. “There is the growing realization that text on the Web is a tremendous resource.”
In its current state, the Web is often described as being in the Lego phase, with all of its different parts capable of connecting to one another. Those who envision the next phase, Web 3.0, see it as an era when machines will start to do seemingly intelligent things.
Researchers and entrepreneurs say that while it is unlikely that there will be complete artificial-intelligence systems any time soon, if ever, the content of the Web is already growing more intelligent. Smart Webcams watch for intruders, while Web-based e-mail programs recognize dates and locations. Such programs, the researchers say, may signal the impending birth of Web 3.0.
“It’s a hot topic, and people haven’t realized this spooky thing about how much they are depending on A.I.,” said W. Daniel Hillis, a veteran artificial-intelligence researcher who founded Metaweb Technologies here last year.
Like Radar Networks, Metaweb is still not publicly describing what its service or product will be, though the company’s Web site states that Metaweb intends to “build a better infrastructure for the Web.”
“It is pretty clear that human knowledge is out there and more exposed to machines than it ever was before,” Mr. Hillis said.
Both Radar Networks and Metaweb have their roots in part in technology development done originally for the military and intelligence agencies. Early research financed by the National Security Agency, the Central Intelligence Agency and the Defense Advanced Research Projects Agency predated a pioneering call for a semantic Web made in 1999 by Tim Berners-Lee, the creator of the World Wide Web a decade earlier.
Intelligence agencies also helped underwrite the work of Doug Lenat, a computer scientist whose company, Cycorp of Austin, Tex., sells systems and services to the government and large corporations. For the last quarter-century Mr. Lenat has labored on an artificial-intelligence system named Cyc that he claimed would some day be able to answer questions posed in spoken or written language — and to reason.
Cyc was originally built by entering millions of common-sense facts that the computer system would “learn.” But in a lecture given at Google earlier this year, Mr. Lenat said, Cyc is now learning by mining the World Wide Web — a process that is part of how Web 3.0 is being built.
During his talk, he implied that Cyc is now capable of answering a sophisticated natural-language query like: “Which American city would be most vulnerable to an anthrax attack during summer?”
Separately, I.B.M. researchers say they are now routinely using a digital snapshot of the six billion documents that make up the non-pornographic World Wide Web to do survey research and answer questions for corporate customers on diverse topics, such as market research and corporate branding.
Daniel Gruhl, a staff scientist at I.B.M.’s Almaden Research Center in San Jose, Calif., said the data mining system, known as Web Fountain, has been used to determine the attitudes of young people on death for a insurance company and was able to choose between the terms “utility computing” and “grid computing,” for an I.B.M. branding effort.
“It turned out that only geeks liked the term ‘grid computing,’ ” he said.
I.B.M. has used the system to do market research for television networks on the popularity of shows by mining a popular online community site, he said. Additionally, by mining the “buzz” on college music Web sites, the researchers were able to predict songs that would hit the top of the pop charts in the next two weeks — a capability more impressive than today’s market research predictions.
There is debate over whether systems like Cyc will be the driving force behind Web 3.0 or whether intelligence will emerge in a more organic fashion, from technologies that systematically extract meaning from the existing Web. Those in the latter camp say they see early examples in services like del.icio.us and Flickr, the bookmarking and photo-sharing systems acquired by Yahoo, and Digg, a news service that relies on aggregating the opinions of readers to find stories of interest.
In Flickr, for example, users “tag” photos, making it simple to identify images in ways that have eluded scientists in the past.
“With Flickr you can find images that a computer could never find,” said Prabhakar Raghavan, head of research at Yahoo. “Something that defied us for 50 years suddenly became trivial. It wouldn’t have become trivial without the Web.”
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