Lesson 3 of 6
How AI Models Are Trained
Models learn in stages — pretraining, fine-tuning, RLHF — from huge amounts of text. This lesson shows where their abilities and blind spots come from.
Learning objectives
- ▸Outline the three stages of training an LLM.
- ▸Explain what training data is and where it comes from.
- ▸Explain why a trained model is frozen at a knowledge cutoff.
The lesson
Read the full lesson →How Are AI Models Trained?AI models are trained in stages — large-scale pretraining on text to learn language, then fine-tuning and reinforcement learning from human feedback (RLHF) to make them helpful, honest, and safe to use.3 min readKey takeaways
- ▸Pretraining (learn language) → fine-tuning (follow instructions) → RLHF (be helpful & safe).
- ▸Training data is trillions of tokens from the web, books, code, and licensed sources.
- ▸Training is a frozen snapshot — built-in knowledge stops at the cutoff date.
Knowledge check
Knowledge check
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1. Which is the correct training order?
2. What is RLHF for?
3. Why can a model be confidently out of date?