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Comment by tokioyoyo | Hacker News Reader

Correct me if I’m wrong, but wouldn’t it simply drive people to use LLMs that are not watermarking their content?

I think your idea is basically right, but there are two points to consider:

- Your hypothesis only holds if the alternative LLM is also "sufficiently good". If Gemini does not stay competitive with other LLMs, Google's AI plans have a much more serious problem.

- Your hypothesis assumes that many people will be capable of detecting the watermarks (both of Gemini and other LLMs) so that they can make a conscious choice for another LLM. But the idea behind good watermarking is that it is not that easy to detect.

According to the article, you can just have another LLM summarise Gemini's watermarked output and that will "likely" defeat the watermark detection.

But, if all the good models can only be trained by large mega corps with close connections to the government, it's only a matter of time until that other LLM will just add its own watermark.

You could probably use much smaller model for such rewriting

Why does the user care if its watermarked? Surely there are only some use cases for this stuff where it matters. Most of the time isn't it just people having ephemeral chats where this wouldn't matter?

Using LLMs to write your essays and reports for school or uni, in a way that could get you punished if caught, is a reasonably big use case.

I see no scenario where there won’t be an LLM that is deliberately tailored for that purpose, possibly even built by an “intel” agency for the very purpose of having blackmail over someone that may become useful later in their career.

Agreed its probably a big use case in general, but like token per token I bet its relatively small! How many big papers do you have to write a semester? Even if its four, that's nothing compared to the everyday use you will make of it.

Sure, but institutions and regulators care about this issue, and at least making some attempt to address it will make them slightly happier.

AIs and LLMs have an extremely uphill PR battle to fight right now. Anything that is deemed AI generated is assumed to be borderline trash (lots of exceptions, but you get the point). So, I can see that if someone uses LLM to generate text, they don’t want it to be marked as “low effort content”.

There are definitely exceptions, and that there are maybe proves that it is less Anti-AI prejudice at play and more just reacting to things that are indeed trashy. It just so happens a lot of it today is from AI I think (for, I hope, obvious reasons).

Just to say, maybe give it a little time, but a watermark like this is not going be thing that decides someone's reaction in the near future, just what it says. (I am just betting here).

But its going to be an uphill battle either way if you are really getting the model to write everything, I do not envy that kind of project.

People use Google Search despite it being littered with adverts and tracking. Maybe Google are counting on either being better than the competition despite watermarking, or simply accepting that people who don't care are enough of a market that it's still worth adding.

Agreed, that's the obvious prediction. They're also going to perform worse on 3p benchmarks right?

If Google locks in enterprise clients using Google Workspace to Gemini then they won't really have a choice. It is selling it as an "add-on" already: https://workspace.google.com/solutions/ai/#plan

Suffice to say it is evident that no other LLM will come close in integration with Google Docs and other Workspace apps as Gemini.

Correct me if I'm wrong, but watermarking is only possible, if the model has a limited set of input you can provide (affects for the output) and a limited set of output it produces, and it should be completely deterministic. And you should pre-calculate all possible combinations.

And this should be also the case for every possible LLMs; then you can compare which LLMs could produce which outputs based on what inputs. Then there is some certainty that this output is produced by this LLM and this another LLM might produce it as well with these inputs.

So... impossible?

People made this same argument about DRM escalations, about increasing privacy violations in the browser, and about Google's donations to support climate change misinformation. Even about Facebook interface redesigns. Every variation of "people will be driven to do X" I've ever heard assumes some coherence and unity of collective purpose that rarely matches the reality of how people behave.

There are counter examples, e.g. Unity. But catching that lightning in a bottle is rare and merits special explanation rather than being assumed.

Using LLMs in exams and homeworks has a different driver. Getting caught results in punishment, so using alternative would be better. None of the aforementioned examples have a “stick” aspect to it when you stick to Google.

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