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A foundation model is anymodel that is trained on broad data (generally using self-supervision at scale) that can be adapted(e.g., fine-tuned) to a wide range of downstream tasks; current examples include BERT [Devlin et al .2019], GPT-3 [Brown et al . 2020], and CLIP [Radford et al . 2021].
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Many of these models are described as foundation models. This term, coined in 2021 by researchers at the Stanford Institute for Human-Centered Artificial Intelligence, broadly describes AI models that acquire the capacity to perform well across a range of different problems through a process of ‘pretraining’ on enormous unannotated datasets.
Foundation models build on ChatGPT tech to learn the fundamental language of biology - Nature Biotechnology Michael Eisenstein 2024
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