Tom Dunlap
SemanticWeb.com Contributor

Of all the semantic web projects and technologies, perhaps none is bigger than CALO, a so far little-known advanced intelligent assistant system with some big-time backing.

CALO stands for Cognitive Assistant that Learns and Organizes, and it emerged from an ambitious program of artificial intelligence (AI) research. One expert called CALO the “largest AI project in history.”

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It’s very important to DARPA, the Defense Advanced Research Projects Agency, which is investing in it heavily. About 25 universities and companies are working on CALO, including MIT and USC; the companies include PARC and Radar Networks.

CALO was demonstrated in detail Thursday night in San Francisco at a meeting of the SDForum, an eclectic group of Bay Area entrepreneurs, programmers, and those interested in the semantic web.

CALO — which semantic web pioneer Tom Gruber calls one of the most “pure play examples” of an intelligent assistant — learns about your documents, email, people, schedules, and meetings, and learns even more as you use it. It helps you organize your information world, prepare for meetings, create presentations, and find information in the context of your work.

Adam Cheyer demonstrated some of CALO’s powers Thursday night. Cheyer is a scientist with an impressive rap sheet, the kind developed after many years in Silicon Valley. He is a program director in SRI’s Artificial Intelligence Center, where he serves as chief architect of the CALO/PAL project. Cheyer is also senior scientist and co-director of the Computer Human Interaction Center (CHIC) at SRI International.

Cheyer said that CALO is being developed in an office format, but it’s being transitioned to the military for various projects like “command post of the future” and “PlatoonLeader.”

CALO has three main high-level functions: information management, meeting understanding, and task management execution.

Cheyer said that other products have done meeting understanding, but CALO is different and more robust because, for example, it knows things like who is in the meeting, what the people do, and what documents are important to this meeting. If CALO notices that a certain manager — let’s say Manager Adam — isn’t in a meeting, it starts to ask questions about Adam. Maybe he isn’t really the project lead? It then does “machine learning” based on those questions.

To see how CALO is doing at a particular company, CALO’s creators have set up a very detailed way to test the system.

Here’s one example: Let’s say Executive Smith had a CALO program running for two weeks, and that program was supposed to be learning all about Smith and all his obligations, professional contacts, presentations, emails, calendar appointments, etc. during those two weeks.

CALO would then know all about the meetings Smith attends, and, if Smith can’t make a meeting, CALO would automatically suggest who should attend the meeting in Smith’s place, and even email the replacement.

The CALO test throws all kinds of detailed questions at the intelligent assistant, and Cheyer expects it to “learn in the wild,” and get a certain number of answers right and achieve a certain score — and to constantly improve.

CALO is still being developed and being kept partially under wraps. Cheyer apologized for the dull, government-issued PowerPoint slides he was using during his presentation, because he is “only allowed to show publicly approved slides.”

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The aforementioned Tom Gruber — an innovator in technologies that augment human intelligence, individually and collectively — led off Thursday night’s SDForum meeting with the theme “intelligence at the interface.” What this meeting is about, Gruber said, is “the horizon, about something that will change the way we use the Internet.”

What does intelligence at the interface mean, and what can it do for you? Gruber wrote that:

“The interfaces we use to interact with the world’s information are getting smarter. Web portals gave us someone else’s idea of the content we should see. Then came search engines, which let us tell the system what we want, one query at a time.

We are about to see the next wave — intelligence at the interface — in which the system knows about us, our information, and our physical environment. With knowledge about our context, an intelligent system can make recommendations and act on our behalf.”

Gruber said the goals of intelligence at the interface are things like: tell me what I need to know; understand what I mean; help me solve my problems; help me meet my needs; help me keep in touch; help me discover; work for me.

In addition to the CALO demo, three other technologies were demoed Thursday:

1. Yahoo Research Berkeley showed off the dazzling ZoneTag and Zurfer, mobile-phone photo-driven applications that use your social, spatial, and temporal context to support and enhance key user tasks on the mobile device. They intelligently help you capture, upload, tag, view and search for photos on your mobile device, minimizing requirements on explicit input and user attention.

2. PARC demonstrated a mobile leisure guide, codenamed Magitti, which recommends places to visit in an urban environment. It pays attention to your messages, your time, location, past behavior, and preferences and it also infers your current and future activity type to better target its recommendations. For instance, it suggests where you should go to dinner when you’re out on the town, or it might suggest what your next activity should be.

3. Radar Networks demonstrated Twine, a new online service based on their semantic web platform (which SemanticWeb.com has written about, Radar’s Twine Ties the Semantic Web Together). Twine helps people organize, find, and share their information more intelligently. It knows about the semantic content of information of all sorts, from web content to email.

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