Transformer Model

Transformers became the foundation of most modern large language models because they can process context efficiently and scale to very large datasets and parameter counts. Variants are also used in vision, audio, multimodal systems, and other machine-learning tasks. The concept matters when teams build production generative-AI applications that need reliable context, controlled outputs, evaluation, and connections to business data.