Coming: Web 3.0, in which the Web becomes more intelligent

1. Entrepreneurs See a Web Guided by Common Sense -- by JOHN MARKOFF

SAN FRANCISCO — From the billions of documents that form the World Wide Web and the links that weave them together, computer scientists and a growing collection of start-up companies are finding new ways to mine human intelligence.

Their goal is to add a layer of meaning on top of the existing Web that would make it less of a catalog and more of a guide — and even provide the foundation for systems that can reason in a human fashion. That level of artificial intelligence, with machines doing the thinking instead of simply following commands, has eluded researchers for more than half a century.

Referred to as Web 3.0, the effort is in its infancy, and the very idea has given rise to skeptics who have called it an unobtainable vision. But the underlying technologies are rapidly gaining adherents, at big companies like I.B.M. and Google as well as small ones. Their projects often center on simple, practical uses, from producing vacation recommendations to predicting the next hit song.

But in the future, more powerful systems could act as personal advisers in areas as diverse as financial planning, with an intelligent system mapping out a retirement plan for a couple, for instance, or educational consulting, with the Web helping a high school student identify the right college.

The projects aimed at creating Web 3.0 all take advantage of increasingly powerful computers that can quickly and completely scour the Web.

“I call it the World Wide Database,” said Nova Spivack, the founder of a start-up firm whose technology detects relationships between nuggets of information by mining the World Wide Web. “We are going from a Web of connected documents to a Web of connected data.”

Web 2.0, which describes the ability to seamlessly connect applications (like geographic mapping) and services (like photo-sharing) over the Internet, has in recent months become the focus of dot-com-style hype in Silicon Valley. But commercial interest in Web 3.0 — or the “semantic Web,” for the idea of adding meaning — is only now emerging.

The classic example of the Web 2.0 era is the “mash-up” — for example, connecting a rental-housing Web site with Google Maps to create a new, more useful service that automatically shows the location of each rental listing.

In contrast, the Holy Grail for developers of the semantic Web is to build a system that can give a reasonable and complete response to a simple question like: “I’m looking for a warm place to vacation and I have a budget of $3,000. Oh, and I have an 11-year-old child.”

Under today’s system, such a query can lead to hours of sifting — through lists of flights, hotel, car rentals — and the options are often at odds with one another. Under Web 3.0, the same search would ideally call up a complete vacation package that was planned as meticulously as if it had been assembled by a human travel agent.

How such systems will be built, and how soon they will begin providing meaningful answers, is now a matter of vigorous debate both among academic researchers and commercial technologists. Some are focused on creating a vast new structure to supplant the existing Web; others are developing pragmatic tools that extract meaning from the existing Web.

But all agree that if such systems emerge, they will instantly become more commercially valuable than today’s search engines, which return thousands or even millions of documents but as a rule do not answer questions directly.

Underscoring the potential of mining human knowledge is an extraordinarily profitable example: the basic technology that made Google possible, known as “Page Rank,” systematically exploits human knowledge and decisions about what is significant to order search results. (It interprets a link from one page to another as a “vote,” but votes cast by pages considered popular are weighted more heavily.)

Today researchers are pushing further. Mr. Spivack’s company, Radar Networks, for example, is one of several working to exploit the content of social computing sites, which allow users to collaborate in gathering and adding their thoughts to a wide array of content, from travel to movies.

Radar’s technology is based on a next-generation database system that stores associations, such as one person’s relationship to another (colleague, friend, brother), rather than specific items like text or numbers.

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.”


2. For Start-Ups, Web Success on the Cheap -- by MIGUEL HELFT

SAN FRANCISCO — When Seth J. Sternberg and two colleagues started Meebo, a Web-based instant-messaging service, they didn’t go looking for venture capitalists. Using their credit cards, they financed the company themselves to the tune of $2,000 apiece. It was enough to cover their biggest expense — leasing a few computer servers at $120 a month each.

Within a month of its introduction in September 2005, Meebo was getting as many as 50,000 log-ins a day, and it needed more servers. It decided to take a modest $100,000 from three angel investors, wealthy individuals who typically contribute small amounts but do not get involved in management decisions.

“We had a bunch of V.C.’s talking to us about potentially putting more money in,” Mr. Sternberg said. “We said no. A lot of things happen when you raise a V.C. round, and they really slow you down.”

Eventually, Meebo did raise money from venture investors — about $3.5 million from Sequoia Capital. But that was after the company was well on its way to showing that its service was a hit; Meebo had about 200,000 daily log-ins.

In the last couple of years, hundreds of other Internet start-up companies in Silicon Valley and elsewhere have followed a similar trajectory. Unlike most companies formed during the first Internet boom, which were built on costly technology and marketing budgets, many of the current crop of Internet start-ups have gone from zero to 60 on a shoestring.

Some have gone without venture capital altogether or have raised far smaller sums than venture investors would have liked. Many were sold for millions before venture capitalists could even get in. That has been a challenge for venture capitalists, who have raised record amounts in recent years and need places to put that money to work.

“V.C.’s hate it; they want you to take big money,” said Jay Adelson, who is the chief executive of two start-ups, Digg and Revision3. Digg took some venture money, but far less than backers offered, and Revision3 has been running on about $850,000 raised from a group of angel investors.

