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 Web sites, 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. Architectural concepts for incrementally growing an Internet-scale knowledge system are introduced, with descriptions of early commercial deployments in manufacturing and healthcare.

I want to share a vision of how to build, or more precisely, grow Internet-scale 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.

25 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 developed centrally by an individual or small group.

Download pdf AI Meets Web 2.0: Building the Web of Tomorrow, Today