[D] Identifying problems where ML will not work • r/MachineLearning

I somewhat disagree with your comment, and overall isn't very helpful to be honest. Image Recognition is nowhere near solved and has only shown promise for high accuracy recently due to innovation in model architectures and the availability of highly parallelisable processing. Typically large dimensional data can be understood by ML much better than humans ( and in shorter times). The whole point is that it find these optimisations and discrimination hyperplanes within your data. There is of course an amount of preprocessing which can be done to reduce the dimensionality making the problem easier to solve.