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2017 Trends to Watch: Artificial Intelligence - Ovum
2017 Trends to Watch: Artificial Intelligence - Ovum

... human history. This AI technology will permeate many application areas in 2017, ranging from autonomous driving to a wide variety of Internet of Things applications, from consumer products to healthcare. IoT in particular will generate big data too vast for humans to process and AI will play a major ...
ISAP 2003
ISAP 2003

... Hellenic National Committee of CIGRE and the Hellenic Artificial Intelligence Society. ISAP 2003 was specifically dedicated to discuss innovative solutions in the area of operation, control, planning and maintenance for large interconnected but also for isolated or weakly interconnected power system ...
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Resources - IIT Bombay

... Halting problem: It is impossible to construct a Universal Turing Machine that given any given pair of Turing Machine M and input I, will decide if M ...
Expert Systems Project Management
Expert Systems Project Management

... likely progress over the next five years. An assessment of the current state of the art and its successes completes the tutorial. INTENDED AUDIENCE This tutorial is addressed to people who intend to manage or participate in the development of expert systems. It is also appropriate for those who need ...
Artificial Intelligence and Robotics
Artificial Intelligence and Robotics

... these fields will ultimately benefit our progress in the quest of creating an intelligent artificial being. AI systems are now in routine use in economics, medicine, engineering and the military, as well as being built into many common home computer software applications, traditional strategy games ...
Machine Learning and AI in Law Enforcement
Machine Learning and AI in Law Enforcement

... 1951 Marvin Minsky’s analog neural networks (1st revolution) 1956 Dartmouth conference: Artificial intelligence with aim of human like intelligence 1956-1974 Many small scale “toy” projects in robotics, control and game solving 1974 Failure of success and Minsky’s criticism of perceptron, lack of co ...
COMP 3009 Introduction to AI
COMP 3009 Introduction to AI

... machine against that of a human being. Turing called the “imitation game” places the machine and a human counterpart in rooms apart from a second human being, referred to as the “interrogator”. The interrogator is not able to see or speak directly to either of them, does not know which entity is act ...
Despite Decades of Research, why have Intelligent user Interfaces
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... Intelligent User Interfaces as a research field has been around since the mid 1980s [2]. There has been a large proliferation of research efforts in this area. There have been books [3], workshops [4], and conferences1, with the academic focus on Intelligent User Interfaces that indicates clearly a ...
Rule-Based/Expert Systems
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Advanced Intelligent Control Methods in Robotics and
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Cooperative Intelligent Agents
Cooperative Intelligent Agents

... (1) A theoretical research report on an agent-based topic based on some recent research papers: application of intelligent agents, on some development of an AI technique using intelligent agents, agent based software engineering, a particular class of agents (interface agents, mobile agents, etc) et ...
Papert (1988)
Papert (1988)

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anglais - La Jaune et la Rouge
anglais - La Jaune et la Rouge

... Apple’s recent acquisition of Vocal IQ, an artificial intelligence company that specializes in voice programs, should not on its face lead to much fanfare : It appears to be a smart business move to enhance Siri’s capabilities. But it is also another sign of the increased role of AI in our daily liv ...
blank page
blank page

Can computers have `conversations` with humans?
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... Artificial Solutions® is the leading specialist in Natural Language Interaction (NLI). The company’s patented technology enables people to converse with applications and services running on computers, mobiles, wearables and other electronic devices in a humanlike, intelligent manner. Called Teneo, i ...
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Herbert A. Simon - History Committee archive
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... Recognition processes, modeled by production systems, have provided one important basis for the expert systems now common in AI applications. The work on EPAM has also continued to the present time, producing a system that simulates human behavior over a wide range of the perceptual, learning, and ...
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... some unknown source. For example, an AI could be extracted from a signal obtained in SETI (Search for Extraterrestrial Intelligence) research, which is not guaranteed to be human friendly [31, 32]. Other sources of such unknown but complete systems include a Levin search in the space of possible min ...
Course Overview - COW :: Ceng On the Web
Course Overview - COW :: Ceng On the Web

