The project might seem broad in its goals, but the researchers believe that ultimately, the system will benefit from multiple technologies working together. Consider the meeting-transcription function, says William Mark, vice president of the information and computer-science division at SRI. Even the best speech-recognition systems would have trouble producing an accurate transcript of a meeting unassisted, he says, but “in our context, because of information management, CALO has deep and rich knowledge about who are the people in the room, and what are the documents and phrases and slang used in context.”
Since CALO has many learning systems, one challenge is integrating them so that CALO has a consistent structure for information that it can use to make decisions based on the noisy, uncertain data that it extracts from its various interactions. Domingos and others have been working on a probability consistency engine, which unifies two traditional approaches to artificial intelligence: logic and probability.
Alan Qi, an assistant professor of computer science at Purdue University, who is not involved with CALO, says that the unification of logic and probability is an important endeavor for the field of artificial intelligence. Combining these two approaches, Qi says, is far better than using either alone. Probabilistic approaches can handle noise and uncertainty well, while a logical structure is best for handling meaning.
Although CALO’s approach is very far-reaching, SRI has made a version, called CALO Express, that boils down some of the features of CALO that are almost ready for deployment. CALO Express is a lightweight version of the real deal that integrates with Microsoft products such as Outlook and PowerPoint. Cheyer says that it includes parts of the three main features of information management, meeting assistance, and task management. He says that CALO Express is now being evaluated for use at DARPA. While it’s uncertain whether CALO Express will become a commercial product available outside of the military, there is still hope that the average person may get access to technologies of this type. The research has already produced a few products, such as Smart Desktop, which is an information-management system that spun off of the task-tracer project done by Oregon State University as part of CALO. Radar Networks, makers of the Semantic Web product Twine, has also worked on some of CALO’s semantic underpinnings. (See “The Semantic Web Goes Mainstream.”)