Then you could send these out in a coordinated fashion to identify which group, if not person, is leaking.
The message says that they will find the leaker, but I doubt it (of course this is from 2010, so if they were found they have been for a while now).
> we watermark all the model outputs using the method described in Kirchenbauer et al. 2023, so that others can detect (with some probability) whether an output comes from Alpaca 7B
https://arxiv.org/abs/2301.10226
> We propose a watermarking framework for proprietary language models. The watermark can be embedded with negligible impact on text quality, and can be detected using an efficient open-source algorithm without access to the language model API or parameters. The watermark works by selecting a randomized set of "green" tokens before a word is generated, and then softly promoting use of green tokens during sampling. We propose a statistical test for detecting the watermark with interpretable p-values
Post-truth is the era where nothing is attributable to a human because of AI interventions, and liability is shielded at every level because of it. It's insane.