Monday, February 2, 2026

Watermarking AI-generated textual content and video with SynthID

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Saying our novel watermarking technique for AI-generated textual content and video, and the way we’re bringing SynthID to key Google merchandise

Generative AI instruments — and the big language mannequin applied sciences behind them — have captured the general public creativeness. From serving to with work duties to enhancing creativity, these instruments are rapidly turning into a part of merchandise which might be utilized by tens of millions of individuals of their every day lives.

These applied sciences will be massively useful however as they develop into more and more in style to make use of, the chance will increase of individuals inflicting unintentional or intentional harms, like spreading misinformation and phishing, if AI-generated content material isn’t correctly recognized. That’s why last year, we launched SynthID, our novel digital toolkit for watermarking AI-generated content material.

Right now, we’re increasing SynthID’s capabilities to watermarking AI-generated textual content within the Gemini app and web experience, and video in Veo, our most succesful generative video mannequin.

SynthID for textual content is designed to enhance most widely-available AI textual content technology fashions and for deploying at scale, whereas SynthID for video builds upon our image and audio watermarking method to incorporate all frames in generated movies. This progressive technique embeds an imperceptible watermark with out impacting the standard, accuracy, creativity or velocity of the textual content or video technology course of.

SynthID isn’t a silver bullet for figuring out AI generated content material, however is a crucial constructing block for growing extra dependable AI identification instruments and can assist tens of millions of individuals make knowledgeable choices about how they work together with AI-generated content material. Later this summer time, we’re planning to open-source SynthID for textual content watermarking, so builders can construct with this know-how and incorporate it into their fashions.

How textual content watermarking works

Giant language fashions generate sequences of textual content when given a immediate like, “Clarify quantum mechanics to me like I’m 5” or “What’s your favourite fruit?”. LLMs predict which token more than likely follows one other, one token at a time.

Tokens are the constructing blocks a generative mannequin makes use of for processing data. On this case, they could be a single character, phrase or a part of a phrase. Every potential token is assigned a rating, which is the proportion probability of it being the best one. Tokens with increased scores are extra doubtless for use. LLMs repeat these steps to construct a coherent response.

SynthID is designed to embed imperceptible watermarks instantly into the textual content technology course of. It does this by introducing extra data within the token distribution on the level of technology by modulating the chance of tokens being generated — all with out compromising the standard, accuracy, creativity or velocity of the textual content technology.

SynthID adjusts the chance rating of tokens generated by a big language mannequin.

The ultimate sample of scores for each the mannequin’s phrase selections mixed with the adjusted chance scores are thought of the watermark. This sample of scores is in contrast with the anticipated sample of scores for watermarked and unwatermarked textual content, serving to SynthID detect if an AI instrument generated the textual content or if it would come from different sources.

A chunk of textual content generated by Gemini with the watermark highlighted in blue.

The advantages and limitations of this system

SynthID for textual content watermarking works greatest when a language mannequin generates longer responses, and in various methods — like when it’s prompted to generate an essay, a theater script or variations on an electronic mail.

It performs properly even beneath some transformations, equivalent to cropping items of textual content, modifying just a few phrases and delicate paraphrasing. Nonetheless, its confidence scores will be enormously decreased when an AI-generated textual content is totally rewritten or translated to a different language.

SynthID textual content watermarking is much less efficient on responses to factual prompts as a result of there are fewer alternatives to regulate the token distribution with out affecting the factual accuracy. This contains prompts like “What’s the capital of France?” or queries the place little or no variation is anticipated like “recite a William Wordsworth poem”.

Many at the moment obtainable AI detection instruments use algorithms for labeling and sorting information, referred to as classifiers. These classifiers usually solely carry out properly on specific duties, which makes them much less versatile. When the identical classifier is utilized throughout various kinds of platforms and content material, its efficiency isn’t at all times dependable or constant. This will result in a textual content being mislabeled, which might trigger issues, for instance, the place textual content is likely to be incorrectly recognized as AI-generated.

SynthID works successfully by itself, nevertheless it may also be mixed with different AI detection approaches to offer higher protection throughout content material varieties and platforms. Whereas this system isn’t constructed to instantly cease motivated adversaries like cyberattackers or hackers from inflicting hurt, it can make it harder to use AI-generated content for malicious purposes.

How video watermarking works

At this yr’s I/O we introduced Veo, our most succesful generative video mannequin. Whereas video technology applied sciences aren’t as broadly obtainable as picture technology applied sciences, they’re quickly evolving and it’ll develop into more and more necessary to assist folks know if a video is generated by an AI or not.

Movies are composed of particular person frames or nonetheless photos. So we developed a watermarking method impressed by our SynthID for picture instrument. This system embeds a watermark instantly into the pixels of each video body, making it imperceptible to the human eye, however detectable for identification.

Empowering folks with information of after they’re interacting with AI-generated media can play an necessary position in serving to forestall the unfold of misinformation. Beginning as we speak, all movies generated by Veo on VideoFX might be watermarked by SynthID.

SynthID for video watermarking marks each body of a generated video

Bringing SynthID to the broader AI ecosystem

SynthID’s textual content watermarking know-how is designed to be appropriate with most AI textual content technology fashions and for scaling throughout totally different content material varieties and platforms. To assist forestall widespread misuse of AI-generated content material, we’re engaged on bringing this know-how to the broader AI ecosystem.

This summer time, we’re planning to publish extra about our textual content watermarking know-how in an in depth analysis paper, and we’ll open-source SynthID textual content watermarking by means of our up to date Responsible Generative AI Toolkit, which gives steering and important instruments for creating safer AI purposes, so builders can construct with this know-how and incorporate it into their fashions.



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