ARTIFICIAL INTELLIGENCE Abstract: This paper aims at presenting the concept of “Artificial Intelligence. ” It is the branch of Computer Science concerned with making computers behave like humans. It is the Science and Engineering of making intelligent machines, especially intelligent computer programs. It is the hot topic on many boards and software houses. The term was coined in 1956 by John McCarthy at the Massachusetts Institute of Technology. This paper briefly describes how Artificial Intelligence works and the various techniques used in AI.
It further describes, the greatest advances that have occurred in the field of Medicine, Military, Expert Systems, Robotics and Natural Language Processing. This paper deals with latest advances that have occurred in the field of games playing. The best computer chess programs are now capable of beating humans. In May 1997, an IBM super-computer called Deep Blue defeated world chess champion Gary Kasparov in a chess match. Today, the hottest area of Artificial Intelligence is neural networks, which are proving successful in a number of disciplines such as voice recognition and natural language processing.
Robotics incorporating artificial intelligence interaction with laser, ultrasound, MRI scanning, are performing delicate brain surgery more accurately than by traditional surgical approaches. A. I. was used in the investigation of Mars in July 1997. This paper reflects the potential impact of AI on our lives. Artificial Intelligence is likely to continue to creep into our lives without us really noticing. Contents Introduction Why Artificial Intelligence? • Motivation How does Artificial Intelligence work? • Planning • Pattern Recognition • Ontology • Robotics • Artificial Life Epistemology Who uses Artificial Intelligence? • Medicine • Artificial Nose • Military • Game AI • Natural Language Processing • Expert Systems Future of AI Technology • Telephone Translator • A Greater Use of Expert Systems • Passing the Turing Test • Research assistants Artificial Intelligence Introduction: Artificial Intelligence is a branch of Science which deals with helping machines find solutions to complex problems in a more human-like fashion. This generally involves borrowing characteristics from human intelligence, and applying them as algorithm in human friendly way.
It is basically the ability of a machine to think for itself. It aims at getting computers to do tasks which require human intelligence. In short it can be described as: Simple things turn out to be the hardest to automate: *Recognizing a face. *Navigating a busy street. *Understanding what someone says. Why Artificial Intelligence? Motivation… Computers are fundamentally well suited to performing mechanical computations, using fixed programmed rules. This allows artificial machines to perform monotonous tasks efficiently and reliably, which humans are ill – suited to.
For more complex problems, things get more difficult. Unlike humans, computers have trouble understanding specific situations, and adapting to new situations. Artificial Intelligence aims to improve machine behaviour in tackling such complex tasks. How does Artificial Intelligence work? Technology… Over the past five decades, AI research has mostly been focusing on solving specific problems. Numerous solutions have been devised and improved to do so efficiently and reliably. This explains why the field of Artificial Intelligence is split into many branches.
Some of the branches have been explained below: Planning: Planning programs start with general facts about the world (especially facts about the effects of actions), facts about the particular situation and a statement of a goal. From these, they generate a strategy for achieving the goal. In the most common cases, the strategy is just the sequence of actions. Pattern recognition: The main focus in AI today is getting a computer to recognize, make senses and recreate in what it sees and hears. The two major divisions of pattern recognition are machine vision and sound. Pattern-Recognition-Vision:
It’s goal is to get a computer to recognize pictures so that it can recognize objects in its surroundings that would be helpful in robotics. Pattern-Recognition-Sound: It wants to achieve a similar goal but is a primary concern with companies that want to produce a new means in which a person interacts with a computer by talking. Ontology:Ontology is the study of what objects are and what are they made of. It is the study of kinds of things that exist. In AI, the programs and sentences deal with various kinds of objects, and we study what these kinds are and what their basic properties are. Robotics:
Robotics is the study of how to design, build, use, and work with robots. Robots are mechanical devices that can move and react to sensory input giving them some degree of autonomous control. Robots are widely used in the industrial sector performing high-precision jobs such as painting and wielding. They are used in laboratories for repetitive tasks in chemistry and biology, and in situations, which would be dangerous for humans such as cleaning toxic waste or defusing bombs. Three laws of robotics: 1. A robot may not injure or harm a human being or allow a human being to come to harm. 2. 2.
A robot must follow the instructions given to it by a human being without violating Rule 1 3. 3. A robot must protect itself as long as such protection does not violate Rules 1 and 2. Artificial life: Artificial life is a field of scientific study that attempts to model living biological systems through complex algorithms. Scientists use these models to test and experiment with a multitude of factors on the behaviour of the systems. Artificial life: From robot dreams to reality It is a diverse field of research, but a common theme is testing out the fundamental principles of life by building detailed working models.
One of the most ambitious goals of artificial-life research is the construction of living systems out of non-living parts. Artificial life is a blanket term used to refer to human attempts at setting up systems with lifelike properties all biological organisms possess, such as self-reproduction, homeostasis, adaptability, mutational variation, optimization of external states, and so on. Epistemology: Epistemology is a study of knowledge that are required for solving problems in the world. Who uses Artificial Intelligence? Applications… To be useful, a system has to be able to do more than just correctly perform some task. – Johan McDermott Artificial Intelligence is helping people in every field to make better use of information to work harder not smarter. The potential applications of Artificial Intelligence are abundant. However, some of the applications of AI have been listed below: Medicine: NEW BLOOD TEST SPOTS CANCER: In one of the biggest advances in cancer research in years, scientists have developed a blood test that can detect cancer with a greater than 90% accuracy. This artificial intelligence –already tested for cancers of the breast, ovary, and lung–could one day be used to detect many types cancer. All that’s needed is a single drop of blood’… ‘The computer does the rest. ‘… In tests on several hundred blood samples, some taken from women with ovarian cancer and others from healthy women, the test proved ‘an astonishing’ 100% accurate in detecting cancer, even at the earliest stages. Artificial nose: Scientists have endowed computers with eyes to see, thanks to digital cameras, and ears to hear, via microphones and sophisticated recognition software. Now they’re taking computers further into the realm of the senses with the development of an artificial nose.
