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I selected this AI as my research topic. Because am sure that the total world is being ruled by artificial intelligence only. So that I would like to tell its discoveries and discuss its impact on the present day world and how it became a living thing among the people and how it involves in people's daily activities.
Based on my searching, I will discuss Intelligence, types of intelligence, Artificial Intelligence, different fields in which Artificial Intelligence takes place, and its inventions and innovations. It also shows that the application areas of Artificial Intelligence and what methods and strategies are use in projects of Artificial intelligence like face recognition and so on.
In this chapter I define intelligence, types of intelligence, artificial intelligence and history of artificial intelligence and goals of artificial intelligence.
Alfred Binet, opines that Intelligence is " The aggregate or global capacity of the individual to act purposefully, to think rationally, and to deal effectively with his environment."
Intelligence is the mind related abilities, such as understanding, learning, and mental ability, communication, reasoning, abstract thought and learning from past experiences and applies the past to the present and present to the future, planning about future and problem solving. Intelligence is widely studied in humans as well as animals and plants.
TYPES OF INTELLIGENCE
Before going to describe artificial intelligence I discussed clearly about various types of intelligence for getting clear idea about intelligence.
Naturalist Intelligence ("Nature Smart")
This intelligence indicates the human ability to separate among living things such as plants and animals. This intelligence was clearly relating to past as hunters, gathers, and farmers.
Musical Intelligence ("Musical Smart")
This musical intelligence recognize pitch, rhythm, timbre, and tone. It modifies us to recognize, to create, to reproduce, and reflect on music as presented by composers, musicians and vocalist and sensitive listeners.
Logical-Mathematical Intelligence (Number/Reasoning Smart)
Logical-mathematical is the power to calculate , measure, consider (logic) a statement that affirms or denies something and is either true or false, and hypotheses, and go through complete mathematical operations. Generally this ability is used for developing mathematics, scientists, and detectives.
Existential Intelligence has the ability to responsiveness to emotional feelings (of oneself and others) and has the mental ability to tackle deep questions about human existence, such as the meaning of life, why do we die, and how did we get here.
Interpersonal Intelligence (People Smart")
This is the people smart ability. It guides us how to understand the people or things and how effectively interact with others. It closely connect with verbal and nonverbal communication, It has distinguishing quality of how to note distinctions among others, the ability to respond to affective changes in your interpersonal environment. Young adults has this kind of intelligence and with this intelligence they would become as leaders among their peers, are good at communicating, and seems to understand other's feelings and motives.
6. Bodily-Kinesthetic Intelligence ("Body Smart")
This ability is known as Body Smart ability. Bodily-Kinesthetic intelligence is the capacity to influence or change objects and the
Bodily kinesthetic intelligence is the capacity to manipulate objects and use a variety of physical skills. This intelligence also involves a sense of timing and the flawlessness of skills through mind-body union. Bodily kinesthetic intelligence are Athletes, dancers, surgeons, and craftspeople exhibit. Those are well-developed bodily kinesthetic intelligence persons.
7. Linguistic Intelligence (Word Smart)
This is one of the important intelligences. Linguistic Intelligence is the ability or power to think in word or words and to think how to express feelings of emotions, happiness through language and be fully aware of complex meanings. Linguistic Intelligence make it possible to apply meta-linguistic skills to reflect on our use of language. It made us to understand the order and meaning or words. Poets, novelists, journalists and effective public speakers and orators has linguistic Intelligence or word build intelligence. With this intelligence adults enjoy reading, writing, telling fictional and non -fictional stories or doing crossword puzzles.
8. Intra-personal Intelligence (Self Smart")
Intra-personal Intelligence is the self smart intelligence. It is the capacity to understand reflex form of one (oneself), and one's thoughts and feelings, ideas, and to use this knowledge in proper planning and directioning one's life. This intelligence involves an appreciation of the self as well as in human condition. Generally psychologist, spiritual leaders and philosophers belongs to intra-personal intelligence.
9. Spatial Intelligence ("Picture Smart")
Spatial intelligence is the Picture Smart intelligence. It thinks in three dimensions.
The first one is core capacities include mental imagery, spatial reasoning and the second one is image manipulation, graphic and artistic skills and the last one is an active imagination. Sailors, pilots, sculptors and painters are comes towards spatial intelligence.
