This article is derived from the 2005 Innovative Applications of Artificial Intelligence conference invited talk "AI Meets Web 2.0: Building the Web of Tomorrow, Today" presented by Jay M. Tenenbaum in Pittsburgh, Pennsylvania. I invited Marry to deliver that talk at IAAI-05 because he is a true AI and web visionary. It is common in times of grade inflation and hyperbole that speakers and authors are introduced as "visionaries." Jay M. Tenenbaum (or Marty, as he is known) actually is a world-renowned Internet commerce pioneer and visionary. Mary envisioned the commercial and industrial use of the Internet more than a decade before it became a reality, at a time when only academics, industrial R&D groups, and government labs had access to it. At the time, Marty's e-commerce vision evoked all kinds of resistance and objections about why it couldn't or shouldn't be done.
In 1991, Marry founded and became the chief executive officer of Enterprise Integration Technologies, the first company to conduct a commercial Internet transaction (1992), a secure web transaction (1993), and an Internet auction (1993). In 1994, Marty formed the CommerceNet industry association and jump-started the Internet marketplace by convincing 50 leading corporations to get online. In 1997, he cofounded Veo Systems, which pioneered the use of XML documents for automating business-to-business transactions. In 1999, Commerce One acquired Veo Systems, and Marty ultimately served as its chief scientist. Marry now splits his time between Internet startups Efficient Finance, Medstory, and Patients Like Me, and the nonprofit CommerceNet.
This article points to the technical opportunity to meet Allen Newell's criteria for intelligent systems by incrementally assembling complex web services applications out of component web services, tagged data, and inference techniques. It also articulates an exciting set of business opportunities to deliver on the economic promise of e-commerce and AL
- -Neil Jacobstein, Chair, IAAI-05
* Imagine an Internet-scale knowledge system where people and intelligent agents can collaborate on solving complex problems in business, engineering, science, medicine, and other endeavors. Its resources include semantically tagged websites, wikis, and blogs, as well as social networks, vertical search engines, and a vast array of web services from business processes to AI planners and domain models. Research prototypes of decentralized knowledge systems have been demonstrated for years, but now, thanks to the web and Moore's law, they appear ready for prime time. This article introduces the architectural concepts for incrementally growing an Internet-scale knowledge system and illustrates them with scenarios drawn from e-commerce, e-science, and e-life.
In this article, I want to share a vision of how to build or, more precisely, grow Internetscale knowledge systems. Such Systems enable large numbers of human and computer agents to collaborate on solving complex problems in engineering, science, and business or simply managing the complexities of life (say planning a trip or an event). It's a vision that's been evolving over 20 years since my days as an AI researcher and, more recently, as an Internet entrepreneur. Thanks to the explosive growth of the web, it's a vision whose time has come. I also have a larger goal: to bridge the AI and web communities, which have so much to give to and learn from each other.
Twenty-five years ago, at the birth of AAAI, Allan Newell articulated a set of criteria that a system had to exhibit to be considered intelligent (see table 1). Newell was very explicit that an intelligent system had to exhibit all of these criteria. This requirement reflected the then prevailing view that intelligent systems were monolithic and were developed centrally by an individual or small group.
Table 1. Newell's Criteria for Intelligent Systems.
* Exhibit adaptive goal-oriented behavior
* Learn from experience
* Use vast amounts of knowledge
* Exhibit self-awareness
* Interact with humans using language an speech
* Tolerate error and ambiguity in communication
* Respond in real time
The web has shown us a different path to intelligence--millions of simple knowledge services, developed collaboratively in a decentralized way by many individuals and groups, all building on each other, and demonstrating a collective form of intelligence. …