It refers to the simulation of human intelligence by machine or computers.
It deals with intelligent machines which can think. The intelligent process of machine involves learning and reasoning.
However, the artificial intelligence is both the intelligence of machines and the branch of computer science which aims to create it. John Mc Carthy, who coined the term in 1956, defines it as the science and engineering of making intelligent machines.
The trait that researchers hope machines will exhibit are reasoning, knowledge, planning, learning, communication, perception and the ability to move and manipulate objects.
Artificial Intelligence research uses tools and insights from many fields, including computer science, psychology, philosophy, neuroscience, operations research, control theory, probability, logic etc. All research also overlaps with tasks such as robotics, control systems, speech recognitions, facial recognition and many others. Other names for this have been proposed, such as computational intelligence, synthetic intelligence, intelligent systems etc.
The field of Artificial Intelligence is also the study of ways in which machines can be made to have sufficient creative reasoning power to perform mental tasks at which at present human beings are better.
Examples of problems that fall under the area of AI include common sense tasks such as understanding a language, recognizing scenes, finding a way to reach an object that is far overhead.
In addition, AI also includes expert tasks such as diagnosing diseases, designing computer systems, planning scientific expeditions etc. But a machine with true artificial intelligence has not been created. AI studies have been focusing too narrowly on intelligent behaviour.
There is also a paradoxical situation where AI specialists have been able to construct sophisticated knowledge based on expert systems but are unable to come to grips with ordinary everyday perceptional motor behaviour such as vision, speech, locomotion, manipulation, language etc. computers at present are smart in some ways but are not intelligent.
They mechanically work out solutions to problems but they do not use a logical, intuitive approach that characterizes human beings. Thus, AI expert systems are the bridge between human and computer method of problem solving.
However, through the applications of AI techniques, expert systems capture the basic knowledge that allows a human to act as an expert when dealing with real life problems.
One of the prime requirements of AI technique is that, must copy, reflect as closely as possible the human judgments reasoning and intuition used in solving real world problems which are characterized by uncertainty. One reason for the computer’s failure to accurately mimic the human reasoning is the use of conventional and classical bivalent/ binary logic.
In binary logic, every event has only two states-either it occurs or it does not. Therefore, such a representation is inadequate for modeling the under stable complex real life intuitions. Thus, from these facts we can infer that, computers as we currently know them are not adequate models of human brains. So, it can be concluded that human brain cannot be equated with artificial intelligence