Live data from Hacker News

OpenAI Adopts Google's SynthID Watermark for AI Images with Verification Tool

openai.com

21–30 of 198 posts

Re: OpenAI Adopts Google's SynthID Watermark for AI Images with Verification Tool

#21

Good. Despite people saying it will be removed, I have seen no reproducible repo demonstrating it.

Stable Diffusion with 10%~15% denoising strength. Done. I tested the day 1 when Nano Banana Pro was released and it worked. It still works today for Nano Banana 2. I didn't post this anywhere because I (arrogantly) thought saying it publicly would make the internet worse. But it was pure arrogancy: if I came up with this the first day then of course other millions of programmers did too. That being said, it'll introd…

Post a repro. I can do that too but then the similarity index is weak. The point is that it it looks indistinguishable then the integrity persists.

In my tests the image looks clearly distinct. In other words, if you can tell the difference then it isn’t a good test.

Re: OpenAI Adopts Google's SynthID Watermark for AI Images with Verification Tool

#22
What information is included in the metadata or SynthID? How many bits can be encoded in a SynthID?

Can it be used to create something like nutritional labels for synthetic content? 10% synthetic text, 30 synthetic images.

Your reality was 15% synthetic today (75% mega corp, 25% open-weight neocloud).

Re: OpenAI Adopts Google's SynthID Watermark for AI Images with Verification Tool

#25

While these are great, isn’t the problem that malicious actors will create systems that do not use synthID

It helps significantly in the current moment. A lot of people are lazy and are getting caught quickly by SynthID.

Eventually it won’t matter when image generation is cheap. But few self-host today and few are willing to pay unsubsidized prices, so the vast majority are using the Gemini, OpenAI, and Midjourney. If all 3 adopted SynthID, only a small fraction would use something else.

Re: OpenAI Adopts Google's SynthID Watermark for AI Images with Verification Tool

#26

While these are great, isn’t the problem that malicious actors will create systems that do not use synthID

It helps significantly in the current moment. A lot of people are lazy and are getting caught quickly by SynthID. Eventually it won’t matter when image generation is cheap. But few self-host today and few are willing to pay unsubsidized prices, so the vast majority are using the Gemini, OpenAI, and Midjourney. If all 3 adopted SynthID, only a small fraction would use something else.

[deleted]

Re: OpenAI Adopts Google's SynthID Watermark for AI Images with Verification Tool

#27

I'm annoyed that Google is keeping it closed-sourced and limited to partners. Is there a negative externality about open-sourcing image watermark technology so anyone can use it and audit the watermarks independently? If not, then I may have a repository for an open-source invisible and tamper-resistant image watermarking approach that's feature complete...

potentially to stop bad actors from poisoning datasets by just adding the filter to real pictures?

Re: OpenAI Adopts Google's SynthID Watermark for AI Images with Verification Tool

#28

Is there no way to do this without uploading it?

I'd built an on-device app for detecting C2PA and IPTC metadata in images, amongst other things. I might be able to add support for SynthID detection once it's been reverse engineered.

Re: OpenAI Adopts Google's SynthID Watermark for AI Images with Verification Tool

#30

Earlier quoted context omitted.

Stable Diffusion with 10%~15% denoising strength. Done. I tested the day 1 when Nano Banana Pro was released and it worked. It still works today for Nano Banana 2. I didn't post this anywhere because I (arrogantly) thought saying it publicly would make the internet worse. But it was pure arrogancy: if I came up with this the first day then of course other millions of programmers did too. That being said, it'll introd…

Yup, OOC a while back I put together a ComfyUI node that took in a NB image and start with the smallest amount of denoise strength using Flux.1 (but works with any model), then run img2img with a synthid check incrementing denoise in a loop until it was defeated. Never released it, but it was obvious to most people in the SD community that denoising using a diffusion model was a relatively trivial means to beat most…

Yet is in itself fairly trivial to detect assuming you use some open-weight image model as a base.
Post reply on HN