Artificial intelligence is a human attempt and it describes the intelligence of machines or the representation of something and model of intelligence in machines. Artificial Intelligence is one of the branches of computer science. AI aims is to create something. Artificial Intelligence has been subject of optimism, but also endured setbacks.(1) Today, the technology takes an crucial part in industry and bringing up for many of the most difficult problems in computer science.(2)
Artificial Intelligence is highly technological and differentiated and it is divided into subfields. But these subfields fail to interchange information or idea with each other.(3) These subfields have formed up just about particular institutions. With the work of individual researchers with longstanding different opines could not slove the solutions of specific problems. Then AI should be done with AI application with differing tools. The central problems of AI such attributes as reasoning, knowledge, planning, learning,communication,perceptual experience and the ability to go and control objects. (4) Strong Artificial intelligence or General Inteligence is still among the field's long term goals.(5)
HSTORY OF ARTIFICIAL INTELLIGENCE :
Artificial beings had been created by the 19th and 20th centuries. Artificial Intelligence research was found at a conference on the campus of Dartmouth College in the summer of 1956.(6) John Mc Carthy, Marvin Minsky, Allen Newell and Herbert Simmon were the leaders of AI research. (7) They and their students composed programs that were,computers were solving word problems in algebra and speaking english. These were simply amazing: (8) U.S AI research was furnished with funds by the Department of Defence(9) in the middle of the year 1960. Laboratories had been installed around the world. (10)Founders of AI were deeply hopeful about the future of new world. (11)Herbert Simon predicted that "machines will be capable, within twenty years, of doing any work a man can do" and Marvin Minsky agreed, writing that "within a generation ... the problem of creating 'artificial intelligence' will substantially be solved".(12)
But till 1974, they failed to recognize some of the problems what they have faced. After that in the early 1980's AI research was recreated by the commercial success of expert systems(13) that reproduced the knowledge and analytical skills of one or more than one human experts. AI research was attained over a billion dollars in the year of 1985. Meanwhile, The U.S was motivated by Japan's fifth generation computer project and British governments to regenerate financial back up for academic in the field.(14) Nevertheless, in 1987 once again AI discredited with the break down of Lisp Machine market. Even though somewhat behind the scenes AI ultimately achieved its biggest success in the 1990s and early 21st century. Presently Artificial Intelligence is applied for logistics, data mining, medical diagnosis and many other areas throughout the end to end technology industry. (15)Due to this success a profound results came in AI: the increasing computational power of computers, a greater vehemence on solving specific sub problems, the creation of new affiliations between AI and other fields working on interchangeable problems, and a new allegiance researchers to upstanding mathematical methods strict scientific standards.(16)
TYPES OF ARTIFICIAL INTELLIGENCE
Following the present technology, artificial intelligence is broken down into two groups, strong artificial intelligence and weak artificial intelligence.(Bethell,2006).
Weak Artificial Intelligence
Weak A.I. denotes to technology. This intelligence is able to influence or control set in advance rules and apply the rules to reach a well-defined goal (Bethell, 2006)(17) Weak artificial intelligence is presently merged into society, mainly in large industries. For example, assembly lines. Assembly lines utilize programs that permit machines to work without depending on their operator for hours on end (Bethell, 2006).(18) The prominent part of artificial intelligence is considered by Voice recognition software.
Weak artificial intelligence has bright and very exciting future. This intelligence holds the exponential growth of computing power at hand. So that scientists believe that weak A.I. discoveries are there in the near future. Super -computers are one of the examples. These super computers will be furnished with so much power, this power will be able to be used as "Expert Systems". It will be able to use a database of expert or skill full knowledge to solve everyday problems(Boden,1990). (19)
The most inspirational technologies are projected to come forth from the development of weak artificial intelligence are three revolutions, robotic, genetic and nanotechnological revolutions are connected together. If once the human body is decoded, by way of the revolution in genetics, robots will be able to be reconstructed which will serve to treat the several misfunctions of the human body. If once this achieved, the hope is that a nanotechnology revolution will take place in which the robots that treat disease will be able to actually be merged into our bodies, function without external control and fix out misfunctions.(Kurzweli,2006).(20) If there is one question arises that this technology truly intelligent? it is unanswerable but this technology has foreboding future.
Strong Artificial Intelligence
The second type of artificial intelligence is Strong Artificial Intelligence. It also denotes to technology like weak artificial intelligence. It has the ability to think how the action or process of acquiring knowledge and understanding through thought, experience or the senses or it is able to function in a similar way like to the human brain(Bethell,2006).
