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The Applications of Artificial Intelligence Introduction Artificial intelligence (AI) is a branch of computer science that studies the computational requirements for tasks such as perception, reasoning, and learning, and develops systems to perform those tasks. AI is a diverse field whose researchers address a wide range of problems, use a variety of methods, and pursue a spectrum of scientific goals. For example, some researchers study the requirements for expert performance at specialized tasks, while others model commonsense processes; some researchers explain behaviors in terms of low-level processes, using models inspired by the computation of the brain, while others explain them in terms of higher-level psychological constructs such as plans and goals. Some researchers aim to advance understanding of human cognition, some to understand the requirements for intelligence in general (whether in humans or machines), and some to develop artifacts such as intelligent devices, autonomous agents, and systems that cooperate with people to amplify human abilities. AI is a young field--even its name, ``artificial intelligence,'' was only coined in 1956.
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This is the goal of the field of AI, yet it is not an easy goal to define. AI researchers express their goals differently, but they all share an interest in creating, through the hardware and software of a computer, an entity that is in some way recognized as intelligent and that shares some aspects of the distinctly human conditions. Thus, AI can be viewed as the attempt to create a machine that is in some way created in the image of the human person, an image loosely defined using the term intelligence. [3] One of the most challenging approaches facing experts is building systems that mimic the behavior of the human brain, made up of billions of neurons, and arguably the most complex matter in the universe. Alan Turing, a British computer scientist, stated that a computer would deserves to be called intelligent if it could deceive a human into believing that it was human.
Because our mind creates representations for things in the world it can be concluded that the mind is also an intentional system (Flanagan, 1991, p. 178). The idea of intentionality within the mind leads us to believe that the assumption stating psychology needs to appeal to internal processes to understand complex behaviors could be supported. Intentionality has been reinforced by psychologists in their explanations of cognitive processes for many years now. The assumption that psychology needs to be attractive to internal processes to understand intelligent behavior seems plausible b... ... middle of paper ... ...on processors Therefore, it is not plausible to support sociobiologists arguments solely. To conclude, it can be said that the understanding of cognitive processes and intelligent behaviors will continue to grow.
While artificial intelligence can produce Ph.D. quality experts, a more difficult challenge lies in creating a naive observer. The common sense people use in everyday reasoning provides one of the most difficult challenges in building intelligent systems. Common sense reasoning is often based on incomplete knowledge and is powerfully broad in its use. Intelligent systems have historically been successful in specific domains with well defined structures. To make them succeed in a broad arena, they would need either a greater base of knowledge or be able to deal with uncertainty and learn.
Some of the leading experts and researchers in the field of Artificial Intelligence (AI) have tried to define the term or the subject. Phillip Jackson, in his book An Introduction to Artificial Intelligence (1985), defines AI research as ‘an attempt to discover and describe aspects of human intelligence that can be simulated by machines’ (Jackson, 1985). John McCarthy, one of the pioneer scientists in the field and the person believed to have coined the term ‘artificial intelligence’ defined the goal of AI as ‘to develop machines that behave as though they were intelligent.’ This definition, however, is insufficient because it does not comprehensively capture the intended purpose of AI; it is too general. The definition that best captures the definition of AI was given ... ... middle of paper ... ...l the cursor of a mouse by what they think and using their speech. The system, created at Washington University, enables people who have had damage to their speech because of a brain injury or who have limited mobility because of injury to use computers just as normal people would (Leuthardt, et al., 2011).