[coverup]

Yeah this is where it would have helped if I had discussed what I meant by "new".

AlphaGo is a supervised learner that outputs optimal Go moves given opposing play. It yields new discoveries in the same sense that a model designed to predict mechanical failures from labeled sensor data would: I didn't know what the model was going to predict until it predicted it, and now I know.

But what the factory owners want is a machine that can take raw, unlabeled sensor data and predict mechanical failures from that. They want insights. "Why not just feed all our data into the model and just see what comes out?" they ask. "I don't see why we need to hire at all if we have this neural net."

The reason you need a human somewhere in the system if you want insights is because someone needed to program AlphaGo specifically to try to win at Go. At the factory, someone needs to tell the machine what a mechanical failure is, in terms of the data, before it can successfully predict them.

Then, neither "winning at Go" nor "mechanical failure" are states that the system hasn't already been programmed to recognize. That's what I mean when I say a supervised learner cannot generate "new" output.