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Complete Index of 16 years of PC AI magazine (in pdf format)
Volume 16, Issue 4
Theme: Knowledge Representation and Management

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PC AI Exclusive - Microsoft Research Tackles the Universal
Translator: A Breakthrough in Accurate and Automatic

Don Barker examines the history and technology of Microsofts internal project NLPWin, the results of two decades of research. By the end of 2002 it will accurately and automatically translate the entire Microsoft Product Support Services (PSS) Knowledge Base from English into Spanish, providing real-time responses to Spanish queries.

Back to Basics - Backward Chaining: An Expert System Fundamental
Dustin Huntington reviews the fundamentals of backward chaining, a key to building many types of interactive expert systems. This widely misunderstood approach to rule-based development can take complex problems and breaks them into small, easily defined sections that the system automatically uses when needed.
The Fuzzy Electric Bulb: An Introduction to Fuzzy Logic with Sample Implementation
M. Alroy Mascrenghe presents the basic concepts of fuzzy logic, where it is used, and how to apply it by walking through a very simple yet realistic example.
It is Time for Utilitarian, Cost Effective Service Robots: The Enabling Confluence of Technologies
R. Martin Spencer explores past and present confluences of low cost hardware technologies that enable truly utilitarian personal robots for multiple marketplaces. Learn how a constellation of AI applications can be networked to a self-navigating Personal Computer Robot (PCR).
Have You Considered Smalltalk?: Smalltalk Fundaments
Jeffrey D. Panici illustrates how Java and C++ are not the only options for your object-oriented endeavors. This article introduces a serious contender that has been around for a while and yet is often overlooked.
Knowledge Based Systems in Adaptive Training: Tailoring Training to Individual Needs
Barry Brosch
demonstrates the use of a knowledge based system to construct assessment driven systems with self-customizing tutorials.

The Art of Intelligence: A Theory of Intelligent Thought
Paul F. Troncone
describes a theory that views intelligence, not as the analysis of facts and data, but as a series of changing relationships based on which he defines a scale with which to measure intelligence.


AI and the Net
Terry Hengl Chess matches man and machine, another AI directory, AI research and information at IBM

Buyers Guide
Expert Systems and Development Systems, Intelligent Tutoring, Machine Learning, Knowledge Management, Logic and Reasoning Systems


Terry Hengl

Product Update
Business Forecasting and Rules, Data Mining, Decision Support, Expert System Development Systems, Intelligent Tools, Internet and Web, Knowledge Based Systems, Languages, Modeling
& Simulation, Neural Networks, Object Oriented Development Languages, Conferences and Training


Where is AI Today?

        While glancing through the Fall 2002 Comdex Program (November 18-22), I could not help noticing how unexciting and predictable the show topics were. With the sliding economy and companies financially strapped, it is not surprising to see some focus on corporate business fundamentals such as IT Management, Web Services, Storage, Security, eMobility, and technical arenas such as Java, .Net, Windows, and so on. However, with the possible exception of Business Intelligence, there is little emphasis on intelligent technologies. Unfortunately, this is a common occurrence during tight economies - corporations focus more on survival and less on gaining market share or using technology to radically improve processes. At the very time that companies should be leveraging technology to improve their bottom line they ignore the opportunity. Smart companies realize this and use intelligent technologies during the downturns to improve their tools, processes, and knowledge - enabling them to gain market share as the economy recovers - an important corporate advantage. Successful companies do not advertise this fact - they do not want their competition using this against them during the next downturn.

        Business Rules, one intelligent technology that is very successful, is really just a vertical application of expert systems for knowledge management. Embraced as a crucial approach to strategic planning by major corporations and vendors such as IBM, American Express, Charles Schwabb, as well as government organizations, Business Rules have become mainstream. The primary premise of many current business rule systems is that the user of the critical business knowledge, the domain experts, maintains the knowledge. In traditional systems, the programmers embed the knowledge in the programs so only programmers can make changes. These rule based concepts of knowledge management are right out of expert systems 101.

        There are numerous opportunities for intelligent technologies to improve a corporation's bottom line during these economic down-turns. Expert system technology is a powerful tool, when applied properly. It can capture the fundamental expertise of those leaving a company or changing assignments due to limited corporate resources. For example, capturing an experienced HR person's knowledge of the corporate HR rules and guidelines frees that person up for other assignments. It can also provide guidance to new HR candidates, when the economy does turn around. The captured knowledge in turn can man the first level of support at customer support or interface centers. Other possible uses of this technology is supplying benefit information to employees, product information to prospective clients, or product support - many questions can be answered at this first level of support, whether using web or voice as the interface protocol. In this issue, we examine an expert system used in intelligent instruction.

        This issue also has a PC AI exclusive. Don Barker, a long-time writer and columnist for PC AI, has spent the past two years researching the Microsoft Research Division (MRD), with Microsoft's support and encouragement, in preparation for a number of articles and possible book on the history and accomplishments of MRD. This opportunity is afforded very few writers and we are excited to have one of the first articles resulting from Don's research. Microsoft has been collecting some of the best AI researchers and developers in a variety of AI related fields and many are now employed in the MRD. In addition, the timing could not be better as Microsoft is about to deploy this machine translation system, the accumulation of two decades of research, later this year.

Terry Hengl

Volume 15-----------------------> Issue 1 (Jan/Feb 2001)   Volume 15 Index (2001)
  Issue 2 (Mar/Apr 2001)   Volume 14 Index (2000)
Issue 3 (May/Jun 2001)   Volume 13 Index (1999)
Issue 4 (Jul/Aug 2001)   Volume 12 Index (1998)
Issue 5 (Sep/Oct 2001)   Volume 11 Index (1997)
Issue 6 (Nov/Dec 2001)   Volume 10 Index (1996)
      Volume 9 Index (1995)
      Volume 8 Index (1994)

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