Model

A model is the core of an AI system. In simple terms, it is a mathematical structure that learns relationships, patterns, or distributions in data and applies them to new examples. But treating a model as just an “algorithm” is too narrow. Its real value is measured not by laboratory accuracy alone, but by how reliable, consistent, cost-effective, and generalizable it is in real-world use. A strong model does more than fit training data well; it also produces sensible outputs in new situations. For that reason, the concept of a model must be approached not only technically, but also from product, operational, and quality perspectives.