[wwright]

I’m not so sure; I think a _lot_ of people would be interested in advanced in non-ML image analysis tech. While ML has been effective for a recent period in industry, it has a number of issues such as intensive training costs, extreme difficulty in fully understanding the behavior of a model (since we can only do experimental verification, and only on behaviors we know to be interesting already), and ethical issues such as unintended gender/racial bias. Just off the top of my head.

I think what you are pointing is really the most toxic part of tech: marketers and investors have found that tech is a good way to aggregate money, and so they have a thrown a lot of funding at tech that can aggregate for them. However, we haven’t actually proven that that tech is the best solution or a sustainable solution. We don’t understand most of what we do with computers very well, we just approximate until it works well enough (for the marketers and investors, of course).

ML and deep learning are very valuable, of course, but their recent market dominance doesn’t indicate that they are the final or most correct solution to the problems they are being used for. It indicates that people want to spend money on it right now.