Training
The expensive process that sets a model's parameters by exposing it to data.
Training runs the model over a huge corpus, measures how wrong it was, then nudges every parameter slightly in the direction that would have made the answer better. Repeat that across trillions of tokens and the parameters settle into something that captures language and much of the world's factual patterns. The cost is why only a handful of companies can train frontier models, and why almost everyone else fine-tunes someone else's.
Related terms
Parameters
The learned numbers inside a model. Their count is the model size.
Inference
Running a trained model to produce an answer. What happens on every request.
Fine-tuning
Further training of an existing model on your own data to shape its behaviour.
Dataset
A collection of examples used to train, evaluate, or ground a system.
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