training

Training a large language model is not a single act — it is a five-stage industrial process that begins with petabytes of scraped text, passes through weeks of GPU computation consuming millions of dollars of electricity, and ends with a model that can hold a coherent conversation. Each stage has a specific job, a distinct failure mode, and a measurable cost. Here is how the whole pipeline works, from raw data to deployed product.

Training and inference are two fundamentally different computational processes. Understanding the distinction explains most of how AI systems work and cost.