Grannan concedes that Siri’s deep artificial intelligence technology, spun out of research at SRI International in Menlo Park, CA, surpasses the artificial intelligence that Vlingo now uses. However, he still sees a big opportunity for Vlingo to make its mark. Instead of the “inch-wide, mile-deep” approach that he believes characterizes Siri, Grannan hopes that Vlingo can offer artificial intelligence that’s “mile wide and inch deep.” In other words, he says, Siri is adept at a very narrow set of subjects, such as helping people make restaurant reservations, but he wants Vlingo to handle a broader range of topics.
The basic version of Vlingo is free; the Cambridge, MA-based company gets revenue by selling targeted advertising and by charging users for the ability to carry out more sophisticated functions, such as voice recognition for sending text messages. Its application is available for Android, iPhone, BlackBerry, Nokia, and Windows Mobile.
The vision of the personal intelligence agent that apps such as Vlingo and Siri represent has been a major research goal for decades.
Voice recognition and natural language processing have made huge strides in the past decade, enabling computers to better understand what people are saying. But one of the main problems in bringing the technology to smart phones has been that users need to see a device react to voice input within a few seconds in order to feel that an application is working, says Mazin Gilbert, executive director of technical research at AT&T Labs and an expert in these technologies. Smart phones don’t have the processing power needed for sophisticated voice recognition and analysis; any device using such an app is just absorbing audio and sending it over the network. Until very recently, Gilbert says, slow network speeds caused a bottleneck that made apps like SuperDialer impractical.
Today’s voice-recognition butler apps also benefit from access to an abundance of data online and application programming interfaces that let services connect to each other. Gilbert believes, however, that software could still get much more sophisticated about interpreting users’ intentions. He’s excited about the surge of smart phone applications, because they promise to provide much more information about how users want to interact with personal assistants. That could fuel further advances in machine learning and natural language processing, making future applications even smarter and easier to use.