14-03-2015, 12:10 PM
respected sir
i need artificial intelligence in power station ppt and document and also references materiels please consider my request and send me as early as possible
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artificial intelligence in powerstation
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respected sir
i need artificial intelligence in power station ppt and document and also references materiels please consider my request and send me as early as possible
31-03-2017, 01:51 PM
According to the father of Artificial Intelligence, John McCarthy, is "The science and engineering of making intelligent machines, especially intelligent computer programs." Artificial Intelligence is a way to make a computer, a computer controlled robot, or software think intelligently, in the same way that intelligent humans think.
Artificial intelligence (AI) is the intelligence displayed by machines. In computing, the field of AI research is defined as the study of "intelligent agents": any device that perceives its surroundings and take actions that maximize their chances of success in some objective. Colloquially, the term "artificial intelligence" applies when a machine imitates "cognitive" functions that humans associate with other human minds, such as "learning" and "solving problems." As machines become increasingly capable, mental installations, once thought to require intelligence, are removed from the definition. For example, optical character recognition is no longer perceived as an example of "artificial intelligence", having become a routine technology. Capacities currently classified as AI include successful understanding of human speech, competition at a high level in strategic game systems (such as Chess and Go ), auto-driving cars, intelligent routing in content distribution networks And interpretation of complex data.
AI research is divided into subfields that focus on specific problems or specific approaches or the use of a particular tool or to satisfy particular applications. The central problems (or goals) of AI research include reasoning, knowledge, planning, learning, natural language processing (communication), perception, and the ability to move and manipulate objects. General intelligence is one of the long-term objectives of the field. Approaches include statistical methods, computational intelligence, and traditional symbolic AI. Many tools are used in AI, including search versions and mathematical optimization, logic, methods based on probability and economy. The AI field is based on computer science, mathematics, psychology, linguistics, philosophy, neuroscience and artificial psychology.
The field was founded on the assertion that human intelligence "can be described so precisely that a machine can be simulated." This raises philosophical arguments about the nature of the mind and the ethics of creating artificial beings endowed with human intelligence, issues that have been explored by myth, fiction and philosophy since antiquity. Some people also consider that AI is a danger to humanity if it progresses endlessly. Attempts to create artificial intelligence have experienced many setbacks, including the ALPAC report of 1966, the abandonment of perceptrons in 1970, the Lighthill Report of 1973, the second IA winter 1987-1993 and the collapse of the Lisp machine market in 1987.
In the 21st century, AI techniques, both "hard" and "soft", have experienced a resurgence following simultaneous advances in computer power, training set sizes and theoretical understanding, and IA have become an essential part of the technology industry, helping to solve many challenging problems in computing.
Artificial intelligence (AI) is the intelligence displayed by machines. In computing, the field of AI research is defined as the study of "intelligent agents": any device that perceives its surroundings and take actions that maximize their chances of success in some objective. Colloquially, the term "artificial intelligence" applies when a machine imitates "cognitive" functions that humans associate with other human minds, such as "learning" and "solving problems." As machines become increasingly capable, mental installations, once thought to require intelligence, are removed from the definition. For example, optical character recognition is no longer perceived as an example of "artificial intelligence", having become a routine technology. Capacities currently classified as AI include successful understanding of human speech, competition at a high level in strategic game systems (such as Chess and Go ), auto-driving cars, intelligent routing in content distribution networks And interpretation of complex data.
AI research is divided into subfields that focus on specific problems or specific approaches or the use of a particular tool or to satisfy particular applications. The central problems (or goals) of AI research include reasoning, knowledge, planning, learning, natural language processing (communication), perception, and the ability to move and manipulate objects. General intelligence is one of the long-term objectives of the field. Approaches include statistical methods, computational intelligence, and traditional symbolic AI. Many tools are used in AI, including search versions and mathematical optimization, logic, methods based on probability and economy. The AI field is based on computer science, mathematics, psychology, linguistics, philosophy, neuroscience and artificial psychology.
The field was founded on the assertion that human intelligence "can be described so precisely that a machine can be simulated." This raises philosophical arguments about the nature of the mind and the ethics of creating artificial beings endowed with human intelligence, issues that have been explored by myth, fiction and philosophy since antiquity. Some people also consider that AI is a danger to humanity if it progresses endlessly. Attempts to create artificial intelligence have experienced many setbacks, including the ALPAC report of 1966, the abandonment of perceptrons in 1970, the Lighthill Report of 1973, the second IA winter 1987-1993 and the collapse of the Lisp machine market in 1987.
In the 21st century, AI techniques, both "hard" and "soft", have experienced a resurgence following simultaneous advances in computer power, training set sizes and theoretical understanding, and IA have become an essential part of the technology industry, helping to solve many challenging problems in computing.
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