E-NOSE TO SNIFF OUT HOSPITAL SUPERBUGS: “E-nose analyses gas samples by passing the gas over an array of electrodes coated with different conducting polymers. Each electrode reacts to particular substance by changing its electrical resistance in a characteristic way. Combining the signals from all the electrodes gives a ‘smell-print’ of the chemicals in the mixture that neural network software built into the e-nose can learn to recognize. As a result, it can be detected from the smell alone that what the bacterial infections are. Military:
A NEW MODEL OF ARMY SOLDIER ROLLS CLOSER TO THE BATTLEFIELD: The American military is working on a new generation of soldier, far different from the army it has. ‘They don’t feel hungry,’ said Gordon Johnson of the Joint Forces Command at the Pentagon. ‘They are not afraid. They don’t forget their orders. They don’t care if the guy next to them has just been shot. Will they do a better job than humans? Yes. ‘ The robot soldier is coming. The Pentagon predicts that robots will be a major fighting force in American military in less than a decade, hunting and killing enemies in combat.
Robots are a crucial part of the Army’s effort to rebuild itself as a 21st-century fighting force, and a $127 billion project called Future Combat Systems is the biggest military contract in American history. Game AI: ONLY A PAWN IN IT’S GAME: Hydra is the latest chess supercomputer to lay down the gauntlet to the world’s top players. Its architects say it is the greatest ever built, but don’t expect it to rejoice in victory or get the post-match drinks in. It is a behemoth of a machine that pits 32-linked processor against its flesh-and-blood opponents.
Hydra’s backers claim it can analyze 200 million chess moves in a second and project the game up to 40 moves ahead. Natural Language processing: The goal of the Natural Language Processing (NLP) group is to design and build software that will analyze, understand, and generate languages that humans use naturally, so that eventually you will be able to address your computer as though you were addressing another person. This goal is not easy to reach. “Understanding” language means, among other things, knowing what concepts a word or phrase stands for and knowing how to link those concepts together in a meaningful way.
It’s ironic that natural language, the symbol system that is easiest for humans to learn and use, is hardest for a computer to master. Long after machines have proven capable of inverting large matrices with speed and grace, they still fail to master the basics of our spoken and written languages. Expert Systems: The primary goal of expert systems research is to make expertise available to decision makers and technicians who need answers quickly. There is never enough expertise to go around–certainly it is not always available at the right place and the right time.
Portable with computers loaded with in-depth knowledge of specific subjects can bring decades worth of knowledge to a problem. EXPERT SYSTEMS – MAKE A DIAGNOSIS: Intution may seem like a human trick, but machines can be pretty good at it too. Underlying a hunch are dozens of tiny, subconscious rules-truths we that have learned from experience. Add them up and you get instinct: a doctor’s sense that a patient’s stomach-ache might really be appendicitis, for example. Program those rules into a computer and you get an expert system- one of many that can screen lab tests, diagnose blood infections, nd identify tumors on a mammogram. Future of AI Technology: Artificial Intelligence and robotics are likely to creep into our lives without us really noticing. However, AI has spawned some useful applications like expert systems and game AI, but the truly pervasive use of AI is still to come as more research and improved technology surfaces in the future. Here are a few applied innovations that AI promises in the future and the technologies behind them. Telephone Translators: One of the common cliches when one talks about the future is how the world is shrinking every day.
Distance used to be a barrier in travel and the invention of the airplane changed all that. Time used to be a factor in communication since the mail system took months to deliver a letter across the United States, but the telephone dissolved such a hurdle. The combinations of travel and communications has brought whole nations together except now the last barrier in international relationship is language. This is where telephone translators will change all that. Essentially, a person from the United States says some things in English into his telephone.
Almost instantaneously, a computer intercepts the voice, translates what was said, and synthetically generate the appropriate Japanese words to the person on the other line. Of Course, the translator would need advanced voice recognition, natural language processing and inferencing to extract what was meant by the English-speaker, and then synthesize a human-sounding Japanese person’s voice in conversational Japanese. A Greater Use of Expert Systems: With such success as a diagnostic in medic and mechanics presently, expert systems will be more prevalent in other applications that require an expert with whom people can consult with.
Need to identify the perfect pet for a friend? A pet expert system could ask some questions related to the person’s personality so that it can conclude the types of animals that would be suited for them. What kinds of dishes can one make tonight with the food in the refrigerator? Input the foods into a cook expert system and find out. The possibilities for expert systems are almost endless. If expert systems are designed and built correctly, users should be able to easily program their own expert and should make better decisions in their lives. Passing the Turing Test:
The idea behind the test is that if a machine could make a person think he/she was interacting with an intelligent person, why not consider the machine intelligent in its own right? The controversy over the Turing Test will probably continue into the future, but once a computer convincingly passes the test and becomes more and more integrated with society, this test would be at least the best approximation of intelligence possible. Research Assistants: The world is moving from the Industrial Age to the Information Age where the phrase “knowledge is power” is becoming a reality.
With so much information out there, it has become harder and harder to find what is really relevant. This is where a research assistant powered by AI can help. Not only can the assistant understand what one is looking for, which requires natural language processing, it is smart enough to know where to look and compare what it finds to what it is looking for to see how relevant the information is, so the person doesn’t have to do the ‘dirty work. ‘ Research assistants will be an important tool in the future by keeping the world of information from exploding into an infinite chaos of unorganized facts and figures.
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