But some people opines that this technology will never be achieved because it is the longest section and part of geological time. But there is some hope to emerged into the weak technological revolution of nanotechnology. The hope is that
These nanobodies will never be able to help our bodies fight disease as well as to make our bodies more intelligent (Kurzweil,2006). The Another hope is to engineer an artificial neural network capable of operating that is comparable to a human brain. Strong artificial intelligence is still only in impregnable state.
GOALS OF ARTIFICIAL INTELLIGENCE
Develop understanding thinking and make computer perform works that need intelligence if performed by people. But perspectively, artificial intelligence can be viewed as two parts of goals engineering goal and scientific goal.
The engineering goal of Artificial Intelligence
This intelligence goal is to solve real-world problems with using Artificial Intelligence as an collection of ideas about representing knowledge, using knowledge, and foregathering systems.
The scientific goal goal of artificial intelligence
This artificial Intelligence goal is to find out which ideas about representing knowledge, using knowledge, and foregathering systems explicate various kinds of intelligence.
To define the artificial intelligence there are many ways. Here is one: Artificial Intelligence is the study of the procedure of calculating, determining something by mathematical or logical methods that make it possible to comprehend, reason, and act. By the regarding of this definition, artificial intelligence differs from most of psychology because of the greater vehemence on calculation, computation, and artificial intelligence deffers from most of computer science because of the emphasis on perception, reasoning and action.
In this chapter I explain how the Artificial Intelligence uses in different fields of applications and how many types of applications are there in artificial intelligence.
APPLICATIONS OF ARTIFICIAL INTELLIGENCE
Artificial Intelligence has been used in various fields including medical diagnosis, stock trading , robot control, law, scientific discovery and toys, finance, telecommunications, games, music, aviation, computer science. Many thousands of AI applications are deeply wrapped in the infrastructure of every industry. Many artificial intelligence applications are not comprehended as AI. It has filtered from numerous applications into general applications. These applications becomes useful enough common enough it's not marked or judged AI anymore.(21) Many thousands of applications are enclosed firmly in the infrastructure of every industry.(22)From the late 1990's and early 21st century, Artificial Intelligence became world widely used as factors or components of large systems, (23).
LIST OF APPLICATIONS
Artificial Intelligence (AI) and Finance
Finance is one of the major applications of artificial intelligence. This applications are used by the banks. For organizing operations, to invest in stocks, and manage properties banks use this artificial intelligence systems.
AI has world wide e and significant application in finance . It can help users source the best financial options, allowing them to manage their money more expeditiously (25)Equipped with details of present financial products such as interest rates of savings accounts or mortgages (security interest) or loans, agents will be able to identify the products that best meet a user's requirements. It helps in overworking data so that smarter business decisions can be made in less time and/or at lower cost.
Artificial Intelligence (AI) and Medicine
This is the second application of artificial intelligence. To organize bed schedules, to make staff rotation, and provide medical information medical clinic can be used artificial intelligence systems.
Potential of AI in medicine has been expressed by a number of researchers. Hoong (1988)(26) summarized the potential of AI techniques in medicine as follows:
Artificial Intelligence in medicine provides a laboratory for the examination, organization, representation and cataloguing of medical knowledge.
He says that AI in medical produces new tools to support medical decision-making, training . Medicine integrates activities in medical, computer, cognitive and other sciences. AI in medicine Offers a content-rich discipline for future scientific medical specialty.
Early studies in intelligent medical system are MYCIN, CASNET, PIP.
Artificial Intelligence (HEAVY INDUSTRY)
Robots are the best example of heavy industrial applications and it is common in many industries. Robots often offers number of jobs but working with robots are dangerous to humans. Robots have proven effective in jobs that are very repetitive which may lead to mistakes or accidents due to a lapse in concentration and other job which humans may find degrading. Japan takes first place producing and using robots in the world.
Artificial Intelligence (Telecommunications)
Telecommunication term has vast range in present technologies. It is huge rage technologies that send over distances. Radio, television and networks are a few more examples of telecommunication Mobile phones, land lines, satellite phones and voice over Internet protocol (VoIP) are all telephony technologies -- just one field.
Many communication, telecommunication companies are there around the world. But most of the companies make use of heuristicsearch in the management of their workforces, BT group is the finest example has distributed heuristicsearch in a scheduling application that provides the work schedules.
