Users can log in without issues, and authentication appears solid.Despite that, some users can access data they clearly shouldn’t.I’m trying to figure out where authorization is breaking down and how to fix it properly.
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A new column was added to the input data.No one thought it would affect the model.Suddenly, inference started failing or producing nonsense results.This keeps happening as systems evolve.
As usage increased, we started seeing more UNABLE_TO_LOCK_ROW errors. These rarely occurred earlier but are now fairly common during updates and integrations. The logic hasn’t changed much. I want to understand why locking becomes more frequent over time.
Predictions affect business decisions.Stakeholders ask “why” a lot.Raw probabilities aren’t helpful.Trust is fragile.
I trained an object detection model on a mixed dataset containing people, vehicles, and small objects like phones and traffic signs.The model detects large objects such as cars and people very reliably.However, it almost completely ignores smaller objects, ...