... Contact information: http://cow.ceng.metu.edu.tr Course Description Artificial Intelligence (AI) – CENG 462 - is a 3-credit, introductory undergraduate course on artificial intelligence methods and applications offered by the Department of Computer Engineering at METU. ...
Info Systems
Info Systems

... Expert Systems: Pros and Cons  Pros  More reliable than humans, incorporating expertise from many sources.  Able to deduce rules that are not apparent, even to experts  Capable of being extended, as the system is applied and knowledge grows  Built in high-level computer languages (called Shell ...
AI: Its Roots and Scope - CSUDH Computer Science
AI: Its Roots and Scope - CSUDH Computer Science

... optimal or exact results are either too expensive or not possible. 7. The use of large amounts of domain-specific knowledge in solving problems. This is the basis of expert systems. 8. The use of meta-level knowledge to effect more sophisticated control of problem-solving strategies. Although this i ...
Center for Intelligent Technologies - AI-CIT
Center for Intelligent Technologies - AI-CIT

... discuss possibility to join http://www.ispacelabnet.org/members Engage cloud computing in our problems prefer Microsoft for research – Imagine cup ...
UBIC Participates in the Japanese Society for Artificial Intelligence`s
UBIC Participates in the Japanese Society for Artificial Intelligence`s

... Company mainly presented examples of the practical business applications of UBIC's AI technology. In addition to participating in this conference, UBIC presented cases of practical AI applications at the 96th meeting of the Special Interest Group on Fundamental Problems of Artificial Intelligence, w ...
The 2018 IEEE International Conference on Systems, Man, and
The 2018 IEEE International Conference on Systems, Man, and

... Call for Special Sessions Proposals to organize Special Sessions are strongly encouraged. Special Sessions must be related to the conference theme or especially hot topics within the conference scope. All submitted papers undergo the same review process, and submission to proposed sessions is not a ...
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AI winter

In the history of artificial intelligence, an AI winter is a period of reduced funding and interest in artificial intelligence research. The term was coined by analogy to the idea of a nuclear winter. The field has experienced several hype cycles, followed by disappointment and criticism, followed by funding cuts, followed by renewed interest years or decades later. There were two major winters in 1974–80 and 1987–93 and several smaller episodes, including: 1966: the failure of machine translation, 1970: the abandonment of connectionism, 1971–75: DARPA's frustration with the Speech Understanding Research program at Carnegie Mellon University, 1973: the large decrease in AI research in the United Kingdom in response to the Lighthill report, 1973–74: DARPA's cutbacks to academic AI research in general, 1987: the collapse of the Lisp machine market, 1988: the cancellation of new spending on AI by the Strategic Computing Initiative, 1993: expert systems slowly reaching the bottom, and 1990s: the quiet disappearance of the fifth-generation computer project's original goals.The term first appeared in 1984 as the topic of a public debate at the annual meeting of AAAI (then called the ""American Association of Artificial Intelligence""). It is a chain reaction that begins with pessimism in the AI community, followed by pessimism in the press, followed by a severe cutback in funding, followed by the end of serious research. At the meeting, Roger Schank and Marvin Minsky—two leading AI researchers who had survived the ""winter"" of the 1970s—warned the business community that enthusiasm for AI had spiraled out of control in the '80s and that disappointment would certainly follow. Three years later, the billion-dollar AI industry began to collapse.Hypes are common in many emerging technologies, such as the railway mania or the dot-com bubble. An AI winter is primarily a collapse in the perception of AI by government bureaucrats and venture capitalists. Despite the rise and fall of AI's reputation, it has continued to develop new and successful technologies. AI researcher Rodney Brooks would complain in 2002 that ""there's this stupid myth out there that AI has failed, but AI is around you every second of the day."" In 2005, Ray Kurzweil agreed: ""Many observers still think that the AI winter was the end of the story and that nothing since has come of the AI field. Yet today many thousands of AI applications are deeply embedded in the infrastructure of every industry."" He added: ""the AI winter is long since over.""
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