Artificial Intelligence ( Toys and Games)
This intelligence is used in computer and video games to create the illusion of intelligence in the behaviour of non-player characters (NPCs). Game artificial Intelligence is often used to refer to a broad set of algorithms that also include techniques from control theory, robotics, computer graphics and computer science in general.
Game artificial intelligence is centred on appearance of intelligence and good gameplay. Its approach is very different from that of traditional AI: cuts up and cheats are acceptable and, in many cases the computer abilities must be toned down to give human players a sense of fairness. This, for example, is true in first-person shooter games, where NPC's otherwise prefer aiming would be beyond human skill.
Artificial Intelligence (Music)
Music is the arrangement of sound in a pleasing sequence or combination to be sung or played on in instruments. This music has been greatly affected by technology.
With Artificial Intelligence, scientists are attempting to make the computer to imitate the activities of the skill full musician. Research in Music and Artificial Intelligence are focusing some of the major areas of composition, performance,music theory,sound processing.
Smart Music is an interactive, computer-based practice tool for musicians. Smart Music is a great practice partner. It does challenging exercises, instant feedback tools.It designed to help the teacher and students alike. This program backups 5 categories : Solo, Skill development, Method books, Jazz, ensemble. Students can choose the difficulty level they want to play at, they can slow down or speed up the tempo or even change the key in which to play the piece.] Computer-aided music instruction isn't new; programs like Band in a Box and Music Minus One also provide accompaniment. But SmartMusic compares students' playing with a digital template, which lets it detect mistakes and mark them on a score. It also simulates the rapport between musicians by sensing and reacting to tempo changes.
AI can be used in music in many different ways, it can be used both to compose (create music) and transpose (create written music from listening to pieces). Getting computers to compose well is an fabulously hard task. Computers find it hard to merely listen to a pieces and "feel" whether it is beautiful, or nothing more than cacophony. Computers that compose often require human input to determine whether the music sounds not.
Different tools of artificial intelligence are also being widely distributed or spread in homeland security, speech and text recognition, data mining, and e-mail spam filtering. Applications are also being developed for gesticulate recognition (understanding of sign language by machines), individual voice recognition ( global voice recognition (from a variety of people in a noisy room), facial expression recognition for interpretation of emotion and non verbal queues. Robot navigation, obstacle avoidance, object recognition are other applications.
This chapter shows an over view of Artificial Intelligence major applications of computer vision and expert system.
Artificial Intelligence in Computer vision
Computer Vision has influenced in the field of Artificial intelligence greatly. It is a diverse and relatively new field of study.
Computer Vision is the science and technology of machines. In these technology machine is able to extract information from an image that is necessary to solve some task. CV is concerned with
the theory behind artificial systems that extract information from images. The images of data can be in many forms such as video sequences, views from multiple cameras, or multi dimensional data from a medical scanner.
Computer Vision looks for to apply its theories and models to the construction of computer vision systems. Controlling process (e.g., an industrial robot or an autonomous vehicle), organizing information(e.g., for indexing databases of images and image sequences), modelling objects or environments (e.g., industrial inspection, medical image analysis or topographical modelling),detecting events (e.g., for people counting), interaction (e.g., as the input to a device for computer-human interaction) are the examples of applications of computer vision systems and it is closely related to the study of biological vision. CV is seen as a part of the AI field of the computer science field in general. AI and CV share other topics such as pattern recognition and learning techniques.
AI deals with autonomous planning or deliberation for robotical systems to navigate through an environment. In detail these environments are required to navigate through them. But required information about environment could be provided by a computer vision system. Acting as a vision sensor its provide high-level information about the environment and the robot.
Physics is another field that is closely related to computer vision. Computer vision systems rely on image sensors which detect electromagnetic radiation which is typically in the form of either visible or infra-red lights.
Signal processing is another field related to computer vision. While i was searching I found that many methods for processing of one-variable signals, typically temporal signals, can be extended in a natural way to processing of two-variable signals or multi-variable signals in computer vision
The above mentioned views on computer vision, many of the rlated research topics and many methods are studied from mathematical point of view and this vision based on statistics, optimization or geometry.
Computer Vision closely related fields are image processing, image analysis and machine vision.
Applications for computer vision
The most eminent application fields in computer vision are medical computer vision or medical image processing and computer vision industry or machine vision and military applications. And autonomous vehicles.
The first application fields of medical image processing extracts the information from image data for making a medical diagnosis of a patient. Generally, image data is in the form of microcopy images, X-ray images, angiography images, ultrasonic images and tomography images.
