A large language model is never sat down and taught facts. It learns by predicting the next token across a mountain of text, then gets reshaped twice more until it behaves like the assistant you talk to. That is how LLMs are trained: pretraining, supervised fine-tuning, and preference tuning. This post walks all three stages in plain words, with small Python you can run yourself. “The computer was born to solve problems that did not exist before.” Bill Gates Last ... Read More