Pre-training

Pre-training is the process of teaching a machine learning model, like an AI, to understand large amounts of data before it is used for specific tasks. During this phase, the model learns general patterns, language, or features from diverse datasets, much like how a student gains foundational knowledge before specializing. This foundational learning helps the model perform better when it is later fine-tuned for particular tasks, such as translation or answering questions. Essentially, pre-training provides the model with a broad understanding, making it more effective and efficient when applied to specific problems.