Pre-training and Post-training
Pre-training: The initial phase of training a language model, where it learns by predicting the next word in huge volumes of unlabelled text
- Pre-training allows the model to learn a broad knowledge of grammar, facts, and semantics
Post-training: Additional steps taken after the pre-training phase to adapt the model to specific tasks, such as following instructions or being helpful
- Post-training allows the model to learn the types of responses that humans would like it to produce
- Post-training helps turn predictive power into useful, aligned, and safe behaviour.
Post-training is a core part of the recent success of LLMs, particularly for chatbots.
Social science applications