Personally I haven't looked into the AIG fields above, however it appears "obvious" that layered "hybrid" approaches will be fundamentally more useful than eith

Personally I haven't looked into the AIG fields above, however it appears "obvious" that layered "hybrid" approaches will be fundamentally more useful than either deep learning or expert systems alone. In that context the article doesn't seem light on details to me since it's primarily advocating layered approaches and I think there are only limited set of layered approaches that would be useful. Why would a practicioner in AI not agree with a hybrid approach being necessary is what I'm wondering. Are there arguments supported with theory or evidence to the contrary? The definition from Wang makes sense. How does AIG differ from other methods? For example, I noticed this article on Bayesian Program Learning a few days ago which IMHO takes a layered approach and is based on human learning models. [https://news.ycombinator.com/item?id=10723485 https://news.ycombinator.com/item?id=10723485] Interestingly there were no comments on it. Could you post refs to some the relevant publications your published opinions? I'm curious about your approach!