Beekman5 std ppt_14

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Beekman5 std ppt_14

  1. 1. Chapter 14 Is Artificial Intelligence Real?
  2. 2. Topics <ul><li>Thinking machines – the concept and the controversy </li></ul><ul><li>How computers play (and win) games </li></ul><ul><li>Computers that Speak and translate human language </li></ul><ul><li>Expert systems and robots at work </li></ul>
  3. 3. Thinking about Thinking Machines <ul><li>If you ask 10 people to define intelligence, you’re likely to get 10 different answers, including some of these: </li></ul><ul><ul><li>The ability to learn from experience </li></ul></ul><ul><ul><li>The power of thought </li></ul></ul><ul><ul><li>The ability to reason </li></ul></ul><ul><ul><li>The ability to perceive relations </li></ul></ul><ul><ul><li>The power of insight </li></ul></ul><ul><ul><li>The ability to use tools </li></ul></ul><ul><ul><li>Intuition </li></ul></ul>
  4. 4. Can Machines Think? A machine may be deemed intelligent when it can pass for a human being in a blind test. — Alan Turing
  5. 5. What Is Artificial Intelligence Artificial intelligence is the study of ideas which enable computers to do the things that make people seem intelligent . — Patrick Henry Winston , in Artificial Intelligence These definitions commonly appear in today’s popular press: Artificial intelligence is the study of how to make computers do things at which, at the moment, people are better . Artificial intelligence is the study of the computations that make it possible to perceive, reason, and act. — Patrick Henry Winston , in Artificial Intelligence
  6. 6. What Is Artificial Intelligence <ul><li>Two common approaches to AI include: </li></ul><ul><ul><li>One approach attempts to use computers to simulate human mental processes. For example, an AI expert might ask people to describe how they solve a problem and attempt to capture their answers in a software model. </li></ul></ul><ul><ul><li>The second, more common, approach to AI involves designing intelligent machine independent of the way people think . According to this approach, human intelligence is just one possible kind of intelligence. </li></ul></ul>
  7. 7. Opening Games <ul><li>Much of the early AI work focused on games because they were easy to represent in the computer’s digital memory, they had clearly defined rules, and the goals were unmistakable. </li></ul><ul><li>Game researchers could focus on the concrete question “How can I create a program that wins consistently?” </li></ul>
  8. 8. Opening Games <ul><li>AI techniques developed by game researchers are still used today in a variety of applications. These techniques include: </li></ul><ul><ul><li>Searching </li></ul></ul><ul><ul><li>Heuristics </li></ul></ul><ul><ul><li>Pattern Recognition </li></ul></ul><ul><ul><li>Machine Learning </li></ul></ul>
  9. 9. Natural Language Communication <ul><li>Since the earliest days of computing, scientists have dreamed of machines that could communicate in natural languages like English, Russian, and Japanese. </li></ul>
  10. 10. Natural Language Communication <ul><li>Types of Natural language applications include: </li></ul><ul><ul><li>Machine Translation Traps </li></ul></ul><ul><ul><li>Conversation without communication </li></ul></ul><ul><ul><li>Nonsense and common sense </li></ul></ul>
  11. 11. M achine Translation Traps <ul><li>A parsing program (or parser ) analyzes sentence structure and identify each word according to whether it was a subject, verb, or other part of speech; another program would look up each word in a translation dictionary and substitute the appropriate word. </li></ul>
  12. 12. Conversation without communication <ul><li>Similar lessons emerged from Joseph Weizenbaum’s work with ELIZA, one of the first software programs to converse in a limited form of natural language. </li></ul>
  13. 13. Nonsense and common sense <ul><li>Every language has a syntax —a set of rules for constructing sentences from words. In a programming language, the syntax rules are exact and unambiguous. </li></ul><ul><li>However, natural-language parsing programs have to deal with rules that are vague, ambiguous, and contradictory. </li></ul>“ Time flies like an arrow.”
  14. 14. Knowledge Bases and Expert System <ul><li>The human brain isn’t particularly good at storing and recalling facts, but excels at manipulating knowledge. </li></ul><ul><li>Computers, on the other hand, are better at handling data than knowledge. </li></ul><ul><li>Consequently, Artificial intelligence researchers have developed techniques for representing knowledge in computers. </li></ul>The computer can’t tell you the emotional story . It can give you the exact mathematical design, but what’s missing is the eyebrows . — Frank Zappa
