31–40 of 71 posts
Why would you want to watermark your content - generally watermarks are used to provide legal proof of provenance which can be important when suing someone for stealing your content but since machine learning outputs cannot be copyrighted this use is not important.
Why would you want to watermark your content - generally watermarks are used to provide legal proof of provenance which can be important when suing someone for stealing your content but since machine learning outputs cannot be copyrighted this use is not important.
I don't believe this in practice, a person will just say that they did it rather than the AI
Why would you want to watermark your content - generally watermarks are used to provide legal proof of provenance which can be important when suing someone for stealing your content but since machine learning outputs cannot be copyrighted this use is not important.
Why would you want to watermark your content - generally watermarks are used to provide legal proof of provenance which can be important when suing someone for stealing your content but since machine learning outputs cannot be copyrighted this use is not important.
This is very much unexplored and unsettled territory in most jurisdictions, both judicially and legislatively. I would refrain from making such authoritative statements for now.
Why would you want to watermark your content - generally watermarks are used to provide legal proof of provenance which can be important when suing someone for stealing your content but since machine learning outputs cannot be copyrighted this use is not important.
You know that thing i want from your large language model? I just submitted my query for it in Finnish, Japanese, Russian, Hebrew, German, French, Latin, Farsi, Basque, and English. plus a few dozen more for good measure and to cover the linguistic landscape Is there any reason to believe watermarking LLMs will hold up in this scenario?
But I think even simple watermarking probably has value; consider a corporate context in which the corporation itself may want to monitor and know what proportion of the code, content, or work product is AI-generated. In that setting, fairly simple markers would allow at least a rough estimate or indication, although they'd have the converse problem of not necessarily indicating places where humans did some hand-editing of the output.