A useful AI evaluation defines the task, expected behavior, failure thresholds, representative cases, and a decision owner.
Some work is best introduced by the problem it solves before its mechanics are made public. I have been developing a private grading and evaluation system for making model behavior and evidence easier to assess.
I am intentionally keeping the implementation and full method off this site for now. If the right conversation arises at DevDay, I would be glad to demonstrate it to OpenAI leaders who want to examine the approach.
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Follow the references below for more detail, or continue through the Journey, Lab, Research, and Teaching sections.