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Generative AI
Foundational Model
A large general model trained once and reused across many downstream tasks.
Rather than training a separate model per task, one broadly trained model is adapted many times through fine-tuning, adapters or prompting.
It concentrates both capability and risk: a flaw in the base model propagates into everything built on it, which is the argument for evaluating the base separately from the application.
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