A second application area in computer vision is in industry or machine vision also extracts information for the purpose of supporting a manufacturing process. One example of this application is quality control where details or final products are being automatically inspected in order to find defects. This vision is also used in agricultural process to remove undesirable food stuff form bulk material, a process called optical sorting.
.Military applications are one of the greatest areas of computer vision. Detection of enemy soldiers or vehicles and missile guidance are the examples of these application.
Autonomous vehicles, which include submersibles, land-based vehicles (small robots with wheels, cars or trucks), aerial vehicles, and unmanned aerial vehicles are the newer applications areas in computer vision
ARTIFICIAL INTELLIGENCE AND EXPERT SYSTEM
Expert system is one of the major branches of artificial intelligence.
An expert system is an intelligent computer program that uses knowledge and inference procedures to solve problems that are difficult enough to require significant human expertise for their solution. It is concerned with the concepts and methods of symbolic inference, or reasoning, by a computer, and how the knowledge used to make those inferences will be represented inside the machine.
Expert system is one of the major branches of artificial intelligence. An expert system is an intelligent computer program that uses knowledge and inference procedures to solve problems that are difficult enough to require significant human expertise for their solution. It is concerned with the concepts and methods of symbolic inference, or reasoning, by a computer, and how the knowledge used to make those inferences will be represented inside the machine.
Expert systems are fully computer based. This expert system checks the presentation and performance of a human expert deeply than checklists, flow charts, diagrams, sheets and decision tables.(27) Generally these devices are goal oriented. This devices may not compare favorably with live mutual interaction or expert systems when efficiency, adaptively, use of imperfect and indetail information and explanationof reasoning are important.
Characteristics of Expert System
Compute based Expert system should be goal oriented.
It should be efficient. It means being effective without wasting time, effort or expense
Having a capacity for adaptation.
It should be the ability to work with imperfect information.
Expert System should justify its requirements, recommendations by explaining their reasoning.
Building Blocks for Expert System
Expert System consists of knowledge base, Inference Engine and User Interface. Each component play important role in functioning of Expert System. Stored knowledge is used with rules to derive inference about the problem [28, 30].
Components of expert system
Knowledge Base System (KBS)
This is one of the major components of expert systems. The most important ingredient of any expert system is knowledge
An Expert (Knowledge Based) System is a problem solving and decision making system based on knowledge of it's task and logical rules or procedures for using knowledge. It stores all relevant information, data, rules, case, and relationships used by the expert system.
The knowledge base expert system contains both factual and heuristic knowledge. Factual knowledge is that knowledge of the task domain that is widely shared, typically found in textbooks or journals, and commonly agreed upon by those knowledgeable in the particular field.Heuristic knowledge is the less in-depth, more experiential, more judgmental knowledge of performance.
This is the major component of expert system. Reasoning engine is a conclusion reached on the basis of knowledge or facts mechanisms simply known as Inference mechanisms for controlling the symbolic information and knowledge in the knowledge base to form a line of reasoning in solving a problem. This mechanism follows from simple backward chaining of IF-THEN rules to case-based reasoning.
Figur1: Structure of Expert System 
This flow chart shows us Structure of Expert System. Expert system is one of the parts in Expert System shell. Expert system has subsystems in this chart. The first one is knowledge acquisition subsystem.
Knowledge acquisition subsystem
Knowledge acquisition subsystem is a subsystem in expert system. This subsystem helps experts to build knowledge with knowledge bases. Collecting knowledge is needed to solve problems and build the knowledge base continues to be the biggest checkpoint in building expert systems.
Explanation subsystem is one of the subsystems in expert systems. This subsystem describes the system's actions. The explanation subsystem can grade from how the final or intermediate solutions were arrived at to justifying the need for additional data.
User interface means in general is computing a program that controls a display for the user (usually on a computer monitor) and that allows the user to interact with the system. This is one of the subsystems in expert system. In this system it means of communication with the user. User interface is a means of communication with the user. Generally it is not a part of the Expert System technology. And it was not given much attention in the past. It is now widely accepted that the user interface can make a vital difference in the perceived utility of a system without regard to drawbacks of the systems.
Expert System Algorithm
Algorithm is a precise rule (or set of rules) specifying how to solve some problem. Expert system follows two algorithms to come from inference about particular problem. These are forward chaining method and backward chaining method.
