Foundation models are large-scale models trained on diverse, unlabeled data using self-supervision. They serve as a base that can be fine-tuned for specific tasks. Examples include GPT-4, Claude, Llama, and Stable Diffusion. The term was coined by Stanford researchers to emphasize how these models form the foundation for many AI applications.
Foundation Model
A large AI model trained on broad data that can be adapted to a wide range of downstream tasks.
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