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You can lead in (2) with good enough (1).

Being a leader in (1) does not mean you'll be good at (2), and vice versa.

There's also a difference between limited data and good enough data.

If you train on good enough data, you can have good enough models.

If people believe the focus of AI/ML should just be precision/recall, or other measures of accuracy, and having tons of data, they're missing many other areas and elements for what make AI/ML successful in application.



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