Introduction to Computing Lecture # 12

1. Introduction to Computing Lecture # 12

2. Outline • Artificial Intelligence (AI) Definition • Turing Test • Main Areas of AI

3. Artificial Intelligence Definition • Use of computers for tasks normally regarded as needing human intelligence.(Pocket Oxford Dictionary) • Artificial intelligence (AI) is the part of computer science that attempts to make computers act like human beings. (Schneider and Gersting) • Artificial intelligence (AI) is a group of related technologies used for developingmachines to emulate human qualities, such as learning, reasoning, communicating, seeing, and hearing. (Williams and Sawyer)

4. Turing Test • Turing test – is intended to determine whether a computer possesses intelligence or self-awareness. • A human judge converses by means of a computer terminal with two entities hidden in another location –one a person typing on a keyboard, the other a software program. • Following the conversation, the judge must decide which entity is human. • In this test, intelligence – the ability to think – is demonstrated by the computer’s success in fooling the judge.

5. Turing Test Human entity Computer program Human judge

6. Main Areas of AI • Today the main areas of AI are these: • Natural Language Processing • Expert Systems • Intelligent Agents • Pattern Recognition • Fuzzy Logic • Virtual Reality and Simulation Devices • Robotics

7. 1. Natural Language Processing • The study of ways for computers to recognize and understandhuman language, such as English, whether in spoken or written form. • Main advances have occurred in speech recognition, in which computers translate spoken speech into text. • E.g., voice authentication or speaker verification • The problem with human language is that it is often ambiguous; different listeners may arrive at different interpretations. • The term “computational linguistics” is often used interchangeably with “natural language processing.”

8. 1. Natural Language Processing • Most existing systems run on large computers, although scaled down versions are now available for microcomputers • Example products: • Intellect: uses a limited English vocabulary to help users orally query databases on both mainframes and microcomputers. • LUNAR: developed to help analyze moon rocks, answers questions about geology on the basis of an extensive database. • Verbex: used by the U.S. Postal Service, lets mail sorters read aloud an incomplete address and will reply with the correct ZIP code.

9. 2. Expert Systems • An interactive computer program used in solving problems that would otherwise require the assistance of a human expert. Also called rule interpreter Such rules are a component of the knowledge base

10. 2. Expert Systems • Three components of an expert system: • Knowledge base – an expert system’s database of knowledge about a particular subject, including relevant facts, information, beliefs, assumptions, and procedures for solving problems. • The basic unit of knowledge is expressed as an IF-THEN-ELSE rule. • Programs can have as many as 10,000 rules. • Inference engine – the software that controls the search of the expert system’s knowledge base and produces conclusions. • User interface - the display screen that the user deals with, in order to ask questions and receive answers.

11. 2. Expert Systems • The success of expert systems depends on the quality of the data and rules obtained from the human experts. • Example products: • MYCIN: helps diagnose infectious diseases. • PROSPECTOR: assesses geological data to locate mineral deposits. • DENDRAL: identifies chemical compounds. • help organic chemists in identifying unknown organic molecules etc • MailJail: uses more than 600 rules to screen out junk email, or spam. • Home-Safe-Home: evaluates the residential environment of an elderly person. • Business Insight: helps businesses find the best strategies for marketing a product. • ExperTAX: helps accountants figure out a client’s tax options, consists of 2000 rules

12. 3. Intelligent Agents • An intelligent agent is a form of smart software, or software with built-in intelligence that monitors work patterns, asks questions, and performs work tasks – such as roaming networks and compiling data – on your behalf. • A kind of electronic assistant that will filter messages, scan news services, and perform similar secretarial tasks. • Intelligent agents are also applied as automated online assistants, where they function to perceive the needs of customers in order to perform individualizedcustomer service.

13. 3. Intelligent Agents • Examples: • Microsoft’s Office Assistant: can answer your questions, offers tips, and provide help for a variety of features specific to the program you are using. • Network agent or bot: searches the internet for information and then brings the results back to you.

14. 4. Pattern Recognition • Pattern recognition involves a camera and software that identify frequentpatterns in what they are seeing and recognize the connections between the perceived patterns and similar patterns stored in a database. • Examples: • Video surveillance cameras have been used to pick out suspicious individuals in crowds. • Handwriting recognition • Fingerprint identification • Automatic voice recognition

15. 5. Fuzzy Logic • A method of dealing with imprecise (incorrect/vague) data and uncertainty, with problems that have many answers rather than one. • Unlike classical logic (true/false), fuzzy logic is more like human reasoning; it deals with probability and credibility. • Instead of being simply true or false, a proposition is mostly true or mostly false, or more true or more false.

16. 5. Fuzzy Logic • Examples: • Running elevators: considerable research into how elevators may be programmed to reduce waiting time based on the nearest available car and free room in the cars. • Handhelds auto-focus video cameras: makes the necessary adjustments in the image to focus properly.

17. 6. Virtual Reality and Simulation Devices • Virtual reality (VR) – a computer-generated artificial reality which projects a person into a sensation of three-dimensional space. Virtual reality simulated air traffic controller training

18. 6. Virtual Reality and Simulation Devices • Required components for virtual reality • Software component • Head-mounted display • Two small video display screens, for each eye • Headphones with 3D sound • Gloves having sensors for collecting data about hand movements. • Examples of Virtual Reality • Atlantis – a computer simulation of The Lost Continent: an arcade-type game

19. 6. Virtual Reality and Simulation Devices • Simulators – devices that represent the behavior of physical or abstract systems. • Virtual-reality simulation technologies are applied a great deal in training. • Example of Simulators: • To train bus drivers: they create bus-like control panels and various scenarios such as icy road conditions. • To train pilots on various aircrafts and to prepare air traffic controllers for equipment failures. • Surgeons in training can develop their skills through simulation on digital-patients

20. 7. Robotics • The development and study of machines that can perform work normally done by people. Security robot on patrol at the LA County Museum of Art

21. 7. Robotics • Robot – an automatic device that performs functions ordinarily executed by human beings or that operates with what appears to be almost human intelligence. • Examples: • AIBO: a robot dog able to learn how to sit, roll over, fetch, and do other activities. • Rosie the HelpMate: delivers special-order meals from the kitchen to nursing stations and hospitals.