Several venture firms are seeking to adapt. Just last week, Charles River Ventures announced it would offer loans of $250,000 to entrepreneurs as a way to gain access to promising start-ups. Other firms are also giving out small loans, albeit not as a part of any formal program.

For its part, Mohr Davidow Ventures has increased the number of “seed” investments — small sums given to embryonic companies — to about 10 a year from 5. And Union Square Ventures, which was formed in 2003, has made nearly half of its investments at $1 million or less, a departure from its initial plan to make first-round bets of $1 million to $3 million, according to its Web site.

“I think there is in the V.C. community a sense that the rules have changed or are changing,” said John Battelle, a journalist and entrepreneur, who is a host of a technology conference in San Francisco this week that will include a panel on the subject. “How does the V.C. who is set up for a model that requires millions, if not tens of millions, revamp for a different scale?”

And as large firms try to go small, they are encountering a new crop of competitors who are happy to bankroll start-ups on the cheap and are fueling the current Internet boom. They include a large pool of angel investors and a number of small venture funds whose specialty is to invest tens of thousands of dollars, or hundreds of thousands at most.

There is even a group called Y Combinator, whose rule of thumb for investing in start-ups is $6,000 per employee. One of its investments, Reddit, was acquired last week by Wired Digital, which is owned by Condé Nast Publications, for an undisclosed sum.

“I came to the conclusion that $500,000 was the new $5 million,” said Michael Maples Jr., an entrepreneur who created a $15 million venture fund aimed at investing in companies that required little capital. Mr. Maples sees himself not so much as a competitor to venture capitalists, but as someone who is filling the gap between angels, who may invest $250,000 or so in a start-up, and venture investors, whose typical early-stage bet is closer to $5 million.

Several forces are allowing companies to operate cheaply compared with the first Internet boom. They include the declining costs of hardware and bandwidth, the wide availability of open-source software, and the ability to generate revenue through online ads.

“It’s a great time to be an entrepreneur,” Joe Kraus, a veteran of the dot-com boom, wrote in a widely noted blog posting last year. Mr. Kraus said it took $3 million to get his first start-up, Excite.com, from idea to product, much of it spent on servers and software, which have since become much cheaper or even free. His new start-up, JotSpot, was started on just $100,000.

With the notable exception of YouTube, many recent acquisitions involved Internet start-ups that simply could not effectively use large amounts from venture capitalists or produce large returns, said Paul Kedrosky, a venture capitalist and blogger.

“The problem is that as a V.C., these companies don’t soak up enough capital,” Mr. Kedrosky said.

To succeed, a firm with a $250 million fund needs a handful of investments from $10 million to $15 million that can return payouts of $150 million or more, Mr. Kedrosky said. But even a twentyfold return on a $1 million investment will not do much for the success of a large fund, Mr. Kedrosky said.

For smaller funds, the economics are far different. For starters, those who manage them do not earn huge management fees. Instead, they are almost always among the largest investors in the fund, so they will earn a return if the investments pay off.

“I think large venture funds in this economic model have a challenge,” said Josh Kopelman, managing director of First Round Capital. Since starting First Round in 2004, Mr. Kopelman has made about 30 investments that range from $250,000 to $500,000. Mr. Kopelman, who made a fortune as a serial entrepreneur, is the largest investor in First Round’s $50 million fund.

Y Combinator is aiming at even smaller firms, and its approach is decidedly unorthodox. It chooses companies for financing in two batches of 8 to 12; one batch is selected in the winter from companies based in Silicon Valley, the other in the summer from those in Cambridge, Mass.

“When you change the amount of money, a lot of things change,” said Paul Graham, one of four partners in Y Combinator, who made millions when his company, Viaweb, was sold to Yahoo in 1998. “We have to mass-produce things. We can be more risky. We are like mice, and V.C.’s are more like elephants. They can only make a few deals, so each one has a whole amount of weight and worry attached to it.”

As for the target investment of $6,000 for each employee, an explanation on Y Combinator’s Web site makes it clear that Mr. Graham and his colleagues are not looking for computer science entrepreneurs who want to be pampered: “C.S. grad students at M.I.T. currently get $2,000/month to live on, so this represents three months’ living expenses. Though in fact most groups make it last longer.”

Established venture capitalists, however, say the new crop of capital-efficient start-ups represents an opportunity, not a problem.

“Companies have bootstrapped themselves in earlier eras,” said Gary Morgenthaler, a general partner at Morgenthaler Ventures. “There is no shortage of companies that need venture capital and company-building skills.”

Jon Feiber, a general partner at Mohr Davidow Ventures, said it was “incredibly good and healthy” that many Internet start-ups were able to do more with less.

“A small percentage of those companies will lend themselves to the model of a larger fund,” Mr. Feiber said. “If your goal is to generate something of huge value and scale, it is going to take more than $300,000 or $400,000.”

JotSpot, the company that Mr. Kraus started on $100,000, may fit that mold. The company eventually took in $4.5 million from a pair of venture capital firms, and last week it was acquired by Google for an undisclosed sum.

“I think it could be a great time to be a venture capitalist,” Mr. Kraus said in an interview. “Like in any competitive market, fear and hope are the two competing forces.” And for venture capitalists, the success of scrappy start-ups may simply be heightening the fear. “I think there is a lot of fear that people won’t get into the best deals,” Mr. Kraus said.