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The longer answer is that in the context of machine learning use cases, strong assumptions about dataintegrity lead to brittle solutions overall. As the story goes, the general history of DG is punctuated by four eras: “Application Era” (1960–1990) – some data modeling, ?though More Policies Emerged” (2010-2018).
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