What's the difference between pre-training and fine-tuning?

Pre-training builds the base model from scratch on enormous general text to learn language and world patterns — hugely expensive, done by frontier labs. Fine-tuning takes that pre-trained model and trains it further on smaller, task- or domain-specific data to specialise it (including instruction-tuning and RLHF that make base models good at following instructions). Pre-training gives broad capability; fine-tuning shapes it toward specific behaviour.