Realized I was overtraining my AI model with too much data

I spent 6 months feeding my custom chatbot tens of thousands of support tickets. Last week I tested it on a simple question about shipping times, and it gave me a 3 paragraph essay about warehouse logistics. A buddy who works in ML told me I was basically force-feeding it noise, not signal. Has anyone else hit a wall with too much raw data before?

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kevin_sullivan2h ago

Honestly used to think more data was always better, like you can't have too much of a good thing. Then I trained a model on like 50,000 customer emails and it started writing every reply like it was a legal document, even for simple stuff like "where's my order?" It would go on about warehouse floor layouts and inventory buffers. Totally changed my mind. Now I'm way more careful about picking only the most useful examples and keeping the number smaller.