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Search For Tomorrow

Not Google. When the company debuted in September 1998, it looked like a throwback. This wasn't a portal. The home page showed mostly white space, anchored by a little rectangle, a box, perfectly blank. Fill in blank and get results. This was plain ol' boring Search, without news headlines, plane tickets, e-mail or any other bells and whistles.

But what results! Google has farms of computers working in parallel. You can put in a couple of words and -- gzzzzt! -- get 600,000-plus results within some preposterously brief amount of time. (Google brags about it: "Search took 0.17 seconds." Showoffs!)


When Google first appeared, in 1998, it seemed like a throwback. Rather than a jazzy "portal," it was just a plain ol' boring search engine. (Google)

_____Related Coverage_____
Online Search Engines Help Lift Cover of Privacy (The Washington Post, Feb 9, 2004)

Google, the creation of Stanford graduate students Sergey Brin and Larry Page, is like many other search engines in its basic operation. It has powerful software programs that automatically "crawl" the Web, clicking on every possible link, scouting the terrain. What has made Google special is that, in assessing the quality of sites, it takes note of how many other pages link to any given page. This is an old idea from academia, called citation analysis. If many Web sites link to a particular page, the page rises in Google's vaunted "page rank" and is more likely to be on the first page of the search results.

"You're getting the advantage of the group mind," says Paul Saffo, a research director at the Institute for the Future.

This is a key concept: As the Web has grown, it has developed a kind of embedded wisdom. Obviously the Web isn't a conscious entity, but neither is it a completely random pile of stuff. The way one part links to another reflects the preferences of Web users -- and Google tapped into that. Google, in detecting patterns on the Web, harvested meaning from all that madness.

This points the way to one of the next big leaps for search engines: finding meaning in the way a single person searches the Web. In other words, the search engines will study the user's queries and Web habits and, over time, personalize all future searches. Right now, Google and the other search engines don't really know their users.

For example, Saffo isn't really interested in the stuff that most people look for when they do a Web search. He's one of the premier futurists of Silicon Valley and fondly recalls the days, back in the 1980s and early 1990s, the pre-Web era, when the Internet was the reserve of the technological elite who posted their brilliant thoughts on electronic bulletin boards. Now, everyone from about third grade up has an e-mail address and loiters around the Web as though it's the corner 7-Eleven. The results of a Web search reflect the tastes of a broad swath of ordinary Americans who in some cases are still wearing short pants.

"The more people get on the Web, the more the Web becomes the vaster wasteland that is the successor to the vast wasteland of television. I don't care what the majority of people are looking at, because the majority of people are really boring," Saffo says.

He needs a better search engine. He needs one that knows that he's a big-brain tech guru and not an eighth-grader with a paper due.

"The field is called user modeling," says Dan Gruhl of IBM. "It's all about computers watching interactions with people to try to understand their interests and something about them."

Imagine a version of Google that's got a bit of TiVo in it: It doesn't require you to pose a query. It already knows! It's one step ahead of you. It has learned your habits and thought processes and interests. It's your secretary, your colleague, your counselor, your own graduate student doing research for which you'll get all the credit.

To put it in computer terminology, it is your intelligent agent.


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