[ehq]

Nice! I noticed that Bard allows you to see drafts it made prior to selecting its final response and I kind of wanted chatGPT to do the same.

This is not just useful to reduce hallucinations or improve reliability in general, but also you could get as precise and specific as you want with the criteria to select the winning draft, which is something you can't control with Bard either. You could also extend this idea by then having another model extract and combine the best aspects out of each draft and so on.

This seems like a pattern / approach that would also be particularly great for cases where the output from the LLM has to be precise to be useful, such as writing code.