[dbecker]

Most of this is true in a strict sense, and it's disappointing that it is presented in such a judgmental way.

Machine learning typically focuses on prediction. There are lots of business problems where prediction is the #1 goal, and ML is great in these circumstances.

Statistics typically focuses on understanding and summarizing data/findings. This is frequently closer to the needs of scientists.

Accepting that classical statistics has contributed more to science than machine learning doesn't make it better. That's like saying "A pipe-wrench is a better tool than a hammer, just ask any plumber."

The fields have a lot of similarities, but different use cases. Most claims that one is "better" come from a tight focus on specific use cases.