Artificial intelligence

Artificial intelligence (AI) is a subfield of computer science that focuses on creating computer software that imitates human learning and reasoning. Computers can out-perform people when it comes to storing information, solving numerical problems, and doing repetitive tasks. Computer programmers originally designed software that accomplished these tasks by completing algorithms, or clearly defined sets of instructions. In contrast, programmers design AI software to give the computer only the problem, not the steps necessary to solve it.

Overview of artificial intelligence

All AI programs are built on two foundations: a knowledge base and an inferencing capability (inferencing means to draw a conclusion based on facts and prior knowledge). A knowledge base is made up of many different pieces of information: facts, concepts, theories, procedures, and relationships. Where conventional computer software must follow a strictly logical series of steps to reach a conclusion (algorithm), AI software uses the techniques of search and pattern matching. The computer is given some initial information and then searches the knowledge base for specific conditions or patterns that fit the problem to be solved. This special ability of AI programs—to reach a solution based on facts rather than on a preset series of steps—is what most closely resembles the thinking function of the human brain. In addition to problem solving, AI has many applications, including expert systems, natural language processing, and robotics.

Expert systems. The expert system is an AI program that contains the essential knowledge of a particular specialty or field, such as medicine, law, or finance. A simple database containing information on a particular subject can only give the user independent facts about the subject. An expert system, on the other hand, uses reasoning to draw conclusions from stored information. Expert systems are intended to act as intelligent assistants to human experts.

Natural language processing. Most conventional computer languages consist of a combination of symbols, numbers, and some words. These complex languages may take several years for a computer user to master. Computers programmed to respond to our natural language—our everyday speech—are easier and more effective to use. In its simplest form, a natural language processing program works like this: a computer user types a sentence, phrase, or words on the keyboard. After searching its knowledge base for references to every word, the program then responds appropriately.

An example of a computer with a natural language processor is the computerized card catalog available in many public libraries. If you want a list of books on a specific topic or subject, you type in the appropriate phrase. You are asking the computer—in English—to tell you what is available on the topic. The computer usually responds in a very short time—in English—with a list of books along with call numbers so you can find what you need.

Words to Know

Algorithm: Clearly defined set of instructions for solving a problem in a fixed number of steps.

Expert system: AI program that contains the essential knowledge of a particular specialty or field such as medicine or law.

Natural language: Language first learned as a child; native tongue.

Robotics: Study of robots, machines that can be programmed to perform manual duties.

Software: Set of programs or instructions controlling a computer's functions.

Robotics. Robotics is the study of robots, which are machines that can be programmed to perform manual duties. Most robots in use today perform various repetitive tasks in an industrial setting. These robots typically are used in factory assembly lines or in hazardous waste facilities to handle substances far too dangerous for humans to handle safely.

Research is being conducted in the field of intelligent robots—those that can understand their environment and respond to any changes. AI programs allow a robot to gather information about its surroundings by using a contact sensor to physically touch an object, a camera to record visual observations, or an environmental sensor to note changes in temperature or radiation (energy in the form of waves or particles).

Intelligent machines?

The question of whether computers can really think is still being debated. Some machines seem to mirror human intelligence, like I.B.M.'s chess-playing computer, Deep Blue, or the robotic artist named Aaron that produces paintings that could easily pass for human work. But most researchers in the field of artificial intelligence admit that at the beginning of the twenty-first century, machines do not have the subtlety, depth, richness, and range of human intelligence. Even with the most sophisticated software, a computer can only use the information it is given in the way it is told to use it. The real question is how this technology can best serve the interests of people.


An algorithm is a set of instructions that indicate a method for accomplishing a task in mathematics or some other field. People use algorithms every day, usually without even thinking about it. When you multiply two numbers with a hand calculator, for example, the first step is to enter one number on the keyboard. The next step is to press the multiplication sign (×) on the keyboard. Then you enter the second number on the keyboard. Finally you press the equals sign (=) to obtain the answer. This series of four steps constitutes an algorithm for multiplying two numbers. Many algorithms are much more complicated than this one. They may involve dozens or even hundreds of steps.

[ See also Automation ; Computer, analog ; Computer, digital ; Computer software ; Cybernetics ; Robotics ]

Also read article about Artificial Intelligence from Wikipedia

User Contributions:

Ahmed desoky
Learning is considered as a parameter for intelligent machines. Deep understanding would help in taking decisions in a more optimized form and also help then to work in most efficient method. As seeing is intelligence, so learning is also becoming a key to the study of biological and artificial vision. Instead of building heavy machines with explicit programming now different algorithms are being introduce which will help the machine to understand the virtual environment and based on their understanding the machine will take particular decision. This will eventually decrease the number of programming concepts and also machine will become independent and take decisions on their own.
Different algorithms are introduced for different types of machines and the decisions taken by them. Designing the algorithm and using it in most appropriate way is the real challenge for the developers and scientists.

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