Trained on buggy code, LLMs often parrot same mistakes
www.theregister.com
: One more time, with feeling ... Garbage in, garbage out, in training and inference

Researchers have found that large language models (LLMs) tend to parrot buggy code when tasked with completing flawed snippets.

That is to say, when shown a snippet of shoddy code and asked to fill in the blanks, AI models are just as likely to repeat the mistake as to fix it.

  • IphtashuFitz@lemmy.worldEnglish
    2·
    15 hours ago

    We have a handful of Python tools that we require to adhere to PEP8 formatting, and have Jenkins pipeline jobs to validate it and block merge requests if any of the code isn’t properly formatted. I haven’t personally tried it yet, but I wonder if these AI’s might be good for fixing up this sort of formatting lint.