Foundation Models
Large-scale models trained on broad data for many tasks.
Definitions (4)
Foundation Models are large-scale AI models trained on broad and diverse datasets that can be adapted or fine-tuned for a wide range of downstream tasks, characterized by general-purpose capabilities and broad applicability.
Large-scale models trained on broad, diverse datasets that can be fine-tuned or adapted for many downstream tasks and use-cases; the guides highlight their generality, adaptation risks, and implications for procurement and governance.
Models trained on broad, general-purpose data that can be adapted for many downstream tasks (foundation or general‑purpose models); the draft law treats these with specific model‑level obligations when system‑level risk arises, including transparency, monitoring, and mitigation measures.
Large-scale AI models trained on vast and diverse datasets that serve as a base for a wide range of downstream tasks, including generative applications, and can be fine-tuned or adapted for specific uses.
Related Terms
Foundation models / Frontier AI
Highly capable, general-purpose AI models with broad applicability....
Large/fundamental models
AI models (≥1 billion parameters) serving as bases for many tasks....
Foundational Model
Large-scale model adaptable to multiple downstream tasks....
Dual-Use Foundation Model
Large foundation model with potential civilian and national security applications....
General Purpose AI (Foundation Models)
Large foundation models usable across multiple tasks and domains....