ML Overhype Criticism
The cluster centers on skepticism and critiques of machine learning's hype, misuse as a universal solution, and limitations, debating its applicability, effort required, and whether every programmer needs it.
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I am not an ML expert, so I cannot respond myself, but I am disappointed at how few responses address the ML aspect of the question.
ML is not science, it's barely math.
The old machine learning for everything answer!ML people need to learn to look into a problem before spouting this sort of stuff.
Interesting. What would be one of those factual statements given your expertise in the area that the ML folks don't understand?
You can rest assured that many people in the ML world are way ahead of you. If ML could be effectively used, it already would be.
ML, while valuable, can be a crutch.
Perhaps you mean monetize instead? They certainly aren't the only ones who can do ML.
Knowing any ML makes it pretty underwhelming.
If you're not trying to build or train new models you are not doing ML.
My guess is you haven't worked anywhere where ML is a part of the core product. think e.g. search and recommendations.