[apohn]

>This couldnt be further from the truth.

I think one thing to keep in mind is that there are specific use cases where the cost of using DL isn't worth the improvement in accuracy (if there is one) from a business ROI perspective.

I know somebody who works in the insurance industry on a text classification use case. The business impact of this use case is important as it's used as part of the claims process. The team he's on has tried a lot of different things, but feature engineering + domain expertise + a particular tree ML model has provided the best performance for the lowest overall cost. They are very open to trying new things, but a DL approach simply hasn't been worth it.