The Grill: Google's Alfred Spector on the hot seat

Computerworld - What kinds of things are coming out of Google research? Google Search by Voice is an example. Wouldn't it be nice to tell a handheld device what you want to know? It's an interesting problem in that one needs to understand spoken voice, correlate that with the most likely search queries, and then show the search result -- doing all this with an intuitive, speedy user interface. This work comes out of our basic research efforts in speech recognition. The Google Mobile App with voice search has been on the iPhone for a few months, and we just released Google Search by Voice on Android [Google's open-source software for mobile devices].

What longer-range projects are you working on? With all the data on the Web, shouldn't we be able to take that information and create a

Dossier

Name: Alfred Spector

Title: Vice president of research and special initiatives

Organization: Google Inc.

Location: Mountain View, Calif.

Favorite non-Google technology: His grand piano

Technology pet peeve: "Having to be an active administrator for eight computers at home."

In high school, he was: "Editor of the yearbook and planning to be a broadcast journalist."

Favorite nonwork pastime: "My kids."

Philosophy in a nutshell: "I try to balance across two dimensions -- balancing the needs of my family/friends/society, productive enterprise, and self; and focusing on achievement yet remembering to mark the passing moments."

Role model: "My father."

Recent good read: The Brothers Karamazov

Favorite movie: Manhattan

database of concepts -- or entities -- and the relationships between them? For example, consider the "is a" relationship. A dog is a pet; a son is a boy, for example. But AI often thought these relationships had to be taught to a system by experts. But the question we have is, can we learn all these things from a huge amount of interaction with a very large corpus of information? If so, we could codify and structure significant aspects of knowledge. The system could automatically glean many kinds of information. It's a very long-range effort.

What would you do with that database of relationships? Let's imagine our search software is responding to a query on pets, but we find articles on dogs and cats, but without the word pets. This database of relationships would let Google know that the article is probably about pets because there are multiple instances of a subcategory of "pet." The database would enable much better search and better language translation because there'd be a better understanding of the meaning of the words.

We believe it may be possible to build up these huge sets of concepts and the relationships between them. You could gain two benefits: more-focused results and probably also results that wouldn't otherwise be found.