Artificial Intelligence (AI) Basics

Definition of AI

• Artificial Intelligence (AI): The development of computer systems that can perform tasks that typically require human intelligence, such as:
  • Learning
  • Problem-solving
  • Reasoning
  • Perception

Types of AI

• Narrow or Weak AI: Designed to perform a specific task, e.g.:
  • Siri (virtual assistant)
  • AlphaGo (game playing)
• General or Strong AI: Human-like intelligence, with ability to reason, learn, and apply knowledge across a wide range of tasks
• Superintelligence: Significantly more intelligent than the best human minds, with potential to greatly benefit or harm humanity

AI Techniques

• Machine Learning: Enables AI systems to learn from data and improve performance over time
• Deep Learning: A type of machine learning using neural networks inspired by the human brain
• Natural Language Processing (NLP): Enables AI systems to understand, generate, and process human language
• Computer Vision: Enables AI systems to interpret and understand visual data from images and videos

Applications of AI

• Robotics: AI-powered robots for manufacturing, healthcare, and other industries
• Healthcare: AI-assisted diagnosis, personalized medicine, and drug discovery
• Finance: AI-powered trading, risk management, and fraud detection
• Transportation: AI-powered autonomous vehicles and traffic management systems

AI Challenges and Limitations

• Explainability: Difficulty in understanding AI decision-making processes
• Bias and Fairness: AI systems learning and perpetuating biases from data
• Job Displacement: AI automation replacing human jobs
• Ethics and Governance: Need for regulations and guidelines for AI development and use

Definition and Types of AI

• Artificial Intelligence (AI) involves developing computer systems that can perform tasks requiring human intelligence, including learning, problem-solving, reasoning, and perception.
• There are three types of AI: Narrow or Weak AI, General or Strong AI, and Superintelligence.

Narrow or Weak AI

• Designed to perform a specific task, such as virtual assistants (e.g., Siri) and game-playing AI (e.g., AlphaGo).

General or Strong AI

• Possesses human-like intelligence, enabling it to reason, learn, and apply knowledge across a wide range of tasks.

Superintelligence

• Significantly more intelligent than the best human minds, with the potential to greatly benefit or harm humanity.

AI Techniques

Machine Learning

• Enables AI systems to learn from data and improve performance over time.

Deep Learning

• A type of machine learning using neural networks inspired by the human brain.

Natural Language Processing (NLP)

• Enables AI systems to understand, generate, and process human language.

Computer Vision

• Enables AI systems to interpret and understand visual data from images and videos.

Applications of AI

Robotics

• AI-powered robots for manufacturing, healthcare, and other industries.

Healthcare

• AI-assisted diagnosis, personalized medicine, and drug discovery.

Finance

• AI-powered trading, risk management, and fraud detection.

Transportation

• AI-powered autonomous vehicles and traffic management systems.

AI Challenges and Limitations

Explainability

• Difficulty in understanding AI decision-making processes.

Bias and Fairness

• AI systems learning and perpetuating biases from data.

Job Displacement

• AI automation replacing human jobs.

Ethics and Governance

• Need for regulations and guidelines for AI development and use.