Comment on Name & same. :)
Carrolade@lemmy.world 1 month agoThis almost makes me think they’re trying to fully automate their publishing process. So, no editor in that case.
Editors are expensive.
Comment on Name & same. :)
Carrolade@lemmy.world 1 month agoThis almost makes me think they’re trying to fully automate their publishing process. So, no editor in that case.
Editors are expensive.
yamapikariya@lemmyfi.com 1 month ago
If they really want to do it, they can just run a local language model trained to proofread stuff like this. Would be way better
FiniteBanjo@lemmy.today 1 month ago
This is exactly the line of thinking that lead to papers like this being generated.
yamapikariya@lemmyfi.com 1 month ago
I don’t think so. They are using AI from a 3rd party. If they train their own specialized version, things will be better.
FiniteBanjo@lemmy.today 1 month ago
Here is a better idea: have some academic integrity and actually do the work instead of using incompetent machine learning to flood the industry with inaccurate trash papers whose only real impact is getting in the way of real research.
alehc@slrpnk.net 5 weeks ago
That’s not necessarily true. General-purpose 3rd party models (chatgpt, llama3-70b, etc) perform surprisingly good in very specific tasks. While training or finetuning your specialized model should indeed give you better results, the crazy amount of computational resources and specialized manpower needed to accomplish it makes it unfeasible and unpractical in many applications. If you can get away with an occational “as an AI model…”, you are better off using existing models.