The Future of Search

The head of Google Research talks about his group's projects.

Peter Norvig, Google's director of research, is an expert ace at building machines that answer tough questions. An authority in programming languages and artificial intelligence, he has written an oft-cited book on AI (Artificial Intelligence: A Modern Approach), has taught at the University of California, Berkeley, and the University of Southern California, and was the head of computational sciences at NASA. In 2001, Norvig came to Google to be the director of search quality. Four years later, he became Google's director of research, overseeing about 100 researchers who investigate topics that range from networking to machine translation. Technology Review spoke with Norvig to get a hint of what we can expect from search technology in the years to come.

Search leader: Peter Norvig, director of Google Research. Credit: Google

Technology Review: What does Google Research do?

Peter Norvig: The core of what we do is still search and advertising. A lot of researchers are working on that. They're working to give better-quality search results and to match ads better. Another area of research is gathering more sources of information, such as text in books, still images, video, and now audio in terms of speech recognition. I think another focus is to understand how people interact with Google and interact with each other on the Web, in general. How do people operate in these social networks? Understanding that question can help us serve them better.

TR: Which research has the most people and funding?

PN: The two biggest projects are machine translation and the speech project. Translation and speech went all the way from one or two people working on them to, now, live systems.

TR: Like the Google Labs project called GOOG-411 [a free service that lets people search for local businesses by voice, over the phone]. Tell me more about it.

PN: I think it's the only major [phone-based business-search] service of its kind that has no human fallback. It's 100 percent automated, and there seems to be a good response to it. In general, it looks like things are moving more toward the mobile market, and we thought it was important to deal with the market where you might not have access to a keyboard or might not want to type in search queries.

TR: And speech recognition can also be important for video search, isn't it? Blinkx and Everyzing are two examples of startups that are using the technology to search inside video. Is Google working on something similar?

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PN: Right now, people aren't searching for video much. If they are, they have a very specific thing in mind like "Coke" and "Mentos." People don't search for things like "Show me the speech where so-and-so talks about this aspect of Middle East history." But all of that information is there, and with speech recognition, we can access it.

We wanted speech technology that could serve as an interface for phones and also index audio text. After looking at the existing technology, we decided to build our own. We thought that, having the data and computational resources that we do, we could help advance the field. Currently, we are up to state-of-the-art with what we built on our own, and we have the computational infrastructure to improve further. As we get more data from more interaction with users and from uploaded videos, our systems will improve because the data trains the algorithms over time.