Artificial Intelligence

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    • artificial intelligence (AI) | Intelligence Shown By Machines
      In computer science, artificial intelligence (AI), sometimes called artificial intelligence, is the intelligence shown by machines, in contrast to the natural intelligence shown by humans and animals. The main AI textbooks define the field as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chances of successfully achieving its goals. Colloquially, the term "artificial intelligence" is often used to describe machines (or computers) that mimic the "cognitive" functions that humans associate with the human mind, such as "learning" and "problem-solving". As machines become increasingly capable, tasks considered "intelligence" are often removed from the definition of AI, a phenomenon known as the AI ​​effect. A joke in Tesler's Theorem says "Artificial intelligence is all that hasn't been done yet." For example, optical character recognition is often excluded from things considered AI, having become a routine technology. The capabilities of modern machines generally classified as AI include understanding human speech, competition at the highest levels in strategic game systems (such as chess and gambling), self-operating cars, intelligent routing in content distribution, and military simulations. Artificial intelligence was founded as an academic discipline in 1955 and over the years has undergone several waves of optimism, followed by disappointment and loss of funds (known as "AI winter"), followed by new approaches, success, and renewed funding. For much of its history, artificial intelligence research has been divided into subfields that often fail to communicate with each other. These subfields are based on technical considerations, such as particular objectives (eg "Robotics" or "machine learning"), the use of particular tools ("logic" or artificial neural networks), or profound philosophical differences. The subfields were also based on social factors (particular institutions or the work of particular researchers). Traditional AI research problems (or goals) include reasoning, knowledge representation, planning, learning, natural language processing, perception, and ability to move and manipulate objects. General intelligence is among the long-term goals of the camp. The approaches include statistical methods, computational intelligence, and traditional symbolic AI . Many tools are used in AI, including versions of mathematical research and optimization, artificial neural networks, and methods based on statistics, probability, and economics. The AI ​​field is based on computer science, information engineering, mathematics, psychology, linguistics, philosophy, and many other fields. The field was founded on the assumption that human intelligence "can be described so precisely that it can manufacture a machine to simulate it". This raises philosophical arguments about the nature of the mind and the ethics of creating artificial beings endowed with human intelligence. These problems have been explored by myth, fiction, and philosophy since antiquity. Some people also consider AI a danger to humanity if it progresses relentlessly. Others believe that AI, unlike previous technological revolutions, will create a risk of mass unemployment. In the twenty-first century, artificial intelligence techniques have undergone a revival following simultaneous advances in computer power, large amounts of data and theoretical understanding; and artificial intelligence techniques have become an essential part of the technology sector, helping to solve many demanding problems in computer science, software engineering, and operational research.
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