Foundations of Artificial Intelligence Overview
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Foundations of Artificial Intelligence Overview

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Questions and Answers

What does Artificial Intelligence (AI) mean?

A man-made thinking power.

Which of the following best describes Artificial Intelligence?

  • A way to enhance human physical capabilities
  • The art of creating machines that perform functions requiring human intelligence (correct)
  • A form of entertainment technology
  • A science that studies the physical world
  • What is Weak AI also known as?

  • Strong AI
  • General AI
  • Deep AI
  • Narrow AI (correct)
  • Narrow AI can operate effectively beyond its preset limitations.

    <p>False</p> Signup and view all the answers

    What major technological advancement has contributed to the AI boom in the 2000s?

    <p>Deep learning and big data.</p> Signup and view all the answers

    Match the following milestones in AI history with their years:

    <p>Alan Turing develops the Turing test = 1950 First scientific conference on AI = 1956 First chatbot 'ELIZA' created = 1966 AI beats world chess champion (Deep Blue) = 1997 ChatGPT revolutionizes chatbots = 2023</p> Signup and view all the answers

    Study Notes

    What is Artificial Intelligence?

    • Artificial Intelligence (AI) combines "artificial" meaning man-made and "intelligence" referring to thinking power, leading to the concept of machines capable of human-like thinking.
    • AI enables the development of intelligent machines that can emulate human behavior, decision-making, learning, and problem-solving.
    • Defined as both the science and engineering of crafting intelligent machines, particularly intelligent computer programs.

    Goals of AI

    • Create computers that undertake dangerous or tedious tasks to enhance human efficiency.
    • Gain insights into the principles underlying human intelligence.

    Foundations of AI

    • Philosophy: Explores logic, reasoning, language, and the concept of the mind as a physical system.
    • Mathematics: Focuses on formal representation, algorithms, computation, and probability.
    • Psychology: Studies adaptation, perception, and motor control using experimental techniques.
    • Linguistics: Involves knowledge representation and grammar development.
    • AI integrates principles from computer science, biology, psychology, linguistics, mathematics, and engineering.

    Historical Foundations of AI

    • 1950s: Coining of the term "artificial intelligence"; early research centered on problem-solving and symbolic reasoning.
    • 1960s-1970s: Emergence of expert systems and initial machine learning; limited by computational power.
    • 1980s-1990s: Growth of interest due to neural networks and personal computers.
    • 2000s-Present: AI boom driven by advancements in deep learning, big data, and cloud computing, showcasing vast applications.

    Key Milestones in AI Development

    • 1950: Alan Turing proposes the Turing Test for machine intelligence assessment.
    • 1956: AI is officially named during a scientific conference.
    • 1966: Development of ELIZA, the first chatbot.
    • 1972: Introduction of MYCIN, an AI system assisting in medical diagnoses and therapy for bacterial infections.
    • 1997: Deep Blue's victory over a world chess champion marks a significant achievement in AI.
    • 2011: Widespread integration of AI-driven voice assistants in smartphones.
    • 2023: ChatGPT significantly influences chatbot applications.

    Types of Artificial Intelligence Based on Capabilities

    • Weak AI (Narrow AI):
      • Designed for specific tasks, operating within a limited scope.
      • Cannot function beyond its trained domain, leading to unpredictable failures.
      • Examples include Apple Siri and IBM's Watson, both of which have defined operational limits.

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    Description

    This quiz provides an overview of the foundations of Artificial Intelligence, covering key concepts and definitions. Participants will explore the relationship between artificial systems and human-like intelligence, gaining insights into its significance in modern computer science.

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