Comment by teddyknox | Hacker News Reader

Comment by teddyknox | Hacker News Reader

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> The thing I would like to get working is telling the net "here is a ton of different buttons, grids, lists and a lot of other UI stuff, and there are all our products - I want to maximize revenue - do whatever you like to get there".

As you referenced in your footnote, this goal is a little like the goal of putting a man on the moon, if the year is 1900. One could the make the case that something resembling an AGI agent would be needed to design/manage a merchant website with any degree of introspection and customizability. Your machine would need to understand business objectives, UI patterns, aesthetics, etc before taking the helm, and these things take years to learn even for even humans. This is not to say that AGI isn't an admirable goal, but that it's an obvious one, just as I imagine reaching the moon was in the centuries leading up to 1969.

Scientific research is certainly a massively parallel effort, pushing the boundary of our knowledge in many different direction at once, but rest assured that there are many good men and women working in this specific direction.

(also know that I have a lot of respect for this kind of vision-oriented thinking, especially because it generally leaves the writer vulnerable to criticism like this)

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.

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.

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