Artificial Intelligence introduction Intelligence Types Learning Types

1. Basics of Artificial Intelligence

2. AI - Definition
• The science and engineering of making intelligent machines,
especially intelligent computer programs –John McCarthy
• Artificial Intelligence is a way of making a computer, a robot,
or a software that think intelligently like intelligent humans
think.

3. How AI is Accomplished?
• By studying how human brain thinks and how humans learn,
decide, and work while trying to solve a problem.
• Use the outcomes of this study (course) as a basis of developing
intelligent software and systems.

4. Need of AI
• There are numerous reasons to learn AI.
– AI can learn through data
– AI can teach itself
– AI can help us understand what “intelligence” means

5. What is Intelligence?
The ability of a system to
• Perceive the environment
• Calculate & reason from the percepts
• Learn from experience
• Store and retrieve information from memory
• Solve problems, comprehend complex ideas
• Use natural language fluently
• Classify, generalize, and adapt to new situations.

6. Types of Intelligence
• Linguistic Intelligence
• Musical Intelligence
• Logical-Mathematical intelligence
• Spatial intelligence
• Soft skills, etc..

7. Signs of Intelligence
• Perception
• Reasoning
• Learning
• Problem Solving

8. Reasoning
•Inductive Reasoning
• Making generalizations from specific observations
• Dhoni is a Cricketer. Dhoni is hardworking. Therefore, all
cricketers are hardworking!
•Deductive Reasoning
• Start with a general statement and reach a specific conclusion
• All cricketers are sportsmen. Dhoni is cricketer. So He is a
sportman.

9. Learning
• Auditory learning
• Episodic learning - process of storing or retrieving experiences in
one's episodic memory and using it to improve behavior. It’s a long-term
memory used to store unique events, or episodes, from one's past.
• Motor learning
• Observational learning
• Perceptual learning
• Relational learning

10. Other types of Learning
• Supervised learning
• Unsupervised learning
• Semi-Supervised learning
• Reinforcement learning

11. Problem Solving
• It is the process in which one perceives and tries to arrive at a
desired solution from a present situation by taking some path,
which is blocked by known or unknown hurdles.
• It is the process of decision making, which involves selecting the
best alternative out of multiple alternatives to reach the desired
goal.

12. Applications of AI
• Games
• Natural Language Processing
• Expert Systems
• Vision Systems
• Speech Recognition
• Handwriting Recognition
• Intelligent Robots

13. References
• Tom Markiewicz & Josh Zheng, Getting started with Artificial Intelligence,
Published by O’Reilly Media,2017
• Stuart J. Russell and Peter Norvig, Artificial Intelligence A Modern Approach