[nickpsecurity]

That’s what I thought would happen. Actually, I thought it might be an easy way to get piles of text for LLM training. But we’d have to counter the bias or mostly use that one in highly-positive, enthusiastic applications. I did have a partial solution.

Look at WizardLM Uncensored: https://www.reddit.com/r/LocalLLaMA/comments/1384u1g/wizardl...

The author just deleted from the training data content with specific words likely to bias it. The test afterwards showed it worked. Reusing their concept, I think we could just remove or edit for honesty common words and phrases in marketing material. You’ve given some good examples.

We could also do that for “scientific” papers which oversell their results. Or anything else where what’s presented as certain is modified to say source(s) X claimed Y. Foundational materials, which trainers vet for quality, would get a lot more training runs before, during, and after riskier material.

I think there’s a lot of potential here by just trimming the fat out of otherwise useful documents. The LLM’s we build to support the work might also become great, lie detectors.