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Chapter 13: Is Artificial Intelligence Real?

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Presentation on theme: "Chapter 13: Is Artificial Intelligence Real?"— Presentation transcript:

1 Chapter 13: Is Artificial Intelligence Real?
The field of computer science devoted to making computers perceive, reason, and act in ways that have been/are reserved for humans. Alan Turing “On Computable Numbers” - Princeton Paper that laid the groundwork for all modern computer science. led a group to build Colossus (completed 1943), a successful NAZI code cracking program. “Computing Machinery and Intelligence” launches the field of AI - Turing Test is established Turing is arrested for being homosexual Committed suicide If he had lived?

2 Chapter 13: Is Artificial Intelligence Real?
Examples of Intelligence include: - ability to learn from experience - power of thought - ability to reason - ability to perceive relations - power of insight - ability to use tools - intuition Can a machine be intelligent? Can a machine Think?

3 Chapter 13: Is Artificial Intelligence Real?
“A machine can be deemed intelligent when it can pass for a human being in a blind test” - Alan Turing Turing Test - Involves two people and a computer. If the computer can convince one human it is also human, it has passed the test. If it acts intelligent, according to Turing, it is intelligent.

4 Chapter 13: Is Artificial Intelligence Real?
ELIZA - one of the first software programs to converse in a limited form of natural language

5 Chapter 13: Is Artificial Intelligence Real?
What is Artificial Intelligence? AI is the study of ideas which enable computers to do things that make people seem intelligent. - Patrick Henry Winston From captures the general idea of AI but breaks down when applied to specific examples. AI is the study of how to make computers do things at which, at the moment, people are better. - Elaine Rich This definition sees AI as a moving frontier. “Whatever hasn’t been done yet.” These difinitions tend to be accurate but are short on specifics. AI is the study of the computations that make it possible to perceive, reason and act. - Patrick Henry Winston This most recent definition brings together the computer scientists challange of producing ‘machine intelligence’ and the psychologists desire to investigate ‘natural intelligence’.

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Two Approaches to AI 1.) Simulation Approach - attempts to use computers to simulate human mental process. Has three problems (a) most people can’t even describe how they do things (b) the human brain is far too complex to duplicate with today’s technology (c ) the best way to do something with a machine is very different from nature

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(2) Intelligent machines approach - designing intelligent machines independent of the way people think. This is best accomplished when the machines are limited to a specific domain. Games Domains (Checkers and Chess) techniques used - Searching: Using brute force to consider all possible decisions. Even checkers have 1021 choices. - Heuristics: Using ‘rules of thumb’ to guide computers toward judgements that experience tells us are likely to be true. - Pattern choices: Remembering patterns or situations which reoccur and call for a specific strategy. - Machine learning: Remembering certain moves and their results. Good moves are remembered and reused, bad ones avoided.

8 Chapter 13: Is Artificial Intelligence Real?
Domains where AI is being developed: 1.) Natural Language Communication - To create machines that can converse with humans at a human level. - Machine translation: Automatic translation using parsing programs. Separates each sentence into parts and then substitutes the translated words. Became the subject of many jokes: “Out of site, out of mind” becomes “Blind and insane” or “invisible idiot” - ELIZA: Developed by Joseph Weizenbaum, 1960s, to simulate understanding - RACTER: wrote “The Policeman’s Beard is only Half Constructed” Why is natural language so difficult? (a) Syntax - strict rules of language construction (b) Semantics - the underlying meaning of words and phrases

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2.) Knowledge Bases - differ from databases in that they are not as rigid and can be reorganised on the basis of changes in relationships. Difficult to build because common sense is acquired through life. When domains are restricted, knowledge bases become the heart of expert systems - software programs designed to replicate the decision making process of a human expert. These systems employ Fuzzy rules that state conclusions as probabilities. Here are some examples: - MYCIN - a medical expert system - XCON - Digital Corporation’s knowledge base of hardware relationships. - American Express - for doing credit checks on card holders. - Blue Cross/Blue Shield - for claims processing - Boeing Company - parts, tools and techniques for assembly - Microsoft - diagnosing printer network problems - Freelance writer Scott French - writing analysis program

10 Chapter 13: Is Artificial Intelligence Real?
AARON - an automated artist programmed by Harold Cohen, artist and professor at University of California, San Diego Uses over 1000 rules of human anatomy and behavior to create drawings of people, plants and abstract objects.