31. Negnevitsky M. Artificial Intelligence. A Guide to Intelligent Systems, Addison Wesley, Second Edition, 2005
Forward Chaining method starts with set of known facts or attributes and applies these values to rules that use them in their premise. Any rules that are examines true attack and produce additional facts that are again applied to germane rules. This process continues until no new facts are produced or a value for the goal is incurred. This move towards works well when it is natural to gather multiple facts before trying to draw off any conclusions and when there are many possible conclusions to be drawn from the facts.
An alternative approach or Backward chaining method starts with a rule. This rule could reach a conclusion after a discussion or deliberation, the goal for the consultation, tries to obtain values for the attributes used in the rule's premise, then holdsback through additional rules if necessary to decide a value of the goal attribute. The backward chaining mechanism produces a more efficient interview than forward chaining when there are many attributes applied in many rules for the reason that it will not be requisite to ask the user to input values of all of the facts. We will be using Backward Chaining Algorithm in project also.
These chaining systems are described as hypothesis driven because they operate by selecting successive rules that can determine the value of a goal or sub-goal. This value becomes the hypothesis to be proven or disproved. Figure 2 show the working of Backward Chaining algorithm .Once an attribute is identified inference engine puts aside the rule it is working with and sets up a new goal and sub-goal to prove the If part of this rule. Then knowledge base is searched again for the rules that can prove the sub-goal. The inference engine repeats the process of stacking the rule until no rules are found in the knowledge base to prove the current goal.
Working of Backward Chaining 
problems and Limitations of Expert Systems
Each and every system has some problems and limitations. Knowledge is not always readily available, just it comes one source of knowledge is experience and expertise can be hard to extract from humans. Each and every expert's approach may be different. Though there approaches are different they may be correct and expert systems users have natural action process of acquiring knowledge and understanding through thought and experience or the senses limits. Expert system works well only in a narrow field of knowledge are the problems and limitations of expert system.
Advantages of expert system
Many applications are there in the artificial intelligence expert systems. But Expert systems computer based applications are more affective than other computer based applications. Because they merge the knowledge of many experts in a particular field, ad can store an inexhaustiable amount of information, and its work much faster, than a human are available twenty four hours a day, and can be used at distance over a network. It has the ability to explain their information requests applications and suggestion. AI expert system can process client's uncertain responses and, by combining various pieces of uncertain information, may still be able to make substantial recommendations. The expert system can conglomerate knowledge of high level employees for any company, which is useful when the company needs to fire them due to worsened market conditions.
Artificial Intelligence expert system reduced decision making time and increased processes and the quality of product. It also tries to decreased downtime captivate hardly expertise. The quality of flexibility, easier operation, the act of removing an unknown mathematical quantity by combining equations, elimination of expensive equipment are the benefits of artificial intelligence expert system.
Speech recognition is known as automatic speech recognition or computer speech recognition.
Speech recognition converts words into text. The term "voice recognition" is sometimes used to refer to recognition systems that must be trained to a particular speaker .
There are two uses for speech recognition systems:
Dictation-The first use is it can translate the spoken word or words into written text.
The second use of CC is by speaking commands it can control of the computer, and software applications.
UNDERSTANDING NATURAL LANGUAGE
Just giving input with a sequence of words into a computer and arranging sentences in order is not enough. The computer should be understand what the user has given and it could provide understanding output to the users. Presently understanding natural language in all domains of computer. Systematic computers never raised this problems.
This chapter explains advantages and disadvantages of artificial intelligence.
Advantages of Artificial Intelligence
Artificial Intelligence has the quality of having a superior or more favourable position. AI has more advantages than disadvantages. Machines in artificial intelligence can be used to take on simple, compound and complex stressful work that would be performed by humans. Machines can complete any difficult or easy easy tasks faster than human assigned to the same work. It will be useful in our home activities. This Intelligence technology tries to discover unexplored landscape by using robotics.
AI machines causes less danger and injury,stress to humans while working with using of machines. The work will be completed with in seconds by the machines. Aiding of mental ,visually and hearing impaired individuals.
While playing games with machines it doesn't getting us bore, it creates challenging atmosphere among the players. Just we would got forget the machine and playing and using machine as a human being.
Understanding complex software makes easy to understand and types with the aid of artificial intelligence. It gives less errors in output actually this errors shall be began by the users only and has less defects.
