[pnt12]

>But from the point of view of everyone else, maybe it is fine

I think from a practical perspective, it is fine. You want results and you have a black box algorithm that produces them, fine.

From an academic perspective, AI research is a mess. The reason you try something is not from a logical theory, but due from a "hunch" or replicatinga similar algorithm applied in a parallel area. If it does not work, you change some parameters and run it more times. Still not working so maybe you extend the network to include some more inputs and hope for better results.

I did my thesis in machine learning and was very disappointed with the state of the field.

[caddemon]

I don't think there's necessarily a problem with trying things on a hunch, some of the best results in science have been due to a hunch or even an accident. The problem comes from trying a dozen hunches and only writing up one, or like you say completely cherry picking hyperparameters.