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It also can't really be overstated how helpful it is as an ML engineer to simply spend the time going through thousands of examples yourself. If you abstract yourself away from the data and just "make metric go up" you'll be missing out on valuable insights about how and why your model might be failing.

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It's almost as if (bear with me ...) these "artificial intelligences" actually need "human intelligences" to guide them. Maybe we can think up a "system" where "experts" can codify rules for the "artificial intelligence" to follow.

Ok the sarcasm got too thick but my point is if the engineer has to spend the time to comb thousands of examples then you don't have AI you have a man in a box pretending to be a machine that plays chess.

We have human teachers for much the same reasons.

Are humans just other humans hiding in boxes pretending to play chess?

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