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I’m guessing for more embedded, low power, or real time applications you’d still need to train a model?

I’d imagine you wouldn’t have the resources to run a souped up foundation model?

Thanks for your question. You are right, current vision-language foundation models are quite heavy. However, for example in NLP there are some works on smaller foundation models. In addition, you could also use a foundational model to help train your smaller model or label more data.

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