A junior tester's comment about my AI output made me rethink my validation process

Last month at work, I was showing off this new generative model that writes product descriptions for our ecommerce clients. Everyone was impressed until this junior tester pointed out that one output had a factually wrong shipping date, and she said the model was just making things up. I got defensive at first, but then I looked closer and she was right, the confidence score said 97% but the date was completely fabricated. I spent the next two weeks building a fact-checking layer that cross-references every claim with our internal databases before anything goes live. Has anyone else dealt with their AI sounding too confident when it's actually wrong?

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jordan_patel5920d ago

Damn, 97% confidence and it just flat out made up a date? That's wild how these models can be so sure about stuff that's completely fake. Good call on building that fact-check layer, sounds like a total game changer.