LLM inference already isn't deterministic, the watermarking technique only limits the space of possible random seeds. There is no reason to believe that this subset of seeds somehow produces lower quality output.

Is this 'best word' with us in the room right now?

Posting for visibility a reminder that this type of watermarking is comically easy to beat. See Scott Aaronson's 2023 research in which he coined the term "pineapple attack": one must simply prompt the model to add the word "pineapple" after every other word and then do a search + replace to remove the word, to obliterate the watermark altogether.

https://www.youtube.com/live/2Kx9jbSMZqA?si=0QgCPBX2_KPZ0QTU...

So the watermark can be removed by rearranging words and choice of words. This seems trivial to bypass with a local model. If I understand this correctly.

It's good to be the King.

And what I mean by that is that companies that are at the top tend to make anti customer decisions because they have lost the concept that pleasing customers matters as priority one.

Watermarks are context poisoning.

Gruber was a good voice in the industry but this article misses the mark in a lot of ways.

A company the size of Anthropic would not voluntarily jeopardize their massive valuation if they didn’t feel the resulting output would maintain a similar level of quality as before. Is there a similar worry that their system prompt, which is injected at the start of every conversation also influences token generation in an artificial way?

If regulation will ruin Claude as a product, market forces will fill the void. There are also a ton of open weight models to choose from. It’s going to be okay.

It's no more a perversion of writing than the act of using an LLM to write in the first place.

If you don’t like it don’t use it