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4min chapter
"Foundation" models
Practical AI: Machine Learning, Data Science, LLM
Is That a Good Parallel?
The idea of having a large base model that's trained in a self supervised way at scale, and used in a variety of downstream tasks is kind of pervasive. And if you get a bug, you know, thinking about the bias and the model or something, it can have fairly substantial consequences as it flows down stream. The name foundation model has also drawn significant attention but i don't know if it's catching on.
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