Alan Turing's decades-old question still influences artificial intelligence because of the simple test he proposed in his article in Mind. In this article, AI Magazine collects presentations about the first round of the classic Turing Test of machine intelligence, held November 8, 1991 at The Computer Museum, Boston. Robert Epstein, Director Emeritus, Cambridge Center for Behavioral Studies, and an adjunct professor of psychology, Boston University, University of Massachusetts (Amherst), and University of California (San Diego) summarizes some of the difficult issues during the planning of this first real-time competition, and describes the event. Presented in tandem with Dr. Epstein's article is the actual transcript of session that won the Loebner Prize Competition--Joseph Weintraub's computer program PC Therapist. In 1985 an old friend, Hugh Loebner, told me The intricacies of setting up a real Turing Test excitedly that the Turing Test should be made that would ultimately yield a legitimate into an annual contest. We were ambling winner were enormous. Small points were down a Manhattan street on our way to occasionally debated for months without dinner, as I recall. Hugh was always full of clear resolution. Turing, proposed a variation on a simple Four years later, while serving as the director parlor game as a means for identifying a of the Cambridge Center for Behavioral Studies, machine that can think: A human judge an advanced studies institute in Massachusetts, interacts with two computer terminals, one I established the Loebner Prize controlled by a computer and the other by a Competition, the first serious effort to locate person, but the judge doesn't know which is a machine that can pass the Turing Test. If, after a prolonged conversation at Hugh had come through with a pledge of each terminal, the judge can't tell the difference, $100,000 for the prize money, along with we'd have to say, asserted Turing, that some additional funds from his company, in some sense the computer is thinking. Crown Industries, to help with expenses. The Computers barely existed in Turing's day, but, quest for the thinking computer had begun. I'll then describe that After much debate, the Loebner Prize Committee first event, which took place on November 8, ultimately rejected Turing's simple 1991, at The Computer Museum in Boston two-terminal design in favor of one that is and offer a summary of some of the data generated more discriminating and less problematic. Finally, I'll speculate The two-terminal design is troublesome for about the future of the competition--now an several reasons, among them: The design presumes annual event, as Hugh envisioned--and that the hidden human--the human about its significance to the AI community.

On Monday, 15 July 1991, prior to the Ninth National Conference on Artificial Intelligence (AAAI-91) in Anaheim, California, over 50 scientists and engineers attended the AAAI-91 Workshop on Intelligent Multimedia Interfaces. The purpose of the workshop was threefold: (1) bring together researchers and practitioners to report on current advances in intelligent multimedia interface systems and their underlying theories, (2) foster scientific interchange among these individuals, and (3) evaluate current efforts and make recommendations for future investigations.

An effective to develop an abstract UI model which solution to this problem must have three encompasses the essence of those systems.

My Ph.D. thesis (Ward 1992, 1991)1 addressed the task of generating natural language utterances. It was motivated by two difficulties in scaling up existing generators. Current generators only accept input that are relatively poor in information, such as feature structures or lists of propositions; they are unable to deal with input rich in information, as one might expect from, for example, an expert system with a complete model of its domain or a natural language understander with good inference ability. Current generators also have a very restricted knowledge of language -- indeed, they succeed largely because they have few syntactic or lexical options available (McDonald 1987) -- and they are unable to cope with more knowledge because they deal with interactions among the various possible choices only as special cases. To address these and other issues, I built a system called FIG (flexible incremental generator). FIG is based on a single associative network that encodes lexical knowledge, syntactic knowledge, and world knowledge. Computation is done by spreading activation across the network, supplemented with a small amount of symbolic processing. Thus, FIG is a spreading activation or structured connectionist system (Feldman et al. 1988).