It saves ours valuable time minimize resources. Time and goal effectively used achieve the end of the goal time never be wasted. Their functions are infinite.
Artificial Intelligence never be "interrupted sleep" It does not Intermittently stopping and starting its tasks . It does not cause to suffer a blight That biological minds like restroom breaks and eating. This is the main advantage of artificial intelligence.
Though an artificial mind could theoretically have emotions, it would be better for performance. Because of unemotional consideration of problems. Sometimes people takes decisions based on emotion rather than logic but it is not the best way to take decisions.
The most useful advantage of artificial intelligence is easier copying. If once artificial mind is trained in any difficult task, that mind can then be copied easily. Compared to the training of multiple people for the same work.
Disadvantages of Artificial Intelligence
Artificial Intelligence has advantages as well as disadvantages.
Machines are involved in our daily activities. For each and every work we depends on machines for example coffee to dinner. Then automatically it lacks the human touch. Sometimes human qualities are disregarded.
People feel and fear that it creates unemployement. Because it has the ability to replace a human job. This gives rise to humans feeling insecure and may have the fear of losing their job.
Human capabilities are reduced with using of machines and their places will be replaced by the machines so that foster feelings of inferiority comes among the workers and staff.
Artificial Intelligence can misfunction and do the opposite of what they are programmed to do.
Younger generation may corrupt. This type of technology may be misused to cause mass scale destruction. One more advantage is there is no filtering of information. Machines does not have the sense of what is good and bad, which is preferable or not and it does not have any feelings of emotions or happies but it works alot. In the present world a man can live without having anything but he does not live without using machines. His total life and total world depends on the machines only.
malfunction and do the opposite of what they are programmed to do
This type of technology can be misused to cause mass scale destruction
In this chapter, I conclude about artificial intelligence and tells advanced use of artificial intelligence.
The term Artificial Intelligence was coined since its 55 years, then how advance AI will be in 2050 and 2100? The foremost research thinkers and scientists and mathematicians expects advantage stages of AI by 2050 or 2100.
Hugh Loebner, inventors opines that " That's hard to say. [Mathematician and scientist Alan]Turing, I believe, thought his test would be passed by 2050. I suppose that by 2100 we'll have human equivalent or superior machines. 2050? That's the Singularity(the point when machine intelligence outpaces that of humans).
In his book The Singularity is Near, he says that calculation is raising at a doubly exponential rate and he assumed that in the present days computers are billions of times more powerful per dollar than when he was an undergraduate and opines that we shall do that again in 25 years. The software is acquiring worldliness and we are well on our way to entirely backward-engineering(reverse-engineering) the human brain within 20 years.
It follows an exponential function of advancement. We shall have gotten fully human-level(turning-test capable)Artificial Intelligence by 2029. These human-level capabilities will immix with the ways that machines are already superior in terms of sharing knowledge at speeds that are a million times faster than human language, and other advantages. We will conflate with this intelligent technology and enhance the appearance of a hybrid of biological and nonbiological intelligence, exclude that the nonbiological assign of our intelligence will continue to elaborate exponentially. So automatically our brain will elaborate their capacity a billion -fold by 2045 through this merger and ongoing exponential advance of information technology.
The expansion will be trillions of trillions-fold and we will start to elaborate on the outside solar system by 2100.
Eric Horvitz, president of the Association for the Advancement of Artificial Intelligence says that a great deal work on computer based building systems that work in a complementary
This is hard to predict right now but I'll mention one area. I foresee a great deal of work on building systems that work towards complimentary way with people, computing system compliments human skills tremendous development of advanced systems that work closely with people in a complementary manner to assist them with their goals.
Another advanced artificial intelligence is qutonomou0s cars. Noel Sharkey, professor of AI and robotics opines that it is not easy to tell whhere artificial intelligence will be in 40 years' or 50 years' time really difficult. In future a lot of autonomous operations will come in robots.
It's very difficult to tell where AI will be in 40 years' or 50 years' time - really difficult... I expect to see a lot of autonomous operation in robots. In future we can see that robots will work as receptionists and works towards medicine also.
He says that " I would hope that in 50 years' time you'd be able to get your appendis removed by machine and also it means you could take a machine down the motorway and have it operate on people rather than rush them to hospital and have them die on the way, which is one of the common things, so those areas I think will be very big. bigBut it depends on what society does and whether we go the technological route, so I couldn't possibly give a prediction that I would think would be true"
The "setbacks" referred to include the ALPAC report of 1966, the abandonment of perceptrons in 1970, the Lighthill Report of 1973 and the collapse of the lisp machine market in 1987.
