In my time developing jet engines I was told a story about how IBM in the early 2000s was paid 10s of millions of dollars to develop a fleet monitoring tool to

In my time developing jet engines I was told a story about how IBM in the early 2000s was paid 10s of millions of dollars to develop a fleet monitoring tool to spot maintenance issue, still a manual task. Over the course of a two year period all operational and development data (since 1980) was fed into a model with all the records of maintenance and issue. IBM came back and said, hey all these issues correspond to this parameter “EOT”… what’s that? EOT stands for “Engine Operating Time”. The insight provided by this model was essentially useless, and their contract was canceled. While ai is very cool, and interesting I think what the author is really saying is “AI” is really naive optimization where the the implementation is really only as good as the practitioners application knowledge. Let’s not forget that at the end of the day Neural Nets are really just overfitting data