The New Google: Internet Giant Opens Up About Real-Time and Local Search, Cloud Computing, and Data Liberation

relevance to the user. “It’s very, very challenging to take short-form content and rank it against a New York Times article or a blog post,” and show the results “only when you want it.” Especially when that content didn’t exist just a few seconds ago, and nobody’s linking to it yet, so Google can’t use PageRank, its classic technology.

Instead, they “heavily rely on what we’ve learned in the past 10 years,” Menzel says. That includes things like how to parse out content that is likely to be irrelevant or spam, in a more general way. And coming up with “brand new signals”—he mentions “new language models” to understand which updates are relevant and which might be some oceanographic scientist’s data beacon, for example, as well as factoring in “how reputable the author is.”

As for the future, Menzel echoed what everyone seems to be saying about search these days: it’s early. “We’ve really just started in on this problem. We still have a long way to go,” he says. Within five years, he says, he hopes Google will make search “much more personal than it is today.” That means more than knowing that you like to follow soccer, for instance, and that you call it “football,” he says—it means understanding who you’re connected to, where you are, and organizing all the information around you.

“Search is still a very unsolved problem,” he says. “There are still a lot of things that are very hard to find on the Internet.”

Local search. This is all about Web search queries that include geographic information—such as “Hong Kong hotels” or “Seattle restaurants”—or are done from mobile devices to find nearby locations, products, or establishments.

Carter Maslan, director of product management for local search at Google, calls it “organizing the world’s information geographically,” or creating a fast, simple guide to the “geo-Web.” The main challenge, he says, is “mapping all these different ways of expressing a query onto a very large corpus of local information. And returning the right answer as quickly as possible.”

Maslan, another former Microsoftie, says Google draws on a vast number of search queries to analyze the way people search for information locally and the way things are referenced on the Web. The ultimate goal, he says, is that “ideally it becomes effortless to find and discover places around you.” Some familiar examples would be searching for directions on your mobile phone after landing at an airport, or being out and about in a neighborhood of New York City, looking for bars.

Which sounds like it should figure heavily into Google’s broader mobile strategy. “Your phone knows a lot,” Maslan says. “It knows where you are, it can determine which direction

Author: Gregory T. Huang

Greg is a veteran journalist who has covered a wide range of science, technology, and business. As former editor in chief, he overaw daily news, features, and events across Xconomy's national network. Before joining Xconomy, he was a features editor at New Scientist magazine, where he edited and wrote articles on physics, technology, and neuroscience. Previously he was senior writer at Technology Review, where he reported on emerging technologies, R&D, and advances in computing, robotics, and applied physics. His writing has also appeared in Wired, Nature, and The Atlantic Monthly’s website. He was named a New York Times professional fellow in 2003. Greg is the co-author of Guanxi (Simon & Schuster, 2006), about Microsoft in China and the global competition for talent and technology. Before becoming a journalist, he did research at MIT’s Artificial Intelligence Lab. He has published 20 papers in scientific journals and conferences and spoken on innovation at Adobe, Amazon, eBay, Google, HP, Microsoft, Yahoo, and other organizations. He has a Master’s and Ph.D. in electrical engineering and computer science from MIT, and a B.S. in electrical engineering from the University of Illinois, Urbana-Champaign.