We are also entering the age of "hey AI, take this repo, reimplement the same functionality".
Now, no LLM is currently anywhere near doing that for ElasticSearch.
But for a project with 4845 lines of Python code? (as per tokei)
Definitely doable, with a bit of handholding and manual fixing.
Would that be a derivative work? Maybe, but that would be a hard legal battle.
> Now, no LLM is currently anywhere near doing that for ElasticSearch.
You could probably feed all of ElasticSearch into an LLM and ask it to "reimplement it" successfully. But why would you even bother? There's already an existing open-source alternative called OpenSearch [1].
> We are also entering the age of "hey AI, take this repo, reimplement the same functionality".
Wouldn't you do this just against the/an API documentation? Interesting thought.