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>"What he's talking about isn't really even AI so much as deep learning: there are lots of other branches that now get virtually no play relative to deep learning."

Can you say what are some of non-Deep Learning branches in AI that aren't getting play relative Machine Learning/Deep Learning?

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Andrew Ng in the linked message said himself: "Maybe you’re training XGBoost on a structured dataset and wondering if you’re missing out on ChatGPT. You may well be onto something even if XGBoost isn’t in the news."

Boosting generally is very competitive with (or better than) neural networks on small to midsized datasets.

Bayesian techniques are always interesting.

Personally I think there are great opportunities linking knowledge engineering approaches (which are very manual-labor heavy) with neural network approaches so we can bridge the taxonomy/unstructured data divide.

Expert Systems /s

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