A trained system that maps input to output through learned patterns. In research practice usually a large language model, but the term also covers image, audio, and multi-modal systems.
Definition: A trained system that maps input to output through learned patterns. In research practice usually a large language model, but the term also covers image, audio, and multi-modal systems.
A trained system that takes input and produces output through learned patterns. In current research practice the term usually means a large language model, but it also covers image, audio, and multi-modal systems. Different versions of the same named model produce different outputs, which is why model version transparency matters for reproducibility.
An AI system trained on vast amounts of text to predict and generate human-like language. Best understood as a concept-transformation engine rather than a knowledge database.
A general-purpose model trained on a broad corpus, used as the base layer for downstream products. Most consumer AI features are a foundational model with a UI wrapper.
A model whose weights are publicly downloadable, runnable on your own infrastructure. Not the same as fully open source: training data and code may still be closed.