Today, surrounded by so many automatic machines industrial robots, and the R2-D2's of Star wars movies, most people think AI is much more advanced than it is. But still, many "computer experts" don't believe that machines will ever "really think." I think those specialists are too used to explaining that there's nothing inside computers but little electric currents. And there are many other reasons why so many experts still maintain that machines can never be creative, intuitive, or emotional, and will never really think, believe, or understand anything.

A major strength of frame-based knowledge representation languages is their ability to provide the knowledge base designer with a concise and intuitively appealing means expression. To be effective as a knowledge base development tool, a language needs to be supported by an implementation that facilitates creating, browsing, debugging, and editing the descriptions in the knowledge base. We have focused on providing such support in a SmallTalk (Ingalls, 1978) implementation of the KL-ONE knowledge representation language (Brachman, 1978), called KloneTalk, that has been in use by several projects for over a year at Xerox PARC. In this note, we describe those features of KloneTalk's displaybased interface that have made it an effective knowledge base development tool, including the use of constraints to automatically determine descriptions of newly created data base items.

Interactive intelligent systems often suffer from a basic conflict between their computationally intensive nature and the need for responsiveness to a user. This paper introduces the Interviewer/Reasoner model, which helps to reduce this conflict. This model partitions an intelligent system into two asynchronous components. The Interviewer's primary function is to gather data while providing an acceptable response time to the user. The Reasoner does most of the symbolic computation for the system. This paper describes the implementation of the model in both timesharing and personal workstation environments, and uses the ONCOCIN system as an example.

Why People Think Computers Can't MOST PEOPLE ARE CONVINCED computers cannot think. I think those specialists are too used t,o That is, really think. This leads them to believe that there can't "thinking." This essay explains why they are wrong . Can Computers Do Only What They're Told? concerned with huge numerical computations: that's why the things were called computers. Most people think that "creativity" Yet even then a fringe of people envisioned what's now If so, then no computer can create-since, clearly, they realized that computers could manipulate not only numbers anything machines can do can be explained. To see what's wrong with that, we'd better turn aside able to go beyond arithmetic, perhaps to imitate the informa-from those outstanding works our cuhure views as very best Con processes that happen inside minds.

We describe a program for verifying that a set of rules in an expert system comprehensively spans the knowledge of a specialized domain. The program has been devised and tested within the context of the ONCOCIN System, a rule-based consultant for clinical oncology. The stylized format of ONCOIN's rule has allowed the automatic detection of a number of common errors as the knowledge base has been developed. This capability suggests a general mechanism for correcting many problems with knowledge base completeness and consistency before they can cause performance errors.

I apologise for any mistakes or misinterpretations I may therefore have made. In October 1981,.Japan announced a national project to develop highly innovative computer systems for the 199Os, with the title "Fifth Generation Computer Systems " This paper is a personal view of that project, The fifth generation plan its significance, and reactions to it. In late 1978 the Japanese Ministry of International Trade THIS PAPER PRESENTS a personal view of the Japanese and Industry (MITI) gave ETL the task of defining a project Fifth Generation Computer Systems project.

A major strength of frame-based knowledge representation languages is their ability to provide the knowledge base designer with a concise and intuitively appealing means expression. The claim of intuitive appeal is based on the observation that the object -centered style of description provided by these languages often closely matches a designer's understanding of the domain being modeled and therefore lessens the burden of reformulation involved in developing a formal description. To be effective as a knowledge base development tool, a language needs to be supported by an implementation that facilitates creating, browsing, debugging, and editing the descriptions in the knowledge base. We have focused on providing such support in a SmallTalk (Ingalls, 1978) implementation of the KL-ONE knowledge representation language (Brachman, 1978), called KloneTalk, that has been in use by several projects for over a year at Xerox PARC. In this note, we describe those features of KloneTalk's displaybased interface that have made it an effective knowledge base development tool, including the use of constraints to automatically determine descriptions of newly created data base items.

Three experiments have been conducted, and some novel designs and design rules have emerged. The paradigm for Eurisko's exploration is a loop in which it generates a new device configuration, computes its I/O behavior, tries to "parse" this into a functionally it already knows about and can use, and then evaluates the results. In the first experiment, this loop took place at the level of charged carriers moving under the effects of electric fields through abutted regions of doped and undoped semiconductors. This was unsurprising, as they were short sentences in the descriptive language we had defined (a language with verbs like Abut and ApplyEField, and with nouns like nDoped Region and IntrinsicChannellRegion).

OUR SUMMER ISSUE departs from the usual format and designers of integrated circuit,s. The authors show how the is devoted to a single thememPapplications of knowledge engineering "engineering of knowledge" can modulate the creation and in VLSI design. Wit,h these examples they expand the usual scope of the the fruits of microelectronics. In t,he second article, collectively explore the opportunities provided by substantially Lenat, Sutherland, and Gibbons consider ways to extend increased amounts of silicon computing power.

Eurisko is an AI program that learns by discovery. We are applying Eurisko to the task of inventing new kinds of three- dimensional microelectronic devices that can then be fabricated using recently developed laser recrystallization techniques. Three experiments have been conducted, and some novel designs and design rules have emerged. The paradigm for Eurisko's exploration is a loop in which it generates a new device configuration, computes its I/O behavior, tries to "parse" this into a functionally it already knows about and can use, and then evaluates the results. In the first experiment, this loop took place at the level of charged carriers moving under the effects of electric fields through abutted regions of doped and undoped semiconductors. Many of the well-known primitive devices were synthesized quickly, such as the MOSFET, Junction Diode, and Bipolar Transistor. This was unsurprising, as they were short sentences in the descriptive language we had defined (a language with verbs like Abut and ApplyEField, and with nouns like nDoped Region and IntrinsicChannellRegion).