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<!DOCTYPE html> <html lang="en"> <head> <meta charset="UTF-8"> <meta name="viewport" content="width=device-width, initial-scale=1.0"> <title>Module 1 - AI Course</title> <link rel="stylesheet" href="../static/module1.css"> <!-- Path to CSS might differ --> </head> <body> <div class="wrapper"> <aside class="sidebar"> <h2>AI Course Modules</h2> <ul> <li class="active"><a href="../module/module1.html">Week 1: Introduction to AI</a></li> <li><a href="module2.html">Week 2: History of AI</a></li> <li><a href="module3.html">Week 3: Machine Learning</a></li> <li><a href="module4.html">Week 4: Deep Learning Fundamentals</a></li> <li><a href="module5.html">Week 5: Natural Language Processing</a></li> <li><a href="module6.html">Week 6: Computer Vision</a></li> <li><a href="module7.html">Week 7: Robotics and AI</a></li> <li><a href="module8.html">Week 8: Ethics in AI</a></li> <li><a href="module9.html">Week 9: AI in Industry</a></li> <li><a href="module10.html">Week 10: Future of AI</a></li> <li><a href="module11.html">Week 11: AI Tools and Libraries</a></li> <li><a href="module12.html">Week 12: Building AI Projects</a></li> </ul> </aside> <section class="content"> <h1>Module 1: Introduction to AI</h1> <h2>Lesson 1.1: What is Artificial Intelligence?</h2> <p> Artificial Intelligence (AI) is a transformative field of computer science focused on creating machines capable of mimicking human cognitive functions such as learning, reasoning, problem-solving, and decision-making. This lesson explores the basic concepts, history, and evolution of AI to help you appreciate how past innovations contribute to current technologies. </p> <h3>Historical Context and Origins</h3> <p> The scientific discipline of artificial intelligence was formally established at a workshop at Dartmouth College in 1956. This marked the formal inception of AI as a field of research, setting the stage for the evolution of its technologies. </p> <ul> <li><strong>1950s:</strong> The Turing Test and early AI programming.</li> <li><strong>1960s and 1970s:</strong> Early AI programs like ELIZA and the challenges of limited technology.</li> <li><strong>1980s:</strong> AI winter due to reduced funding and interest.</li> <li><strong>1990s:</strong> Resurgence with machine learning and the Internet.</li> <li><strong>2000s:</strong> Advancements in algorithms and the boom of big data.</li> <li><strong>2010s and Beyond:</strong> AI becomes integral to consumer technology and industry with advancements in real-world applications.</li> </ul> <h2>Lesson 1.2: Categories of AI</h2> <p> This lesson discusses the two primary categories of AI: Narrow AI and General AI, examining their applications and implications. </p> <h3>Narrow AI (Artificial Narrow Intelligence)</h3> <ul> <li><strong>Characteristics:</strong> Task-oriented, limited scope, example-based operations.</li> <li><strong>Applications:</strong> Voice assistants, recommendation systems, autonomous vehicles.</li> </ul> <h3>General AI (Artificial General Intelligence)</h3> <ul> <li><strong>Characteristics:</strong> Adaptive learning, understanding and reasoning, autonomy.</li> <li><strong>Future Applications:</strong> Complex decision-making, research and development, personalized education.</li> </ul> <p> Understanding these categories helps contextualize the capabilities and limitations of AI technologies and provides insight into how AI can evolve in the coming years. </p> </section> </div> </body> </html>
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