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Koller: AI requires synthesizing deep learning with causal and interpretable modeling

Daphne Koller · No Priors Ep. 46 | Best of 2023 with Sarah Guo and Elad Gil · Jan 11, 2024 · at 12:38

Daphne Koller was not on this episode. A recording of them was played into it, so these are their words but not an appearance on No Priors. It still counts as said, and it is kept out of every score on their page.

Daphne Koller, founder and CEO of insitro and machine learning pioneer, explains why purely end-to-end deep learning is insufficient for clinical applications without causal reasoning and interpretability.

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“What I think we're starting to see right now is a the pendulum starting to swing back in the sense that there is a greater understanding that you really need a bit of both. You need that hugely powerful pattern recognition that we get from deep learning, but you also need the ability to reason about things like causality, and you also need some interpretability of your deep learning models so that you can potentially convey to a clinician why you made the decision that you did. And so what we're ending up with as a really powerful Paradigm is some kind of synthesis of the ideas from both of these disciplines coming together.”

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