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Artificial intelligence
This document provides an overview of artificial intelligence (AI), including its history, categories, branches, applications, and tools. It discusses how AI has evolved through different generations of computing. Key topics covered include expert systems, neural networks, programming languages used in AI, the American Association for Artificial Intelligence (AAAI), and perspectives on AI's future potential impacts and applications.
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Artificial intelligence
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- 2. INDEX 1. INTRODUCTION 2. TIMELINEOF AI 3. CATEGORIES OF AI 4. BRANCHES OF AI 5. APPLICATIONS OF AI 6. TOOLS USED IN AI 7. MODERN APPLICATIONS OF AI 8. FIFTH GENERATION COMPUTING 9. AMERICAN ASSOCIATION FOR ARTIFICIAL INTELLIGENCE (AAAI) 10. FUTURE SCOPE 11. BIBLIOGRAPHY
- 3. INTRODUCTION INTELLIGENCE? “Thecapacity to learn and solve problems” in particular. The ability to solve novel problems. The ability to act rationally. The ability to act like humans. ARTIFICIAL INTELLIGENCE? Intelligence exhibited by an artificial entity. Basically : Putting human intelligence into a machine.
- 4. INTRODUCTION Artificial intelligence(AI) is the intelligence exhibited by machines or software. Major AI researchers and textbooks define this field as "the study and design of intelligent agents", in which an intelligent agent is a system that perceives its environment and takes actions that maximize its chances of success. John McCarthy, who coined the term in 1955, defines it as “the science and engineering of making intelligent machines’’. Some say it’s putting the human mind into computers. The field was founded on the claim that a central property of humans, human intelligence -- the sapience of Homo sapiens—"can be so precisely described that a machine can be made to simulate it.
- 5. INTRODUCTION Artificial Intelligenceand general artificial intelligence are distinct areas of research. General Intelligence is still among the field’s long term goals. Artificial intelligence refers to intelligence exhibited by machines. They can be broken down into: ARTIFICIALINTELLIGENCE Reasoning Knowledge Planning Learning Natural language processing(communication) Perception Ability to move and manipulate objects
- 6. INTRODUCTION The AIfield is interdisciplinary, in which a number of sciences and professions converge. ARTIFICIAL INTELLIGENCE Computer science Mathematics Psychology Linguistics Philosophy Neuroscience Artificial Psychology
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- 9. ARTIFICIALINTELLIGENCE ARTIFICIAL NARROW INTELLIGENCE (weakAI) ARTIFICIAL GENERAL INTELLIGENCE (strong AI) ARTIFICIAL SUPER INTELLIGENCE
- 10. BRANCHES OF AI Logical AI Search Pattern recognition Representation Inference Common sense knowledge and reasoning Learning from experience Planning Epistemology Ontology Heuristics Genetic programming
- 11. APPLICATIONS OF AI Game playing Speech recognition Computer vision Hospitals and medicine Heavy industry Expert systems Understanding natural language
- 12. EXPERT SYSTEMS Thefirst expert systems were created in the 1970s and then proliferated in the 1980s. Expert systems were introduced by the Stanford Heuristic Programming Project led by Edward Albert Feigenbaum , who is sometimes referred to as the "Father of expert systems". In artificial intelligence, an expert system is a computer system that emulates the decision-making ability of a human expert. A computer application that performs a task that would otherwise be performed by a human expert. For example, there are expert systems that can diagnose human illnesses, make financial forecasts, and schedule routes for delivery vehicles. Some expert systems are designed to take the place of human experts, while others are designed to aid them.
- 13. EXPERT SYSTEMS Anexpert system is divided into two sub-systems: knowledge base inference engine The knowledge base represents facts and rules. To design an expert system, one needs a knowledge engineer, an individual who studies how human experts make decisions and translates the rules into terms that a computer can understand. The inference engine applies the rules to the known facts to deduce new facts. Inference engines can also include explanation and debugging capabilities.
- 15. EXPERT SYSTEMS A``knowledge engineer'' interviews experts in a certain domain and tries to embody their knowledge in a computer program for carrying out some task. How well this works depends on whether the intellectual mechanisms required for the task are within the present state of AI. When this turned out not to be so, there were many disappointing results. One of the first expert systems was MYCIN in 1974, which diagnosed bacterial infections of the blood and suggested treatments. It did better than medical students or practicing doctors, provided its limitations were observed. Namely, its ontology included bacteria, symptoms, and treatments and did not include patients, doctors, hospitals, death, recovery, and events occurring in time. Its interactions depended on a single patient being considered. Since the experts consulted by the knowledge engineers knew about patients, doctors, death, recovery, etc., it is clear that the knowledge engineers forced what the experts told them into a predetermined framework. In the present state of AI, this has to be true. The usefulness of current expert systems depends on their users having common sense.
