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. KoolKat23 · 1790432930 · focus · HN ↗

      Benchmarked output quality versus actual output quality are very different things. Some usecases are at the very fringe of model intelligence and depth of intelligence and logic suffers.

      1. Phemist · 1790433410 · focus · HN ↗

         Ofcourse the AI corps are incentivized to downplay the effects of watermarking where they can, as they stand to gain so much from rolling it out (prevent model collapse).

         Also interested in how this watermarking push makes sense when considering RSI.

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