Short version: it's likely a SynthID style statistical watermarking scheme that Anthropic is using. There's likely no hidden unicode and no large stable green/red scheme.
Longer version: I found some really statistically significant outcomes when using Gloaguen et al.’s (https://www.sri.inf.ethz.ch/blog/probingsynthid) detection algorithm for SynthID, though unfortunately it seems like the models might be pre-biased to pass that test already. The difficult thing is that it's hard to conclusively know which models definitely already have watermarking enabled and if there are any models that don't have watermarking, which means that being able to get a highly positive statistical result is much harder.
You can take a look at the full writeup, but many of the clues from Anthropic's blog post, plus negative results on many of the simpler tests, point to them using such a scheme. Of course, it's possible that they came up with a novel new scheme/algorithm, but amongst the available literature, the SynthID family of models is probably the best bet.
Short version: it's likely a SynthID style statistical watermarking scheme that Anthropic is using. There's likely no hidden unicode and no large stable green/red scheme.
Longer version: I found some really statistically significant outcomes when using Gloaguen et al.’s (https://www.sri.inf.ethz.ch/blog/probingsynthid) detection algorithm for SynthID, though unfortunately it seems like the models might be pre-biased to pass that test already. The difficult thing is that it's hard to conclusively know which models definitely already have watermarking enabled and if there are any models that don't have watermarking, which means that being able to get a highly positive statistical result is much harder.
You can take a look at the full writeup, but many of the clues from Anthropic's blog post, plus negative results on many of the simpler tests, point to them using such a scheme. Of course, it's possible that they came up with a novel new scheme/algorithm, but amongst the available literature, the SynthID family of models is probably the best bet.