Integrated Language and Vision Systems, Scholarship Travel Program If you are interested in assisting AAAI at the national conference, New Mexico State University, Continued please contact AAAI at volunteer Dec. 1991 AAAI announces the continuation of @aaai.org. All inquiries should 1991 IFIP/KR Workshop its scholarship travel program for students include your name, address, telephone, Eleventh International Workshop on who want to attend the National advisor's name, and email Distributed Artificial Intelligence, Conference on Artificial Intelligence address. All requests to volunteer at Glen Arbor, Michigan, February 1992 in San Jose, California, 12-17 July AAAI-92 must be received by the 1992. First International Conference on and (2) are members of April 3 AAAI-92 Scholarship AI Planning Systems, University of AAAI. In addition, repeat scholarship Application Deadline Maryland, June 1992 applicants must have fulfilled the April 29 Al Magazine Summer Issue The Third International Conference volunteer and reporting requirements Calendar Deadline on Principles of Knowledge Representation for previous awards.

Feedback connections are required so that the teacher signal on the output neurons can modify weights during supervised learning. Relaxation methods are needed for learning static patterns with full-time feedback connections. Feedback network learning techniques have not achieved wide popularity because of the still greater computational efficiency of back-propagation. We show by simulation that relaxation networks of the kind we are implementing in VLSI are capable of learning large problems just like back-propagation networks. A microchip incorporates deterministic mean-field theory learning as well as stochastic Boltzmann learning. A multiple-chip electronic system implementing these networks will make high-speed parallel learning in them feasible in the future.

Feedback connections are required so that the teacher signal on the output neurons can modify weights during supervised learning. Relaxation methods are needed for learning static patterns with full-time feedback connections. Feedback network learning techniques have not achieved wide popularity because of the still greater computational efficiency of back-propagation. We show by simulation that relaxation networks of the kind we are implementing in VLSI are capable of learning large problems just like back-propagation networks. A microchip incorporates deterministic mean-field theory learning as well as stochastic Boltzmann learning. A multiple-chip electronic system implementing these networks will make high-speed parallel learning in them feasible in the future.

Feedback connections are required so that the teacher signal on the output neurons can modify weights during supervised learning. Relaxation methods are needed for learning static patterns with full-time feedback connections. Feedback network learning techniques have not achieved wide popularity because of the still greater computational efficiency of back-propagation. We show by simulation that relaxation networks of the kind we are implementing in VLSI are capable of learning large problems just like back-propagation networks. A microchip incorporates deterministic mean-field theory learning as well as stochastic Boltzmann learning. A multiple-chip electronic system implementing these networks will make high-speed parallel learning in them feasible in the future.

I survey four viewpoints about what AI is. I describe a program exhibiting AI as one that can change as a result of interactions with the user. Such a program would have to process hundreds or thousands of examples as opposed to a handful. Because AI is a machine's attempt to explain the behavior of the (human) system it is trying to model, the ability of a program design to scale up is critical. Researchers need to face the complexities of scaling up to programs that actually serve a purpose. The move from toy domains into concrete ones has three big consequences for the development of AI. First, it will force software designers to face the idiosyncrasies of its users. Second, it will act as an important reality check between the language of the machine, the software, and the user. Third, the scaled-up programs will become templates for future work. For a variety of reasons, some of which I discuss one of the following four things: (1) AI means in this article, the newly formed Institute magic bullets, (2) AI means inference engines, for the Learning Sciences has been concentrating (3) AI means getting a machine to do something its efforts on building high-quality you didn't think a machine could do educational software for use in business and (the "gee whiz" view), and (4) AI means elementary and secondary schools. In the two having a machine learn.

All inquiries should include your travel support for students who are registration area. Now Exempt from applicants must have fulfilled your lab's research efforts to be the volunteer and reporting requirements California Sales Tax shown to a large portion of the AI for previous awards. This year, Recent California legislation required community. California that can be run in parallel on several who submit a letter of recommendation Senate Bill 89 (Chapter 461, screens. Please do not send tapes of a from a faculty supervisor in lieu Statutes of 1991)-signed by the governor particular project or lecture but, of a paper, student authors from foreign at press time-provides AAAI rather, tapes that present broad institutions, and foreign scholars.