[sapphireblue]

IMHO talking about AGI here sounds like "all or nothing" type of thinking. Almost all problems can be formulated as [perhaps very hard] machine learning problems of 3 basic types https://en.wikipedia.org/wiki/Machine_learning#Types_of_prob... .

Every ML problem has a lot of algorithms that can be applied to it to solve it. Previously unsolvable problem (e.g. learning playing atari game from pixels) can become solvable if a better ML algorithm is devised, more compute power is applied, or the problem is simplified (maybe with data augmentation or feature engineering, or constraining the domain).

I think the problem you are stating - finding the best configuration of website to extract more ad revenue - can be simplified until it is solvable by currently available algorithms and hardware. Big companies are already doing similar things - Google uses reinforcement learning to recommend new items on its services, Facebook is known to use machine learning to somehow make more profit from users.

Given expert knowledge of the problem and good algorithms, it can be solved in some form, that's my point here.

[teddyknox]

Sure. I think what the OP was playing around with was whether we could generalize from, as you said, "expert knowledge of the problem[s] and good algorithms" so that AI could replace components in the incumbent programming paradigms. Agreed, when the end problem is well-defined and you know how "do" machine learning, the world is your oyster.