2. I. Introduction to AI
II. Types of AI
III. Machine Learning
IV. Natural Language Processing (NLP)
V. Computer Vision
VI. Robotics and Automation
VII. Expert Systems
VIII. Speech Recognition
IX. Ethical Considerations in AI
Table of
3. Introduction
to
What is the goal of Artificial
Intelligence or AI?
To create machines capable
of intelligent behavior.
Examples:
Siri, Google Assistant, and
autonomous vehicles
4. Types
1. Narrow AI (Weak AI): Specialized in a
specific task
2. General AI (Strong AI): Mimics human
cognitive abilities across various tasks
3. Superintelligent AI: Surpassing human
intelligence
Example:
Virtual personal assistants are a form of Narrow AI
5. Machine
Definition: Subset of AI enabling systems
to learn and improve from experience
Types:
• Supervised
• Unsupervised
• Reinforcement Learning
Example:
Recommender systems
Fraud detection algorithms
6. Natural
Processing
Definition: AI's ability to understand
and generate human language
Applications: Chatbots, language
translation, sentiment analysis
Example: Google Translate, Amazon
Alexa's language understanding
7. Computer
Definition: AI's capability to
interpret and understand visual
information
Applications: Facial recognition,
object detection, image and video
analysis
Example: Autonomous vehicles,
security surveillance systems
8. and
Definition: Utilizing AI to control and
automate physical processes
Applications: Manufacturing, logistics,
healthcare
Example: Robotic arms in production
lines, surgical robots
9. Expert
Definition: AI systems designed to
mimic human decision-making in
a specific domain
Applications: Medical diagnosis,
financial planning
Example: IBM's Watson for
healthcare diagnostics
10. Speech
Definition: AI's ability to convert
spoken language into text
Applications: Virtual assistants,
voice-controlled devices
Example:
Apple's Siri, Amazon Echo's Alexa
11. Ethical
in AI
• Bias in AI algorithms
• Privacy concerns
• Job displacement
• Transparency and accountability
13. Icons
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