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Definition of Artificial Intelligence

Definition of Artificial Intelligence

Artificial intelligence is terms that might remind us of the greatness of Optimus Prime in the film The Transformers. Artificial intelligence is often identified with the ability of robots that can behave like humans. Definition of Artificial Intelligence, Various definitions expressed by experts to be able to give an idea of ​​artificial intelligence are some of them:

Artificial Intelligence (Artificial Intelligence) is an area of ​​research, application and instruction related to computer programming to do things that in human view are intelligent (H. A. Simon [1987]).

Artificial Intelligence (AI) is a study of how to make computers do things that can now be done better by humans (Rich and Knight [1991]).

Artificial Intelligence (AI) is a branch of computer science that in representing knowledge uses more forms of symbols than numbers, and processes information based on heuristic methods or based on a number of rules (Encyclopedia Britannica).

History of Artificial Intelligence

Various literature on artificial intelligence mention that the idea of ​​artificial intelligence began in the early 17th century when Rene Descartes suggested that the animal's body was nothing but complicated machines. Then Blaise Pascal created the first mechanical digital counting machine in 1642. Later in the 19th century, Charles Babbage and Ada Lovelace worked on programmable mechanical calculators.

Development continued, Bertrand Russell and Alfred North Whitehead published Principia Mathematica, which overhauled formal logic. Warren McCulloch and Walter Pitts published "Logical Calculus of Ideas that Remain in Activities" in 1943 which laid the initial foundation for neural networks.

The 1950s were a period of active effort in AI. The first AI program to work was written in 1951 to run the Ferranti Mark I engine at the University of Manchester (UK): a script play program written by Christopher Strachey and a chess game program written by Dietrich Prinz. John McCarthy coined the term "Artificial Intelligence" at the first conference in 1956, in addition he also discovered the Lisp programming language. Alan Turing introduced "Turing test" as a way to operationalize intelligent behavior tests. Joseph Weizenbaum built ELIZA, a chatterbot that applies Rogerian psychotherapy.

During the 1960s and 1970s, Joel Moses demonstrated the power of symbolic considerations to integrate problems within the Macsyma program, the first knowledge-based program in mathematics. Marvin Minsky and Seymour Papert published Perceptrons, which demonstrated the limits of simple neural networks and Alain Colmerauer developed the computer language Prologue. Ted Shortliffe demonstrates the power of a rule-based system for the representation of knowledge and inference in diagnosis and medical therapy which is believed to be the first expert system. Hans Moravec developed the first computer controlled vehicle to overcome the road that had obstacles independently.

Types of Artificial Intelligence

In its development, artificial intelligence can be grouped as follows:

Expert System, a computer as a means to store knowledge of experts so that computers have the expertise to solve problems by imitating expertise possessed by experts.

Natural Language Processing (Natural Language Processing), users can communicate with computers using everyday language, such as English, Indonesian, and so on.

Introduction to Speech Recognition, humans can communicate with computers using sound.

Robotics & Sensor Systems.

Computer Vision, interpret images or visible objects through a computer.

Intelligent Computer-Aided Instruction, a computer can be used as a tutor who can train & teach.

Game Playing.

Soft Computing

Soft computing is an innovation in building intelligent systems, namely systems that have expertise such as humans in certain domains, are able to adapt and learn in order to work better in the event of changes in the environment. Soft computing exploits tolerance for inaccuracies, uncertainties, and partial truths to be easily resolved and controlled to fit reality (Prof. Lotfi A Zadeh, 1992).

The methodologies used in Soft computing are:

Fuzzy / Fuzzy Logic Logic (accommodating inaccuracy).

Artificial Neural Network (using learning).

Probabilistic Reasoning (accommodating uncertainty).

Genetic / Evolutionary Computing (optimization) algorithm.

Something unique, for example, in the future when you visit a travel agent site, then on a computer screen a woman's face will appear that is perfect because everything is a computer creation. Uniquely, you will be able to converse with this artificial woman, just like you talk to a female staff really at the counter of a travel agency. If this is achieved, then services can be provided 100% online, with very high accuracy. Especially from the consistency, friendliness, speed and accuracy of service. It's different if we use original human staff whose consistency cannot be accurate because it is affected by physical and emotional conditions at that time.

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