^ a b AI applications widely used behind the scenes:
Russell & Norvig 2003, p.Â 28
Kurzweil 2005, p.Â 265
NRC 1999, pp.Â 216-222
Pamela McCorduck (2004, pp.Â 424) writes of "the rough shattering of AI in subfields-vision, natural language, decision theory, genetic algorithms, robotics ... and these with own sub-subfield-that would hardly have anything to say to each other."
^ a b This list of intelligent traits is based on the topics covered by the major AI textbooks, including:
Russell & Norvig 2003
Luger & Stubblefield 2004
Poole, Mackworth & Goebel 1998
^ a b General intelligence (strong AI) is discussed in popular introductions to AI:
Kurzweil 1999 and Kurzweil 2005
6. Dartmouth conference:
McCorduck 2004, pp.Â 111-136
Crevier 1993, pp.Â 47-49, who writes "the conference is generally recognized as the official birthdate of the new science."
Russell & Norvig 2003, p.Â 17, who call the conference "the birth of artificial intelligence."
NRC 1999, pp.Â 200-201
7. Hegemony of the Dartmouth conference attendees:
Russell & Norvig 2003, p.Â 17, who write "for the next 20 years the field would be dominated by these people and their students."
McCorduck 2004, pp.Â 129-130
^ Russell and Norvig write "it was astonishing whenever a computer did anything kind of smartish." Russell & Norvig 2003, p.Â 18
^ "Golden years" of AI (successful symbolic reasoning programs 1956-1973):
McCorduck 2004, pp.Â 243-252
Crevier 1993, pp.Â 52-107
Moravec 1988, p.Â 9
Russell & Norvig 2003, pp.Â 18-21
The programs described are Daniel Bobrow's STUDENT, Newell and Simon's Logic Theorist and Terry Winograd's SHRDLU.
^ DARPA pours money into undirected pure research into AI during the 1960s:
McCorduck 2004, pp.Â 131
Crevier 1993, pp.Â 51, 64-65
NRC 1999, pp.Â 204-205
^ AI in England:
^ Optimism of early AI:
Herbert Simon quote: Simon 1965, p.Â 96 quoted in Crevier 1993, p.Â 109.
Marvin Minsky quote: Minsky 1967, p.Â 2 quoted in Crevier 1993, p.Â 109.
a b Expert systems:
ACM 1998, I.2.1,
Russell & Norvig 2003, pp.Â 22âˆ’24
Luger & Stubblefield 2004, pp.Â 227-331,
Nilsson 1998, chpt. 17.4
McCorduck 2004, pp.Â 327-335, 434-435
Crevier 1993, pp.Â 145-62, 197âˆ’203
^ Boom of the 1980s: rise of expert systems, Fifth Generation Project, Alvey, MCC, SCI:
McCorduck 2004, pp.Â 426-441
Crevier 1993, pp.Â 161-162,197-203, 211, 240
Russell & Norvig 2003, p.Â 24
NRC 1999, pp.Â 210-211
^ Second AI winter:
McCorduck 2004, pp.Â 430-435
Crevier 1993, pp.Â 209-210
NRC 1999, pp.Â 214-216
^ a b Formal methods are now preferred ("Victory of the neats"):
Russell & Norvig 2003, pp.Â 25-26
McCorduck 2004, pp.Â 486-487
17,18. Bethell, T. (2006, July/August). The search for artificial intelligence. American Spectator, 39(6), 26-35. Retrieved February 5, 2008, from eLibrary.
19. Boden, M. (1990). The social impact of artificial intelligence. In R. Kurzweil (Ed.), The Age of Intelligent Machines (pp. 450-453) Cambridge, MA: The MIT Press.
20. Kurzweil, R. (2006). Reinventing humanity: The future of machine-human intelligence. The Futurist, 40, 39. Retrieved February 5, 2008, from eLibrary.
20. Russell, Stuart J.; Norvig, Peter (2003), Artificial Intelligence: A Modern Approach (2nd ed.), Upper Saddle River, New Jersey: Prentice Hall, ISBNÂ 0-13-790395-2, http://aima.cs.berkeley.edu/Â
21,23. Kurtzweil, Ray (2005), The singularity is nearÂ : when humans transcend biology, New York: Viking, ISBNÂ 9780670033843Â
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