Fox News correspondent Grady Trimble has the latest on fears the technology will spiral out of control on'Special Report.' Artificial intelligence leader OpenAI has introduced the ability to turn off chat history in its popular chatbot ChatGPT. In a Tuesday blog post, the company said conversations that are started when chat history is disabled will not be used to train and improve its models and will not appear in the history sidebar. The controls are found in the ChatGPT settings and can be changed at any time. The mode rolled out ot all users.

Chatbots and conversational AI have been gaining acceptance as essential pieces of successful customer service and employee support strategies. If your organisation doesn't have at least one of these solutions already, it's likely you are planning to deploy one soon or are exploring the possibility of adding one to your 2023 strategy. Unfortunately, as adoption of this technology is increasing so is the oversaturation of the market with poor performing chatbot products. Now many live chat, CRM, and contact centre vendors are attempting to jump on the conversational AI bandwagon with their own'add-on bots'. This is creating both confusion for buyers and a starker divide between vendors selling add-on bots and vendors that are true conversational AI specialists.

Computational metacognition represents a cognitive systems perspective on high-order reasoning in integrated artificial systems that seeks to leverage ideas from human metacognition and from metareasoning approaches in artificial intelligence. The key characteristic is to declaratively represent and then monitor traces of cognitive activity in an intelligent system in order to manage the performance of cognition itself. Improvements in cognition then lead to improvements in behavior and thus performance. We illustrate these concepts with an agent implementation in a cognitive architecture called MIDCA and show the value of metacognition in problem-solving. The results illustrate how computational metacognition improves performance by changing cognition through meta-level goal operations and learning.

The Brain Makers: Genius, Ego, and Greed in the Quest for Machines That Think, Harvey P. Newquist, Sams Publishing, Indianapolis, Indiana, 1994, 488 pp., $24.95, ISBN 0-672-30412-0. Newquist is a business reporter who covered the field during the 1980s when academic researchers went commercial in one of the 1980's smaller speculative bubbles. His book begins with a history spanning Babbage to Turing to Minsky, McCarthy, Newell, Simon, Samuel, and others at the 1956 Dartmouth meeting and moves on to the 1980s, where the real story begins. Good, if glib, descriptions of people, places, and events are punctuated by technical explanations ranging from poor to inane. Because I am a little slow, it took me a quarter of the book to recognize a journalist with an attitude.

The First International Conference on Intelligent Systems for Molecular Biology (ISMB-93), held 6-9 July 1993 at the Lister Hill Center of the National Library of Medicine (NLM), attracted over 200 computer scientists and biologists from 13 countries. As organizers of the conference, we saw it as the culmination of a series of successful meetings and colloquia, including workshops by the American Association for Artificial Intelligence, that, taken as a whole, indicate that molecular biology is one of the most rapidly growing application areas of AI and warrants a dedicated conference. AAAI was a cosponsor of the meeting and published the proceedings (AAAI Press, Menlo Park CA, ISBN 0-929280-47-4, $45). Extensive additional support in the form of grants was provided by the National Institutes of Health (NIH), primarily through NLM but also through the Division of Computer Research and Technology, and by the Department of Energy Office of Health and Environmental Research (which, like NIH, is heavily involved in the Human Genome Project). Further support was provided by the Biomatrix Society, a group that has a predilection for AI approaches to biological data.

However, recently, there seems to be a new wave of interest, as indicated by many papers, monographs, edited books, and doctoral theses, in exploring aspects of similarity and analogical reasoning from various perspectives. Amid these numerous publications, Similarity and Analogical Reasoning surely stands out as the most valuable reference work on the topic, covering especially well the recent advances in the understanding of this topic, with many chapters written by leading researchers. Although it is based on a collection of papers initially presented at the Workshop on Similarity and Analogy, unlike the typical workshop proceedings, this volume is well edited and coherent in both its content and format, with a great deal of cross-references and detailed summary-comment chapters for every part of the book. Let us look at the book in detail. Because each of these chapters has a different perspective, approach, and organization, I first discuss a number of chapters one by one.

Basic Books Ad In the introduction to this anthology, Boden defines the philosophy of AI broadly "as the science of intelligence in general--or, more accurately, as the intellectual core of cognitive science." Through this comprehensive definition, she embraces the definitional extremes, including those that traditionally view AI "as the study of how to build and/or program computers to enable them to do the sorts of things that minds can do" and those that make no reference to the computer at all. This collection, however, focuses on the philosophical problems associated with the machine metaphor and asks whether machine intelligence is possible. For those already familiar with the literature, this volume provides a handy compendium. For students, it provides a concise overview of the machine intelligence debate.

AI (see AI Magazine, Vol. 6, All of the contributions in this book have a practical slant, showing how Al has been successfully applied to a wide spectrum of domains and tasks. They provide an excellent sampling of the types of applications coming on line. Systems architectures and development strategies are addressed along with tactical issues, payback data, and real benefits. To order call toll-free .I -800-356-0343 or 617-625-8569 Fax orders.

A large body of work exists today in the area of design, including Brown and Chandrasekharan (1989) and Dym and Levitt (1991). Also see the Winter 1990 issue of AI Magazine, which was guest edited by J. S. Gero with Mary Lou Maher. By virtue of the teaching experience that supports this book, however, it is more comprehensive and presents its viewpoint in a systematic, orderly progression. The differences between the approaches by different groups are slight. For example, the propose, critique, and modify approach of Chandrasekaran's group (AI Magazine, Winter 1990) is akin to the prototype creation, refinement, and adaptation idea previously described.

Today, mobile robotics is an increasingly important bridge between the two areas. It is advancing the theory and practice of cooperative cognition, perception, and action and serving to reunite planning techniques with sensing and real-world performance. Further, developments in mobile robotics can have important practical economic and military consequences. For some time now, amateurs, hobbyists, students, and researchers have had access to how-to books on the low-level mechanical and electronic aspects of mobile-robot construction (Everett 1995; McComb 1987). The famous Massachusetts Institute of Technology (MIT) 6.270 robot-building course has contributed course notes and hardware kits that are now available commercially and in the form of an influential book (Jones 1998; Jones and Flynn 1993).