  15. 15. Knowledge Bases and Expert System <ul><li>Knowledge Bases contain a system of rules for determining and changing the relationship among those facts. Facts stored in a database are rigidly organized in categories; ideas stored in a knowledge base can be reorganized as new information changes their relationships. </li></ul>
  16. 16. Knowledge Bases and Expert System <ul><li>An expert system is a software program designed to replicate the decision-making process of a human expert. At the foundation of every expert system is a knowledge base representing ideas from a specific field of expertise. </li></ul>
  17. 17. Expert Systems in Action <ul><li>The first successful expert systems were developed around medical knowledge bases. </li></ul><ul><li>The business community has been more enthusiastic than the medical community in its use of expert systems. Some examples of expert systems in action include: </li></ul><ul><ul><li>American Express uses an expert system to automate the process of checking for fraud and misuses of its no-limit credit card. </li></ul></ul><ul><ul><li>Blue Cross/Blue Shield of Virginia an expert system automates insurance claim processing. </li></ul></ul>
  18. 18. Expert Systems in Perspective <ul><li>From the following examples it should be clear that expert systems offer many advantages. An expert system can perform these tasks: </li></ul><ul><ul><li>Help train new employees </li></ul></ul><ul><ul><li>Reduce the number of human errors </li></ul></ul><ul><ul><li>Take care of routine tasks so workers can focus on more challenging job </li></ul></ul><ul><ul><li>Provide expertise when no experts are available </li></ul></ul><ul><ul><li>Preserve the knowledge of experts after those experts leave an organization. </li></ul></ul>
  19. 19. Pattern Recognition: Making Sense of the World <ul><li>Pattern recognition involves identifying recurring patterns in input data with the goal of understanding or categorizing that input. </li></ul><ul><li>Applications include: </li></ul><ul><ul><li>Image Analysis </li></ul></ul><ul><ul><li>Optical Character Recognition </li></ul></ul><ul><ul><li>Automatic Speech Recognition </li></ul></ul><ul><ul><li>Talking Computers </li></ul></ul><ul><ul><li>Neural Networks </li></ul></ul>
  20. 20. Pattern Recognition: Making Sense of the World <ul><li>Image analysis is the process of identifying objects and shapes in a photograph, drawing, video, or other visual image. </li></ul>
  21. 21. Pattern Recognition: Making Sense of the World <ul><li>Optical character recognition (OCR) software locates and identifies printed characters embedded in images—it “reads” text. This is no small task for a machine, given the variety of typefaces and styles in use today. </li></ul>
  22. 22. Pattern Recognition: Making Sense of the World <ul><li>Automatic speech recognition systems use pattern recognition techniques similar to those used by vision and OCR systems, including these: </li></ul><ul><ul><li>Segmentation of input sound patterns into individual words and phonemes </li></ul></ul><ul><ul><li>Expert rules for interpreting sounds </li></ul></ul><ul><ul><li>Context “experts” for dealing with ambiguous sounds </li></ul></ul><ul><ul><li>Learning from a human trainer </li></ul></ul>
  23. 23. Pattern Recognition: Making Sense of the World <ul><li>Many computer applications speak like humans by playing prerecorded digitized speech and other digitized sounds stored in memory or disk. </li></ul>
  24. 24. Pattern Recognition: Making Sense of the World <ul><li>Neural networks (or neural nets ) are distributed, parallel computing systems inspired by the structure of the human brain. Instead of a single, complex CPU, a neural network uses a network of a few thousand simpler processors called neurons. </li></ul>
  25. 25. The Robot Revolution <ul><li>A robot is a computer-controlled machine designed to perform specific manual tasks. A robot’s central processor might be a microprocessor embedded in the robot’s shell, or it might be a supervisory computer that controls the robot from a distance. </li></ul>
  26. 26. The Robot Revolution <ul><li>Robots offer several advantages: </li></ul><ul><ul><li>Robots can work 24 hours a day, 365 days a year, without vacations, strikes, sick leave, or coffee breaks. </li></ul></ul><ul><ul><li>Robots are effective at doing repetitive jobs in which bored, tired people are prone to make errors and have accidents. </li></ul></ul><ul><ul><li>Robots are ideal for jobs that are dangerous, uncomfortable, or impossible for human workers. </li></ul></ul>
  27. 27. AI Implications and Ethical Questions <ul><li>Experts believe that scientists will eventually create artificial beings that are more intelligent than their creators ….. </li></ul><ul><li> a prospect with staggering implications. </li></ul>

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