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Advantages to Expert Systems - help train new employees - reduce number of human errors - take care of routine tasks, freeing workers to focus on more challenging jobs - provide expertise when no experts are available - preserve the knowledge of experts after they have gone - combine the knowledge of several experts make knowledge available to more people

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Image Analysis - the process of identifying objects and shapes in a photo, drawing, video or other visual image. OCR - Optical Character Recognition Automated Speech Recognition Talking Computers - Synthetic speech vs speech digitized speech Neural Networks -

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Neural Networks or neural nets - rather than one powerful CPU, uses thousands of simpler processors in a form of distruibuted, parallel computing. Attempts to mimic the way the brain works. They are not programmed trained by trial and error. Information is stored as patterns of activity Artificial vision and pattern recognition.

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Robotics -

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What is Artificial Intelligence? AI is the study of ideas which enable computers to do things that make people seem intelligent. - Patrick Henry Winston AI is the study of how to make computers do things at which, at the moment, people are better. - Elaine Rich AI is the study of the computations that make it possible to perceive, reason and act. - Patrick Henry Winston Two Approaches to AI 1.) Simulation Approach - attempts to use computers to simulate human mental process. Has three problems (a) most people can’t even describe how they do things (b) the human brain is far too complex to duplicate with today’s technology (c ) the best way to do something with a machine is very different from nature

16 Chapter 13: Is Artificial Intelligence Real?
Two Approaches to AI (continued) (2) Intelligent machines approach - designing intelligent machines independent of the way people think. This is best accomplished when the machines are limited to a specific domain. Games Domains (Checkers and Chess) techniques used - Searching: Using brute force to consider all possible decisions. Even checkers have 1021 choices. - Heuristics: Using ‘rules of thumb’ to guide computers toward judgements that experience tells us are likely to be true. - Pattern choices: Remembering patterns or situations which reoccur and call for a specific strategy. - Machine learning: Remembering certain moves and their results. Good moves are remembered and bad ones avoided.

17 Chapter 13: Is Artificial Intelligence Real?
These are some Domains where AI is being developed: - Natural Language Communication - To create machines that can converse with humans at a human level. (1) Machine translation: Automatic translation using parsing programs. Separates each sentence into parts and then substitutes the translated words. Became the subject of many jokes: “Out of site, out of mind” becomes “Blind and insane” or “invisible idiot” (2) ELIZA: Developed by Joseph Weizenbaum, 1960s, to simulate understanding (3) RACTER: wrote “The Policeman’s Beard is only Half Constructed” Why is natural language so difficult? (1) Syntax - strict rules of language construction (2) Semantics - the underlying meaning of words and phrases

18 Chapter 13: Is Artificial Intelligence Real?
Knowledge Bases - differ from databases in that they are not as rigid and can be reorganised on the basis of changes in relationships. Difficult to build because common sense is acquired through life. When domains are restricted, knowledge bases become the heart of expert systems - software programs designed to replicate the decision making process of a human expert. These systems employ Fuzzy rules that state conclusions as probabilities. Here are some examples: 1.) MYCIN - a medical expert system 2.) XCON - Digital Corporation’s knowledge base of hardware relationships. 3.) American Express - for doing credit checks on card holders. 4.) Blue Cross/Blue Shield - for claims processing 5.) Boeing Company - parts, tools and techniques for assembly 6.) Microsoft - diagnosing printer network problems 7.) Freelance writer Scott French - writing analysis program


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