Once we solve AutoML, the automated creation of machine learning pipelines, we can move on to focus on the art of loss function engineering
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I think in many areas the loss function is easier (and in others it's insanely hard). Does automl include feature engineering?
I think people are limiting themselves to poor problem specifications (e.g. image classification vs. "vision") bc the ML part is hard enough
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If the ML part wasn't a concern, we would suddenly discover that there are no simple problems, with simple loss functions
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