When you type in "GM" into Google, we know it's "General Motors." If you type in "GM foods" we answer with "genetically modified foods." Because we're processing so much data, we have a lot of context around things like acronyms. Suddenly, the search engine seems smart like it achieved that semantic understanding, but it hasn't really. It has to do with brute force. That said, I think the best algorithm for search is a mix of both brute-force computation and sheer comprehensiveness and also the qualitative human component.

IDGNS: Where is the universal search effort at Google?

Mayer: It is early stage and we're working on more radical things now. The team launched [universal search] in May ... Books, images, news, video, and local information have now been blended in [with general Web search]. The team is now devoting its time and energy to three different pieces. They're working really hard to internationalize universal and bring it to all of our different countries and languages because it's English-only and largely in the U.S. They're working on bringing in [other vertical engines] like blog search, patents, scholar. And they're also looking at how to do more radical things in terms of overall ranking and relevance and user presentation, the user interface piece.

The reason why universal search was such a big change for us was that there were three [key] pieces [to adapt]. We had to change the entire infrastructure to make the thing cost effective. Then there's the ranking piece: Now that you have all these results, how do you order them? And the final piece was the user interface.

Now the infrastructure is in place and the engineers can finally get to have fun thinking about what they can do in terms of relevance, ranking, and user interface. With that third [user interface] piece, we're doing a lot of experimentation building a bunch of interesting prototypes of how universal search could play out this year or two or three years out.

IDGNS: Is the ultimate goal to fold all these vertical tabs of news, image, video, book search, and so on into the general Web search query box?

Mayer: We want people to think of the search box as one query box. That said, we do acknowledge that there are times when you know you want an image or a news story, so obviously we'll still have links to those independent indices. But you shouldn't have to use those if you're not an expert and you don't know what's there [in all our specialty search engines] ... we'd like all of those [secondary indices] to be integrated into the main [Web] search engine.

IDGNS: What's Google's take on all the so-called "deep Web" content search engines can't get to for a variety of technical reasons?

Mayer: The issue on "deep Web" content is that it's usually in databases and [Web] crawling isn't a great way of getting at a database. ... So we've been doing things like Google Base. Most databases allow people to do an XML feed off of them so you can do an XML output of your database and you can upload that database to Google and Google Base.

IDGNS: Are you making progress with that approach?

Mayer: Yes, literally hundreds of millions of items have been uploaded into Google Base. So we're making progress indexing that data, but we're not doing a good enough job surfacing that data in the search results. So we have it, and if you go to Google Base, you can find it but it's hard to figure out, from the universal search aspect, when it should be blended into the main search results.