Why Large Language Models Work: A Modern AI Perspective
R1 · UNDERSTAND11 minIn this course, you will gain a clear understanding of why Large Language Models (LLMs) became effective around 2020-2023. You will learn the historical context and essential vocabulary to explain how modern LLM tools fit within the broader 60-year field of AI, and why previous AI approaches did not achieve similar success.
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Syllabus
1. What the word "AI" actually covers
- Defining AI and its Shifting Boundaries
- Examples Across the AI Hierarchy
- Module 1 Summary and Quiz
2. A brief, honest history (three waves)
- Symbolic AI and the AI Winters
- Statistical ML and the Deep Learning Ignition
- The Transformer and the LLM Era
3. Prior AI vs. generative AI: what actually changed
- Contrasting AI Paradigms
- Discriminative vs. Generative AI
- Module 3 Summary and Quiz
4. Why LLMs "suddenly started working" (the crux)
- The Scalable Transformer Architecture
- Self-supervised Pre-training
- Scale and Scaling Laws
- The 'Just Add Scale' Caveat
5. Situating today's products (5-minute close)
- Mapping Real-World AI Tools
- Module 5 Summary and Final Quiz