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   Artificial Intelligence

A. Dharanipriya and T. Suganya

1Scholar, 2Scholar

Information Technology Department, Sri Krishna Arts and Science College, Coimbatore, India.

Abstract: AI means Artificial Intelligence. Intelligence” however cannot be defined but AI can be described as branch of computer science dealing with the simulation of machine exhibiting intelligent behaviour. It is the science and engineering of making intelligent machines, especially intelligent computer programs.Artificial intelligence involves two basic ideas. First, it involves studying the thought processes of human beings. Second, it deals with representing those processes via machines (like computers, robots, etc.).One of the main benefits of speech recognition system is that it lets user do other works simultaneously. The user can concentrate on observation and manual operations, and still control the machinery by voice input commands.

Keywords: AI Machines, Parallelism,Artificial intelligence, Eliza, AI Specialization.


The early computers dealt with numeric computations. The current computers are involved in reasoning with the knowledge in addition to numerical computations. With the artificial intelligence (AI) the role of computers changes from something useful to something essential. The aim of artificial intelligence is in some way to try to make computers perform tasks that humans tends to be good at. It is an investigation into the attempt to make computers behave in a smarter manner. The actual name Artificial Intelligence was coined by “John McCarthy” in the 60s and he was also the designer of the language LISP. Artificial Intelligence fills the gap between the scientists of human behaviour and human scientists. In fact, one thing that AI has quite firmly established is that human beings are more complex than some rather naïve analyses have suggested. Predictions that human-like AI are soon to be built are often just media sensationalism and have far provided wrong.

    Logical approach with approximate numeric answers in philosophy and, also in practice, is associated with the level of appreciation of actor (who works). In psychology, intelligence involves learning adaptation and self-organization in response to known or unknown situations or stimuli. The response to a learnt situation, displays the sign of intelligence for humans as well as animals. These concepts in philosophy and psychology corresponded to human beings, but not to machine, the inanimate entity, which still an open problem. Artificial intelligence is not only the science of computation but also the logic of cognition.


The idea of actually trying to build a machine to perform useful reasoning may have begun with Ramon lull (c.1300CE). The first known calculating machine was built around 1623 by scientist Wilhelm Schickard. Gottfried Leibniz then built a crude variant, to perform operations on concepts rather than numbers .The first work that is now generally recognized as artificial intelligence was McCullough and pitts’  1943 formal design for truing-complete “artificial neurons”.[1]

 Fig 1. Related fields of AI.

Throughout the human history, people have used technology to model themselves. Each new technology has, in its turn, been exploited to build intelligent agents or models of mind. Hobbes (1588- 1679), who has been described by Haugeland(1985),p.85 as the “Grandfather of AI”, espoused the position that thinking was symbolic reason like talking out loud or working out an answer with pen and paper .Once real computers were built, some of the first applications of computers were AI programs .During the 1970s and 1980s, there was a large body of work on expert systems, where the aim was to capture the knowledge of an expert in some domain so that a computer could carry out expert tasks. The 1970s and 1980s were also a period when AI reasoning became widespread in languages such as prolog [Colmerauer and Roussel (1996)] [Kowalski (1988)]. [2]


Artificial intelligence is the science and engineering of making intelligent machines, especially intelligent computer programs. It is related to the similar task of using computers to understand human intelligence, but AI does not have to confine itself to methods that are biologically observable.


There are three different headings under which one studies AI hardware. They are

• Language based machines

• Knowledge based machines

• Intelligent interface machines


A. Language based machines:

Language based machines are designed with a particular AI programming language in mind. A LISP or PROLOG machine implements the primitive functions of the language directly in the microcode.

B. LISP machines:

A LISP language is a collection of functions that call each other. The basic data structure of LISP is a list. Lists are represented as a series of linked lists. All data that LISP manipulates are stored as lists and a major chunk of LISP execution time is spent in traversing the pointers. One major characteristic of LISP language is its garbage collection facility.

C. PROLOG Machines:

A PROLOG program is a collection of clauses having Horn Clause representation. PROLOG performs interface process by unification technique. The specialty of PROLOG language is its parallelism. There are two major kinds of parallelism in PROLOG. They are:

• AND parallelism

• OR parallelism

Some of the important PROLOG machines are Parallel Inference Machines (PIM), Parallel Inference Engine (PIE), Programmed Logic Machine (PLM) and the Tamura machine.


To ensure knowledge in knowledge base, various formalisms like logic, production rules, semantic nets, frames etc., exist. The reasoning mechanism for logic is resolution; for production rules, either forward chaining or backward chaining; for semantic nets, by propagation through the net; and in frames, by procedural attachment.


