Artificial intelligence

• AI Applications


  • Intelligent Robots
  • Expert Systems
  • Gaming
  • Vision Systems
  • Natural Language Processing
  • Handwriting Recognition
  • Speech Recognition
• AI is the science and engineering of making intelligent machines, especially intelligent computer programs. 
• Intelligent Robots


  • AI-programmed robots can perform all human tasks and adapt to changes
• It is composed of two words: artificial defines man made and intelligence defines thinking power. 
• Expert Systems


  • AI-enabled machines provide explanations and advice to humans, like car engine fault diagnosis machines
• Cognition refers to the use of conscious mental process, which means the process of thought 
• Gaming


  • AI can generate numerous options based on data, like chess and tic-tac-toe
• Vision Systems

  • AI can understand and comprehend computer visual input
• Goal of intelligent system 

  Is to enable the system to think and behave like humans do, in order to solve a problem. 
• Natural Language Processing


  • AI has become proficient in human-spoken natural language
• Handwriting Recognition


  • AI software can read and convert handwritten text
• Speech Recognition


  • AI can handle speech-related data, understand commands, handle background noise, and voice modulation
• Purpose of AI 

  1. Implement human intelligence in machines by creating systems that can think, act, learn and behave like humans. 

  2. Create expert systems that can behave intelligently, learn, explain, demonstrate and give suggestions to its users. 

  3. Enable a system to understand and process natural language. 

  4. Empower a system to perform intellectual tasks that a human can perform. 
• Domains Overview

  • Mundane tasks: Routine tasks like common sense, planning, reasoning.

  • Formal tasks: Requires formal training like verification and theorems.

  • Expert tasks: Require educational qualifications like engineering for manufacturing planning, medical diagnosis.
• AI tools

  • Logic: used for concept representation and problem-solving
  • search and optimization: used for solving Ai problems through exhaustive search methods
  • classifiers and statistical learning methods: patterns or observations that form a dataset
  • probabilistic methods for unrealistic reasoning: used for problems involving assumed data and circumstances