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    Artificial intelligence (AI) is exhibited by . In , the field of AI research defines itself as the study of ““: any device that perceives its environment and takes actions that maximize its chance of success at some goal. Colloquially, the term “artificial intelligence” is applied when a machine mimics “cognitive” functions that humans associate with other , such as “learning” and “problem solving” (known as ). As machines become increasingly capable, mental facilities once thought to require intelligence are removed from the definition. For instance, is no longer perceived as an exemplar of “artificial intelligence”, having become a routine technology. Capabilities currently classified as AI include successfully , competing at a high level in systems (such as and ), , intelligent routing in , and interpreting complex data.

    AI research is divided into subfields that focus on specific or on specific or on the use of a particular or towards satisfying particular .

    The central problems (or goals) of AI research include , , , , (communication), and the ability to move and manipulate objects. is among the field’s long-term goals. Approaches include , , and . Many tools are used in AI, including versions of , , . The AI field draws upon , , , , , and .

    The field was founded on the claim that “can be so precisely described that a machine can be made to simulate it”. This raises philosophical arguments about the nature of the and the ethics of creating artificial beings endowed with human-like intelligence, issues which have been explored by , and since . Some people also consider AI a danger to humanity if it progresses unabatedly. Attempts to create artificial intelligence have experienced many , including the of 1966, the abandonment of in 1970, of 1973, and the in 1987.

    In the twenty-first century, AI techniques, both “hard” and “soft” have experienced a resurgence following concurrent advances in , sizes of , and theoretical understanding, and AI techniques have become an essential part of the , helping to solve many challenging problems in computer science.




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