Foundation Model
Core ConceptsA large AI model trained on broad data at scale that can be adapted for many different downstream tasks.
Full Explanation
The term was coined by Stanford's Center for Research on Foundation Models in 2021. Foundation models (GPT-4, Claude, Gemini, LLaMA) are trained once at enormous scale, then fine-tuned or prompted for specific applications. The 'foundation' metaphor captures that these models form the base layer for thousands of AI applications built on top.
Related Terms
A type of AI model trained on vast amounts of text data that can generate, summarize, translate, and reason about language.
Further training a pre-trained AI model on a smaller, task-specific dataset to specialize its behavior.
The neural network architecture that underpins all modern large language models, introduced by Google in 2017.