Thread

1. WithinReason · 1790430559 · focus · HN ↗

   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.

   1. lemagedurage · 1790432297 · focus · HN ↗

      That's not true. Watermarks are messing with the next token generation probabilities based on some random seed. The quality is neccesarily lower, the difference is simply too small to notice, typically.

      1. jeremysalwen · 1790434229 · focus · HN ↗

         You have a misunderstanding of how LLM generation works. Before any watermarking gets involved with these models there is ALWAYS a random seed used for generation. For any prompt, some seeds will give better answers, and some will give worse ones.

         Let's say there are four billion possible seeds. There are four billion possible ways we could watermark the generation. We could say "we will choose seed 1, that way we will know exactly what output it produced", we could say "we will choose seed 2, that way we will know exactly what output it produced"... etc etc. Now, if we decide "not to watermark", we STILL must choose a seed. So we are actually still applying one of the watermarks, the only difference is we are not careful to remember which one. Could some seeds give a better or worse answer to some specific prompt? Yes. Could choosing a random "watermark" to apply be better or worse on average than choosing a random seed to apply? No. It's mathematically impossible.

         This is like an open source project changing their seed from "12321" to "43", and saying that because we changed the seed, the quality is "necessarily lower".

         1. lemagedurage · 1790434751 · focus · HN ↗

            We're not simply changing the seed. The LLM provides some probability to tokens, and the SynthID watermarking makes it slightly more likely to choose some and slightly less likely to choose others within that distribution.
         2. odo1242 · 1790439406 · focus · HN ↗

            It doesn’t change the seed; it arbitrarily makes certain tokens more or less likely.

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