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Artificial Intelligence

What Is Intelligence?, Overview Of Ai, General Problem Solving, Expert Systems, Natural Language Processing

Certain tasks can be performed faster and more accurately by traditionally programmed computers than by human beings, particularly numerical computation and the storage, retrieval, and sorting of large quantities of information. However, the ability of computers to interact flexibly with the real world—their "intelligence"—remains slight. Artificial intelligence (AI) is a subfield of computer science that seeks to remedy this situation by creating software and hardware that possess some of the behavioral flexibility shown by natural intelligences (people and animals).

In the 1940s and 1950s, the first large, electronic, digital computers were designed to accomplish specific tasks (e.g., a numerical calculation set up by a human programmer) by completing a series of clearly defined steps, an algorithm. Programmers wrote algorithmic software that precisely specified both the problem and how to solve it. AI programmers, in contrast, seek to program computers not with rigid algorithms but with flexible rules for seeking solutions. An AI program may even be designed to modify the rules it is given or to develop entirely new rules.

What types of problem are appropriate for traditional, algorithmic computing and what types call out for AI? Some of the tasks that are hardest for people are, fortunately, algorithmic in nature. Teachers can describe in detail the process for multiplying numbers, and accountants can state accurately the rules for completing tax forms, yet many people have difficulty performing such tasks. Straightforward, algorithmic programs can perform them easily because they can be broken down into a series of precise procedures or steps that do not vary from case to case. On the other hand, tasks that require little thought for human beings can be hard to translate into algorithms and therefore difficult for computers to perform. For example, most people know that a pot of boiling water requires careful handling. We identify hot pots by flexible recognition of many possible signs: steam rising, radiant heat felt on the skin, a glimpse of blue flame or red coils under the pot, a rattling lid, and so forth. Once we know that the pot is boiling, we plan our actions accordingly. This process seems simple, yet describing exactly to a computer how to reliably conclude "this pot is hot" and to take appropriate action turns out to be extremely difficult. The goal of AI is to create computers that can handle such complex, flexible situations. One obstacle to this goal is uncertainty or confusion about what is intelligence.

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