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Identifying AI-generated content with SynthID

Our SynthID toolkit watermarks and identifies AI-generated content. These tools embed digital watermarks directly into AI-generated images, audio, text or video. In each modality, SynthID’s watermarking technique is imperceptible to humans but detectable for identification.

Being able to identify AI-generated content is critical to promoting trust in information. While not a silver bullet for addressing problems such as misinformation or misattribution, SynthID is a suite of promising technical solutions to this pressing AI safety issue.

This toolkit is currently launched in beta and continues to evolve. It’s now being integrated into a growing range of products, helping empower people and organizations to responsibly work with AI-generated content.

How does SynthID work?

SynthID uses a variety of deep learning models and algorithms for watermarking and identifying AI-generated content.

  • Watermarking: SynthID embeds a digital watermark directly into AI-generated content, without compromising the original content.
  • Identification: SynthID can scan images, audio, text or video for digital watermarks, helping users determine if content, or part of it, was generated by Google’s AI tools.


SynthID for AI-generated text

We’ve expanded SynthID to watermarking and identifying text generated by the Gemini app and web experience.

Finding a robust solution to watermarking AI-generated text that doesn’t compromise the quality, accuracy and creative output has been a great challenge for AI researchers. To solve this problem, our team developed a technique that embeds a watermark directly into the process that a large language model (LLM) uses for generating text.

An LLM generates text one token at a time. These tokens can represent a single character, word or part of a phrase. To create a sequence of coherent text, the model predicts the next most likely token to generate. These predictions are based on the preceding words and the probability scores assigned to each potential token.

For example, with the phrase “My favorite tropical fruits are __.” The LLM might start completing the sentence with the tokens “mango,” “lychee,” “papaya,” or “durian,” and each token is given a probability score. When there’s a range of different tokens to choose from, SynthID can adjust the probability score of each predicted token, in cases where it won’t compromise the quality, accuracy and creativity of the output.

SynthID adjusts the probability score of tokens generated by the LLM.

This process is repeated throughout the generated text, so a single sentence might contain ten or more adjusted probability scores, and a page could contain hundreds. The final pattern of scores for both the model’s word choices combined with the adjusted probability scores are considered the watermark. This technique can be used for as few as three sentences. And as the text increases in length, SynthID’s robustness and accuracy increases.

A piece of text generated by Gemini with the watermark highlighted in blue.

SynthID for AI-generated music

In November 2023, SynthID was expanded to watermark and identify AI-generated music and audio. SynthID's first deployment was through Lyria, our most advanced AI music generation model to date, and all AI-generated audio published by our Lyria model has a SynthID watermark embedded directly into its waveform.


SynthID adds a digital watermark to AI-generated audio that is imperceptible to the human ear.

First, SynthID converts the audio wave, a one dimensional representation of sound, into a spectrogram. This two dimensional visualization shows how the spectrum of frequencies in a sound evolves over time.

SynthID converts audio into a visual spectrogram to add a digital watermark.

Once the spectrogram is computed, the digital watermark is added into it. Finally, the spectrogram is converted back to the waveform. During this conversion step, SynthID leverages audio properties to ensure that the watermark is inaudible to the human ear so that it doesn’t compromise the listening experience.

The watermark is robust to many common modifications such as noise additions, MP3 compression or speeding up and slowing down the track. SynthID can also scan the audio track to detect the presence of the watermark at different points to help determine if parts of it may have been generated by Lyria.

SynthID for AI-generated images and video

SynthID adds a digital watermark that’s imperceptible to the human eye directly into the pixels of an AI-generated image or to each frame of an AI-generated video. We’ve designed it so it doesn’t compromise image or video quality, and allows the watermark to remain detectable — even after modifications like cropping, adding filters, changing colors, changing frame rates (for video) and saving with various lossy compression schemes (commonly used for JPEG images).

The watermark is detectable even after modifications like adding filters, changing colors and brightness.

Where is SynthID available?

This technology is available to Vertex AI customers using our text-to-image models, Imagen 3 and Imagen 2, which create high-quality images in a wide variety of artistic styles. SynthID technology is also watermarking the image outputs on ImageFX.

We’ve also integrated SynthID into Veo, our most capable video generation model to date, which is available to select creators on VideoFX.

SynthID generates an imperceptible digital watermark for AI-generated images.

SynthID can also scan a single image, or the individual frames of a video to detect digital watermarking. Users can identify if an image, or part of an image, was generated by Google’s AI tools through the About this image feature in Search or Chrome.

An example of using the “About this image” feature, where SynthID can help users determine if an image was generated with Google’s AI tools.