Finally, the previous implementations were very silly! OpenAI had a nice tool, but it only detected their own watermarks, and Google's process was "upload the image to Gemini and ask if it's AI generated", which seemed like a perplexing waste of tokens and breath.
(While a sibling comment points out putting the image through Google Image Search as an alternative, I don't remember this being signposted in the support article I've read, so I unfortunately didn't know about it)
Even Google themselves previously offered a no-auth way (just very niche): if you uploaded an image to Google Image search, and went to "About this image", it would show if the image was Google AI-generated. Now it doesn't.
We need to inform everyone that this technology can encode database identifiers and enough entropy to uniquely identify you as an author (or downloader).
They are not spymarks if they don't encode any personal IDs and are merely used to indicate that an image was AI-generated. I don't think Google or OpenAI use SynthID to include personal data.
It's presumably so they can rate-limit people who are trying to reverse-engineer or otherwise strip it (e.g. iteratively tweaking until it stops getting detected)
How hard can it be to download a set of real images and generated ones in order to train a model to detect and strip the watermark with minimal perceptual difference?
That’s the justification, but the EULA incorporates Google’s regular consumer terms; which means what you upload can also be used for advertising and targeting; and basically any purpose whatsoever by Google.
Yeah I've been wanting to run a ton of Wikipedia images through the detector to see if fakes snuck in. Doesn't seem to be a practical way to do this. Even Open AIs tool has a low rate limit
I've never seen it mentioned anywhere so I will just here complain that Google also removed the ability to paste images into Google Image search some years ago for no apparent reason. It worked great and I used it all the time.
It's a real shame Google isn't more transparent about how it actually works, and doesn't provide any mechanism for classifying images in bulk or offline.
They don't want you to know, because they're the baddies. Imagine how much money they can get from advertisers if they're able to identify every single piece of code, reddit thread, email, GitHub readme that you've ever written based on your secret ID. They're creaming themselves just thinking about it.
"Excellent work acquiring that outlook data Anat, now let's cross check the defunct company emails against YouTube videos edited with Google PrivateEditAI™ to figure out what the social security number of this YouTube account is."
Unfortunately this is the truth, no one can be given a benefit of the doubt because despite years of good grace they have been anti-user and enshittified everything they touch.
I worry we’ll have to approach this the other way around: verify that photos came from a camera, using hardware support like Apple’s Reference Image, rather than try to detect every AI generated one.
In many situations, photos are evidence. AI tools make convincing fakes, such as images of defect product.
Ah but that's the genius of the scheme. Every single one of those providers will detect your secret ID and refuse the request. And sneak their own one in for good measure.
(While a sibling comment points out putting the image through Google Image Search as an alternative, I don't remember this being signposted in the support article I've read, so I unfortunately didn't know about it)
Even Google themselves previously offered a no-auth way (just very niche): if you uploaded an image to Google Image search, and went to "About this image", it would show if the image was Google AI-generated. Now it doesn't.
https://brand.io/article/spymarks/
We need to inform everyone that this technology can encode database identifiers and enough entropy to uniquely identify you as an author (or downloader).
This extends to other forms of media as well.
How hard can it be to download a set of real images and generated ones in order to train a model to detect and strip the watermark with minimal perceptual difference?
The textbox below it says Paste image link, but you can actually paste an image from your clipboard here, too.
URLs expand Googlebot’s indexes; pasted images don’t.
This is the best SynthID write-up I've found so far: https://fyx.me/articles/attempting-model-extraction-of-googl...
It covers how it actually works (probably), and how to train your own classifier for it, with some seemingly decent results.
"Excellent work acquiring that outlook data Anat, now let's cross check the defunct company emails against YouTube videos edited with Google PrivateEditAI™ to figure out what the social security number of this YouTube account is."
> classifying images in bulk or offline
You've described exactly the elements spammers and fraudsters need to be able to defeat this mechanism.
https://help.openai.com/en/articles/8912793-provenance-signa...
There is rate limit though
In many situations, photos are evidence. AI tools make convincing fakes, such as images of defect product.
Or did it just become public
Edit:
Blog post today https://blog.google/innovation-and-ai/models-and-research/go...
https://deepwalker.xyz/blog/evaluating-synthid-watermark-rob...
Hey Gemini, find a synonym for every second adjective. Replace in text.
Hey Grok, find a synonym for every third proper noun. Replace in text.
Hey …
More detail at https://deepmind.google/models/synthid/
For those who, like me, were hoping it was a vision model to identify synthesizer models from photos of concerts and music studios!