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Stellar inference speed via AutoNAS
Practical AI: Machine Learning, Data Science, LLM
Is There a Learning Cycle in the Automatic Neural Architecture Search?
i love how you term that, like the efficiency landscape. As you plot this out and explore that space yourself, i'm wondering one way to think about what you're doing is, i'm a data cientist. I've trained my model, now i run it through auto neral architecture search and get out my better model. But i'm wondering if this sort of cycle, as you do that more and more, you start sort of building some intuition as a data scientist or a practitioner to, like, start with a better model in the first place. Do you think there's that sort of feedback and that learning that can happen?
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