[pydry]

I've worked with ML for a while and I wouldnt say that this is the case at all.

ML also didnt replace manual decision making. A lot of previously automated decision making was done with what were basically encoded rules of thumb which didnt overfit much worse than "more advanced" ML models did.

[jncfhnb]

Your personal failure to use ML successfully has no bearing on its wider deployment and success. Overfitting strongly implies that you or whoever was doing it just didn’t know what they were doing.

ML is used everywhere.

[pydry]

Wow, salty :)

How many ML projects for large businesses have you been on?

[jncfhnb]

Dozens. I’m a consultant and it’s what I do. The modeling is very easy. The operational changes are the hard part. Basically any random task of. A sort of maintenance, production, replacement, procurement or scheduling task can save 10-30% with a simple model. There’s a long way to go but this stuff is everywhere.

The world hasn’t even fully realized the productivity value of spreadsheets and email.

[m_rpn]

Email summarizers and such don't count as revolution, sorry.