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1.1.1 What is artificial intelligence?
1.1.1 What is artificial intelligence?

... McCarthy convinced Minsky, Claude Shannon, and Nathaniel Rochester to help him bring together U.S. researchers interested in automata theory, neural nets, and the study of intelligence. They organized a two-month workshop at Dartmouth in the summer of 1956. Perhaps the longest-lasting thing to come ...
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... McCarthy convinced Minsky, Claude Shannon, and Nathaniel Rochester to help him bring together U.S. researchers interested in automata theory, neural nets, and the study of intelligence. They organized a two-month workshop at Dartmouth in the summer of 1956. Perhaps the longest-lasting thing to come ...
No Slide Title - Learning Research and Development Center (LRDC)
No Slide Title - Learning Research and Development Center (LRDC)

... Reduce high transaction cost of legal services Make it easier to treat like cases alike Facilitate alternative dispute resolution Advance public understanding of the law and legal system ...
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... state. The problems for which such simulation is appropriate are generally prediction problems: given a spatial situation and some proposed actions on, or interaction between, the elements in it, what will be the spatial representation corresponding to the new situation? The simulation is supposed t ...
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ibm-cognitive-curriculum-6-6

... Business: What should executives and managers know about this rapidly advancing technology? What should students know about the full range of market opportunities? Society: What should everyone (citizens of the 21st century) know about the practical, political, and philosophical implications? Interd ...
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IOSR Journal of Computer Engineering (IOSR-JCE)

... communication costs. Because most techniques used in today's IDS are not able to deal with the dynamic and complex nature of cyber-attacks on computer networks. So the author reviewed several influential algorithms for intrusion detection based on various machine learning techniques, and divided the ...
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... Despite the apparent success of the technology, few people use such speech recognition systems on their desktop computers. A typical office environment, with high amplitude of background speech, is one of the most adverse environments for current speech recognition technologies, and large-vocabulary ...
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... this line of research. They first identified the key features in risk assessment based on past classifications such as those presented by Wallace and Keil (2004) and further interviews with project managers. They identified a total of 39 risk factors which they grouped into 5 risk categories: projec ...
IOSR Journal of Computer Engineering (IOSR-JCE)
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... II. Application of AI and Allied Techniques in IDS Artificial Intelligence contributes significantly for intrusion detection in terms of data reduction, analyzing data to identify components and identifying the intruders. Artificial Intelligence could make the use of Intrusion Detection Systems. The ...
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Global Artificial Intelligence Market Analysis & Trends - Industry Forecast... 2025 Brochure
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... Table 12 North America Artificial Intelligence Market By Hardware, Forecast (2013-2025) (US$ MN) Table 13 North America Artificial Intelligence Market By System Type, Forecast (2013-2025) (US$ MN) Table 14 North America Artificial Intelligence Market By AI Type, Forecast (2013-2025) (US$ MN) Table ...
Recent advances in computational models of natural argument
Recent advances in computational models of natural argument

... There are two distinct ways in which AI has developed systems involving argumentation. The first is in using concepts and intuitions about argument to inspire and provide foundations for the development of formal systems ~and often, specifically, formal nonclassical logics!. This approach we might t ...
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Exploring coordination properties within populations of distributed agents Elizabeth Sklar

... perceive where they are supposed to be in the formation, given their current location and those of the other robots, then they move into position to maintain the formation. Stone & Veloso (1998) propose the use of “locker-room agreements” for the RoboCup soccer simulation league as a way of impleme ...
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History of artificial intelligence

The history of artificial intelligence (AI) began in antiquity, with myths, stories and rumors of artificial beings endowed with intelligence or consciousness by master craftsmen; as Pamela McCorduck writes, AI began with ""an ancient wish to forge the gods.""The seeds of modern AI were planted by classical philosophers who attempted to describe the process of human thinking as the mechanical manipulation of symbols. This work culminated in the invention of the programmable digital computer in the 1940s, a machine based on the abstract essence of mathematical reasoning. This device and the ideas behind it inspired a handful of scientists to begin seriously discussing the possibility of building an electronic brain.The field of AI research was founded at a conference on the campus of Dartmouth College in the summer of 1956. Those who attended would become the leaders of AI research for decades. Many of them predicted that a machine as intelligent as a human being would exist in no more than a generation and they were given millions of dollars to make this vision come true. Eventually it became obvious that they had grossly underestimated the difficulty of the project. In 1973, in response to the criticism of James Lighthill and ongoing pressure from congress, the U.S. and British Governments stopped funding undirected research into artificial intelligence. Seven years later, a visionary initiative by the Japanese Government inspired governments and industry to provide AI with billions of dollars, but by the late 80s the investors became disillusioned and withdrew funding again. This cycle of boom and bust, of ""AI winters"" and summers, continues to haunt the field. Undaunted, there are those who make extraordinary predictions even now.Progress in AI has continued, despite the rise and fall of its reputation in the eyes of government bureaucrats and venture capitalists. Problems that had begun to seem impossible in 1970 have been solved and the solutions are now used in successful commercial products. However, no machine has been built with a human level of intelligence, contrary to the optimistic predictions of the first generation of AI researchers. ""We can only see a short distance ahead,"" admitted Alan Turing, in a famous 1950 paper that catalyzed the modern search for machines that think. ""But,"" he added, ""we can see much that must be done.""
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