
Premium
Opening Credits
1/1/2026
Chapter 1: Introduction
1/1/2026
Chapter 2: Birth of AI
1/1/2026
Chapter 3: Early AI models
1/1/2026
Chapter 4: Magic of probabilities
1/1/2026
Chapter 5: Tokenisation
1/1/2026
Chapter 6: The geomentry of words
1/1/2026
Chapter 7: The transformation revolution
1/1/2026
Chapter 8: Understanding order in transformers
1/1/2026
Chapter 9: Learning through error
1/1/2026
Chapter 10: Balancing randomness and determinism
1/1/2026
Chapter 11: Why size matters
1/1/2026
Chapter 12: Preventing overfitting
1/1/2026
Chapter 13: Retaining the past, shaping the future
1/1/2026
Chapter 14: Seeing, hearing, and understanding
1/1/2026
Chapter 15: Behind the curtain inside the world of llm research
1/1/2026
Chapter 16: Fine tuning and transfer learning
1/1/2026
Chapter 17: Aligning AI with human values
1/1/2026
Chapter 18: Meta learning and few shot capabilities
1/1/2026
Chapter 19: Interpretability and explainability
1/1/2026
Chapter 20: The future of intelligence
1/1/2026
Ending Credits
1/1/2026