Just spent 3 hours debugging an AI model that kept failing. The problem? Not the code. Not the data. It was my own assumptions. We're rushing to deploy AI without asking the basic questions:
– What problem are we actually solving?
– Who benefits from this?
– What happens when
Debugging an AI Model Can Require Reexamining Deployment Assumptions
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