In the old world of rule-based systems, machine errors are considered edge cases. What changes when building products with AI, where errors are more common? What if you no longer know if your output is an error?
Managing errors isn't an AI problem that requires reinventing the wheel. It's evolved into a core aspect of product development. A car's engine failure is a lot more critical than, say, a stereo speaker issue.
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