expert


Where AI Meets Neuroscience: How The Human Brain Will Make Robots Smarter

#artificialintelligence

Experts who want to build a better robot are calling for brain scientists and artificial intelligence programmers to work together, saying it will benefit both the advancement of AI technology and our understanding of the human mind. It's not about making an exact replica of the human brain and placing it into a robot. Neuroscientist-turned-AI researcher Pascal Kaufmann told International Business Times that the focus should be on understanding how the brain works as a whole, rather than piece by piece, and then using the principles that govern it in an artificial mind. He compares the development of artificial intelligence to the invention of the airplane: Human beings could not replicate a bird wing with all its nuances, but they created a plane by using the scientific principles by which a bird flies and it worked just as well. Some programmers are trying to mimic the human brain but "I think that's pointless … to copy [and] paste nature," Kaufmann said.


12 Days of AI: RE•WORK 2017 Highlights

#artificialintelligence

In the spirit of Christmas, we're going to count down to the new year with the 12 Days of AI, bringing you a new, festive AI post every day! What better way to kick off 2018 than to look back at the RE•WORK highlights of 2017 and celebrate some of our successes of the past 12 months. This year saw RE•WORK hosting more events and bringing our globally renowned Summits to new locations. Our first ever Canadian Summit this year took place in Montreal, the'Silicon Valley of AI', and was one of our biggest events to date with over 600 attendees over the two days. We were fortunate enough to be joined by the'Godfathers of AI', Yoshua Bengio, Yann LeCun and Geoffrey Hinton who appeared on a panel together for the first time ever.


The Hidden Web

AI Magazine

The difficulty of finding information on the World Wide Web by browsing hypertext documents has led to the development and deployment of various search engines and indexing techniques. However, many information-gathering tasks are better handled by finding a referral to a human expert rather than by simply interacting with online information sources. A personal referral allows a user to judge the quality of the information he or she is receiving as well as to potentially obtain information that is deliberately not made public. The process of finding an expert who is both reliable and likely to respond to the user can be viewed as a search through the network of social relationships between individuals as opposed to a search through the network of hypertext documents. Project is to create models of social networks by data mining the web and develop tools that use the models to assist in locating experts and related information search and evaluation tasks.


The Current State Of AI: One Man's Opinion

AI Magazine

General Issues What is AI all about? In general, I see two possible answers to this question. First, AI can be seen as a modern methodological tool now being used in the ancient enterprise of the study of mind. It also usually means getting a machine to do what previously only humans have done before (rather than simply improving existing techniques). There are really only three reasons to "do" izI From the scientific point of view, you should do 2I because you are interested in the mind From the technological point of view, you should do AI because you The dispute between these formalists, and more intuitive researchers, has been referred to by me (elsewhere) as the neat/scruffy distinction.


Book Reviews

AI Magazine

Stephen Grossberg The expanded edition of Perceptrons (MIT Press, Cambridge, Mass, 1988, 292 pp, $12.50) by Marvin L. Minsky and Seymour A. Papert comes at a time of unprecedented interest in the biological and technological modeling of neural networks. The one-year-old International Neural Network Society (INNS) already has over 3500 members from 38 countries and 49 U.S. states, with members joining at the rate of more than 200 per month. The American Association for Artificial Intelligence was, in fact, a cooperating society at the INNS First Annual Meeting in Boston on 6-10 September 1988. Hardly a week goes by in which a scientific meeting or special journal issue does not feature recent neural network research. Thus, substantive technical reviews or informed general assessments of the broad sweep of neural network research are most welcome to help interested scientists find their way into this rapidly evolving technology.


Expert Micros

AI Magazine

This advertisement might be posted by any manager delegatcd the responsibility for investigating the applications and market possibilities of expert systems for his/her company . To the rescue have come the authors whose books are reviewed in this article. Each author provides answers to some of the questions raised by those considering the use of expert systems on microcomputers: What are expert systems? Can they be implemented on a PC? Have any successful PC applications been created? Do I really need an expert system?


Book Reviews

AI Magazine

Stephen Grossberg The expanded edition of Perceptrons (MIT Press, Cambridge, Mass, 1988, 292 pp, $12.50) by Marvin L. Minsky and Seymour A. Papert comes at a time of unprecedented interest in the biological and technological modeling of neural networks. The one-year-old International Neural Network Society (INNS) already has over 3500 members from 38 countries and 49 U.S. states, with members joining at the rate of more than 200 per month. The American Association for Artificial Intelligence was, in fact, a cooperating society at the INNS First Annual Meeting in Boston on 6-10 September 1988. Hardly a week goes by in which a scientific meeting or special journal issue does not feature recent neural network research. Thus, substantive technical reviews or informed general assessments of the broad sweep of neural network research are most welcome to help interested scientists find their way into this rapidly evolving technology.


1058

AI Magazine

Case-based reasoning (CBR) is becoming a viable real-world technology. First, it fragments each CBR system across many chapters, making it difficult to get the big picture of how the system works and obscuring the interrelatedness of the system's parts. In addition, having each chapter draw its examples from multiple systems adds a certain context-switching overhead: Each time a system is introduced (or reintroduced), the book must set the context anew, and the reader must recall the details of the system. A second drawback to the unified framework is that although it has fairly broad coverage, it is still biased toward those systems that fit it best. As a result, important work sometimes gets only a cursory mention in the book.


Technoloev Transfer

AI Magazine

We use our experience with the Dipmeter Advisor system for well-log interpretation as a case study to examine the development of commercial expert systems. We discuss the nature of these systems as we see them in the coming decade, characteristics of the evolution process, development methods, and skills required in the development team. 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 system tools and components We also note that traditional programming skills continue to be required in the development of commercial expert systems Finally, we discuss the problem of technology transfer and compare our experience with some of the traditional wisdom of expert system development. We have observed during this effort that the development of a commercial expert system imposes a substantially different set of constraints and requirements in terms of characteristics and methods of development than those seen in the research environment.


Research Workshop on Expert Judgment, Human Error, and Intelligent Systems

AI Magazine

This workshop brought together 20 computer scientists, psychologists, and human-computer interaction (HCI) researchers to exchange results and views on human error and judgment bias. Human error is typically studied when operators undertake actions, but judgment bias is an issue in thinking rather than acting. Both topics are generally ignored by the HCI community, which is interested in designs that eliminate human error and bias tendencies. As a result, almost no one at the workshop had met before, and the discussion for most participants was novel and lively. Many areas of previously unexamined overlap were identified.