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