The external interface of Japanese FGCS talks about intelligent I/O interfaces. These interfaces bridge the gap between the humans and the machines. Intelligent I/O interfaces play a pivotal role in computer vision, speech recognition and image processing. We have advanced from Small Scale Integration (SSI) to Medium Scale Integration (MSI), then to Large Scale Integration (LSI), then to Very Large Scale Integration (VLSI) and now are in the brink of Ultra Large Scale Integration (ULSI).[3]


McCarthy is one of the founders of AI, he defines intelligence as the computations; part of ability to achieve goals in the world. Different people think of AI differently and there is no unique definition.

• The first view  is that AI is about duplicating what the (human) brain DOES(Cognitive science)

• The second view is that AI is about duplicating what the (human) brain SHOULD do, that is doing things logically or relationally.

• Turing test: A system is said to be passed Turing test if a human questioner is unable to determine from repeated questions of any kind, whether he or she is not talking to another person or to a machine system.

ELIZA: The very first so-called intelligent system named ELIZA passed the Turing test which was written by Joseph Weizenbaum during the period from 1964 to 1966. This program created breakthrough at that time and researchers started aiming very high of making human-like machines.

    Eliza was a program that conversed with user in English. People were amazed to see this program. The program was able to converse about any subject, because it stored subject information in data banks. Another feature of Eliza was ability to pick up speech patterns from users questions and provide responses using those patterns. The following passage contains dialogue between Eliza and a teenage girl. The system initiates the conversation marked as > and user’s responses are marked as *.

Passage of Eliza conversation:

>hello. I am Eliza.

*Can you help me?

>don’t you believe that I can help you?


>I see

*I feel depressed.

>how long have you been feeling depressed?

*since last month.

>That is quite interesting.

*What is interesting in this?

>Have you asked anyone else?


>Are you saying no just to be negative?

*No I didn’t ask anyone.

>Why no?

*I didn’t believe other person.

>Say, do you have any psychological problems?

*I don’t know.

>tell me more.

Since then lot many versions of Eliza have been developed and are available on the internet. The basic philosophy and characteristics of the program are same [6].


Artificial Intelligence has applications in every field of human endeavor. It combines precision and computational power with pure logic, to solve problems and reduce error in operation. Already, robot expert systems are taking over many jobs in industries that are dangerous for or beyond human ability [4]. some of the applications of AI are

1. Problem Solving.

2. Game Playing.

3. Theorem Proving.

4. Natural language processing and understanding

5. Perception General Speech Reorganization Pattern Reorganization

6. Image Processing

7. Expert System

8. Computer Vision

9. Robotics

10. Intelligent Computer Assisted Instruction

11. Automatic programming

12. Planning and Decision Support systems

13. Engineering Design and Comical Analysis

14. Neural Architecture.

15. Heuristic Classification.[5]


By breaking up AI research into more specific problems, such as computer vision, speech recognition and automatic planning, which more clearly definable goals, scientists managed to create a critical mass of work aimed at solving these individual problems.

Some of the fields where technology has matured and enabled practical applications, are:

• Lollypop

• Skynet

• Speech recognition systems

• Computer vision

• Text Analysis

• Robot control

• Planning

 2015 was a big year. Artificial Intelligence is moving into the commercial world. AI has been worked on for many years, largely in research. Various aspects of commercial use of AI , otherwise known as machine learning, is used for advertising and web searches and things like that. It wasn’t until the last few years that AI could do things that people can’t do. Several milestones were achieved in 2015 in particular that made it possible for us to use in all kinds of areas.


Artificial Intelligence includes the following areas of specialization.

• Games playing: programming computers to play games against human opponents.

• Expert systems: programming computers to make decisions in real-life situations (for example some expert system help doctors diagnose disease based on symptoms).

• Natural language: programming computers to understand natural human languages.

• Neural networks: System that simulate intelligence by attempting to reproduce the types of physical connections that occur in animal brains.

• Robotics: programming computers to see and hear and react to other sensory stimuli.


AI is at the center of a new enterprise to build computational models of intelligence. The main assumption is that intelligence (human or otherwise) can be represented in terms of symbol structures and symbolic operations which can be programmed in a digital computer. There is much debate as to whether such an appropriately programmed computer would be a mind, or would merely simulate one, but AI researchers need not wait for the conclusion to that debate, nor for the hypothetical computer that could model all of human intelligence. Aspects of intelligent behavior, such as solving problems, making inferences, learning, and understanding language, have already been coded as computer programs, and within very limited domains, such as identifying diseases of soybean plants, AI programs can outperform human experts. Now the great challenge of AI is to find ways of representing the commonsense knowledge and experience that enable people to carry out everyday activities such as holding a wide-ranging conversation, or finding their way along a busy street. Conventional digital computers may be capable of running such programs, or we may need to develop new machines that can support the complexity of human thought.

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