3 ms·

Looks like a good use case for LLMs! https://chatgpt.com/share/67538beb-73e8-800a-b602-fe26b131e543 https://chatgpt.com/share/67538beb-73e8-800a-b602-fe26b131e

• mkl 2y ago
  Hardly. That just threw away Edit1, failing to follow instructions even in this very simple case.
• tags2k 2y ago
  o1 gets the original article question correct: https://chatgpt.com/share/675410c1-22c4-8001-b36a-24425127cc10 https://chatgpt.com/share/675410c1-22c4-8001-b36a-24425127cc...
• antics 2y ago
  Author here! We have experimented with building this, see my comment elsewhere here: https://news.ycombinator.com/item?id=42348651 https://news.ycombinator.com/item?id=42348651 One of the surprising things is that LLMs regularly "fix" things that no other system can fix. Like if we both add the same sentence to a doc. It's interesting stuff. With that said I am not sure that this specific LLM is providing the "right" answer. It seems like AN answer! But I think the real solution might be to ask the user what to do.
• sausagefeet 2y ago
  Take what you wrote and flip it and you get a different answer: https://chatgpt.com/share/67542c95-fea8-8008-8749-7b7daf355c54 https://chatgpt.com/share/67542c95-fea8-8008-8749-7b7daf355c... Here is the resulting semantically meaningful diff that reconciles the edits: - The color of orange is orange + The colour of orange is orange This reflects the change in spelling from "color" to "colour," which is the only meaningful difference between the two edits.