If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
AI applications have been deployed and used for industrial, government, and consumer purposes for many years. Over the years, the breadth of applications has expanded many times over and AI systems have become more commonplace. Indeed, AI has recently become a focal point in the industrial and consumer consciousness. This article focuses on changes in the world of computing over the last three decades that made building AI applications more feasible.
NewsFinder automates the steps involved in finding, selecting, categorizing, and publishing news stories that meet relevance criteria for the Artificial Intelligence community. The software combines a broad search of online news sources with topic-specific trained models and heuristics. Since August 2010, the program has been used to operate the AI in the News service that is part of the AAAI AITopics website.
The AAAI video archive is a central source of information about videotapes and films with information about AI that are stored digitally on other sites or physically in institutional archives. For each video, the archive includes a brief description of the contents and personae, one or more representative short clips for classroom or individual use, and the location of the archival copy (for example, at a university library).
Smith, Reid G., Farquhar, Adam
Enabling organizations to capture, share, and apply the collective experience and know-how of their people is seen as fundamental to competing in the knowledge economy. As a result, there has been a wave of enthusiasm and activity centered on knowledge management. To make progress in this area, issues of technology, process, people, and content must be addressed. In this article, we develop a road map for knowledge management. It begins with an assessment of the current state of the practice, using examples drawn from our experience at Schlumberger. It then sketches the possible evolution of technology and practice over a 10-year period. Along the way, we highlight ways in which AI technology, present and future, can be applied in knowledge management systems.
Smith, Reid G.
The fifth Distributed Artificial Intelligence Workshop was held at the Schlumberger-Doll Research Laboratory from October 14 to 17, 1984. It was attended by 20 participants from academic and industrial institutions. It included brief research reports from individual groups along with general discussion of questions of common interest. This report summarizes the general discussion and contains summaries of group presentations that have been contributed by individual speakers.
Smith, Reid G.
We use our experience with the Dipmeter Advisor system for well-log interpretation as a case study to examine the development of commercial expert system. We argue that the tools and ideas of rapid prototyping and successive refinement accelerate the development process. We note that different types of people are required at different stages of expert system development: Those who are primarily knowledgeable in the domain, but who can use the framework to expand the domain knowledge; and those who can actually design and build expert systems. Finally, we discuss the problem of technology transfer and compare our experience with some of the traditional wisdom of expert system development.
Smith, Reid G., Young, Robert L.
"The Dipmeter Advisor system attempts to emulate human expert performance in an important and specialized oil well-log interpretation task. The system is currently being used in a small number of Schlumberger Field Log Interpretation Centers as an aid to human dipmeter interpreters. In this paper, we describe the problem just enough to establish the vocabulary for discussing the program and the characteristics of the domain. We then present the internal structure of the program and attempt to put it in perspective with respect to first-generation expert systems. We discuss ways in which characteristics of the task domain impose constraints on the design or signal interpretation programs, and attempt to extract knowledge useful to future expert system developers."Proceeding ACM '84 Proceedings of the 1984 annual conference of the ACM on The fifth generation challenge Pages 15 - 23 ACM New York, NY, USA ©1984