Foundation models is a concept in artificial intelligence referring to large-scale models trained on broad, diverse datasets, designed to be adaptable to a wide range of downstream tasks through methods like fine-tuning or prompting, thereby serving as a foundational layer for numerous specialized AI applications and driving research into generalization, transfer learning, and emergent capabilities.