- 16. Natural Language Processing Threebasic types of processing occur during human/ computer voice interaction, Voice synthesis Using a computer to recreate the sound of human speech Voice recognition Using a computer to recognize the words spoken by a human Natural language comprehension Using a computer to apply a meaningful interpretation to human communication
- 17. TOOLS USED INAI In the course of 50 years of research, AI has developed a large number of tools to solve the most difficult problems in computer science. A few of the most general of these methods are discussed below. Search and optimization Logic Probabilistic methods for uncertain reasoning Classifiers and statistical learning methods Neural networks Control theory Languages
- 19. A neural networkis an interconnected group of nodes, akin to the vast network of neurons in the human brain.
- 20. PROGRAMMING LANGUAGES AIML(Artificial Intelligence Markup Language) for use with A.L.I.C.E.-type chatterbots. IPL was the first language developed for artificial intelligence. Lisp is a practical mathematical notation for computer programs based on lambda calculus. There are many dialects of Lisp in use today, among them are Common Lisp, Scheme, and Clojure . Prolog is a declarative language where programs are expressed in terms of relations, and execution occurs by running queries over these relations. Prolog is widely used in AI today. STRIPS is a language for expressing automated planning problem instances Planner is a hybrid between procedural and logical languages. It gives a procedural interpretation to logical sentences Python is very widely used for Artificial Intelligence. They have a lot of different AIs with corresponding packages: General AI, Machine Learning, Natural Language Processing and Neural Networks. AI applications are also often written in standard languages like C++ and languages designed for mathematics, such as MATLAB and Lush.
- 26. FIFTH GENERATION COMPUTING The term "fifth generation" was intended to convey the system as being a leap beyond existing machines. In the history of computing hardware, First generation(1940 -1956) : Computers using vacuum tubes. Second generation(1956 -1963): Computers using transistors and diodes. Third generation(1964 -1971): Computers using integrated circuits. Fourth generation(1971- present): Computers using microprocessors. Whereas previous computer generations had focused on increasing the number of logic elements in a single CPU, the fifth generation (present and beyond), instead turn to massive numbers of CPUs for added performance.
- 27. FIFTH GENERATION COMPUTING The Fifth Generation Computer Systems project (FGCS) was an initiative by Japan's Ministry of International Trade and Industry, begun in 1982, to create a computer using massively parallel computing/processing. It aimed to create an "epoch-making computer" with-supercomputer-like performance and to provide a platform for future developments in artificial intelligence. Fifth generation computing devices, based on artificial intelligence, are still in development, though there are some applications, such as voice recognition, that are being used today. The use of parallel processing and superconductors is helping to make artificial intelligence a reality.
- 28. IBM 650 IBM7090 IBM 360/91
- 29. Association for theAdvancement of Artificial Intelligence (AAAI) Founded in 1979, the Association for the Advancement of Artificial Intelligence (AAAI) (formerly the American Association for Artificial Intelligence) is a nonprofit scientific society devoted to advancing the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines. AAAI aims to promote research in, and responsible use of, artificial intelligence.
- 30. FUTURE SCOPE • Artificialminds will just single mindedly pursue their aims and these aims may not necessarily coincide with ours. • “WE’RE UNLIKELY EVER TO BE ABLE TO EFFECTIVELY CONTROL ANY SUPER INTELLIGENCE WE CREATE”.
- 31. • A machinewould’nt specifically want to kill us but its ammortality would mean that it would be willing to cause our extinction if necessary.
- 32. But,according to theoptimists,in a world of artificial super intelligence machines will still be our servants.
- 33. • The immediatepriority of super intelligence would beto help us to create FREE ENERGY. • In turn dramatically reducing the prices of almost everything. • Everything currently costly,would drop to almost zero!! • The way data costs now.
- 34. BIBLIOGRAPHY http://www.webopedia.com/ www.sciencedirect.com http://www.aaai.org/ https://www.youtube.com/results?search_query=artificial+intelligence+ http://machineslikeus.com/news/whatever-happened-artificial- intelligence
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