This is getting tiring. Watermarking has no effect on model output quality when implemented correctly. It's somewhat like swapping a random RNG seed to the seed 42, and detecting what the seed was from a random sequence. The sequence generated from the seed 42 is just as random as any other seed. There couldn't be a quality difference. And yes, the output from an LLM is a conditional random sequence of tokens from a distribution determined by a model.
Model companies are doing this for themselves anyways, it’s so they don’t feed generated content back into the slopper and collapse the model. From that angle it over time contributes to better model quality.
Watermarking sounds like a good idea, but it's not. Token drift from watermarking will degrade the quality of outputs and could allow clever people to circumvent guardrails.
You should assume all text is AI generated. If you want to "test" someone at school or during an interview, have them write with a pencil and paper.
You should assume all text is AI generated. If you want to "test" someone at school or during an interview, have them write with a pencil and paper.