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Artificial Intelligence

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Presentation on theme: "Artificial Intelligence"— Presentation transcript:

1 Artificial Intelligence

2 Artificial Intelligence
What is AI? Intelligence: “ability to learn, understand and think”. AI is the study of how to make computers make things which at the moment people do better. Examples: Speech recognition, Smell, Face, Object, Intuition, Inferencing, Learning new skills, Decision making, Abstract thinking. Artificial Intelligence

3 What is AI? Artificial Intelligence is concerned with the design of intelligence in an artificial device. The term was coined by McCarthy in 1956. Two ideas in the definition Intelligence Artificial device Artificial Intelligence

4 Artificial Intelligence
AI Features Thinking humanly Thinking rationally Acting humanly Acting rationally Artificial Intelligence

5 Acting Humanly: The Turing Test
Alan Turing ( ) “Computing Machinery and Intelligence” (1950) Imitation Game Human Human Interrogator AI System Artificial Intelligence

6 Turing Test To pass the Turing Test a computer need to possess the following capabilities: Natural language processing Knowledge representation Automated reasoning Machine learning Computer vision robotics Artificial Intelligence

7 Thinking humanly A given program thinks like a human
Through introspection Reporting on one’s inner thoughts Through psychological experiments Computer’s I/O and timing behaviors match corresponding human behaviors Artificial Intelligence

8 Artificial Intelligence
Acting Rationally Rational agent approach. Agent: something that acts. Rational agent: one that acts so as to achieve the best. Acting so as to achieve one’s goals, given one’s beliefs. Does not necessarily involve thinking. Advantages: - More general than the “laws of thought” approach (Thinking Rationally). - More amenable to scientific development than human-based approaches. Artificial Intelligence

9 Artificial Intelligence
The Foundations of AI Philosophy (423 BC - present): - Logic, methods of reasoning. - Mind as a physical system. - Foundations of learning, language, and rationality. Mathematics (c present): - Formal representation and proof. - Algorithms, computation, decidability, tractability. - Probability. Psychology ( present): - Adaptation. - Phenomena of perception and motor control. - Experimental techniques. Linguistics ( present): - Knowledge representation. - Grammar. Artificial Intelligence

10 History of AI Gestation of AI (1943-1955) Birth of AI (1956)
Great Expectation ( ) Dose of Reality ( ) Knowledge-based systems ( ) AI becomes an industry (1982-present) Return of Neural Networks (1986-present) AI becomes a science (1987-present) Emergence of intelligent agents (1995-present) Artificial Intelligence

11 Artificial Intelligence
Task Domains of AI Mundane Tasks: Perception Vision Speech Natural Languages Understanding Generation Translation Common sense reasoning Robot Control Formal Tasks: Games : chess, checkers etc Mathematics: Geometry, Logic, Proving properties of programs Expert Tasks: Engineering ( Design, Fault finding, Manufacturing planning) Scientific Analysis Medical Diagnosis Financial Analysis Artificial Intelligence

12 Artificial Intelligence
AI Technique Intelligence requires Knowledge Knowledge possesses less desirable properties such as: Voluminous Hard to characterize accurately Constantly changing Differs from data that can be used AI technique is a method that exploits knowledge that should be represented in such a way that: Knowledge captures generalization It can be understood by people who must provide it It can be easily modified to correct errors. It can be used in variety of situations Artificial Intelligence

13 Typical AI problems Common-place tasks Expert tasks
Recognizing people, objects Communicating (through natural language) Navigating around obstacles on the streets Expert tasks Medical diagnosis Mathematical problem solving Playing games like chess Artificial Intelligence

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