One of the many issues with generative art — apart from the ethical implications of training on artists’ work — is the potential for creating deepfakes. For example, the pope’s hot new hip-hop attire (an AI image created with MidJourney) going viral on social media was an early example of what could become more commonplace as generative tools evolve. It doesn’t take much imagination to see how something like political ads using AI-generated art could do much more damage than a funny image circulating on Twitter. “Watermarking audio and visual content to help make it clear that content is AI-generated” was one of the voluntary commitments that seven AI companies agreed to develop after a July meeting at the White House. Google is the first of the companies to launch such a system.

Google doesn’t go too far into the weeds about SynthID’s technical implementation (likely to prevent workarounds), but it says the watermark can’t be easily removed through simple editing techniques. “Finding the right balance between imperceptibility and robustness to image manipulations is difficult,” the company wrote in a DeepMind blog post published today. “We designed SynthID so it doesn’t compromise image quality, and allows the watermark to remain detectable, even after modifications like adding filters, changing colours, and saving with various lossy compression schemes — most commonly used for JPEGs,” DeepMind’s SynthID project leaders Sven Gowal and Pushmeet Kohli wrote.

The identification part of SynthID rates the image based on three digital watermark confidence levels: detected, not detected and possibly detected. Since the tool is embedded into the image’s pixels, Google says its system can work alongside metadata-based approaches, like the one Adobe uses with its Photoshop generative features, currently available in an open beta.

SynthID includes a pair of deep learning models: one for watermarking and the other for identifying. Google says the two trained on diverse images, culminating in a combined ML model. “The combined model is optimised on a range of objectives, including correctly identifying watermarked content and improving imperceptibility by visually aligning the watermark to the original content,” Gowal and Kohli wrote.

Google acknowledged that it isn’t a perfect solution, adding that it “isn’t foolproof against extreme image manipulations.” But it describes the watermark as “a promising technical approach for empowering people and organisations to work with AI-generated content responsibly.” The company says the tool could expand to other AI models, including those tasked with generating text (like ChatGPT), video and audio.

Although watermarks could help with deepfakes, it’s easy to imagine digital watermarking turning into an arms race with hackers, with services that adopt SynthID requiring continual updating. In addition, the open-source nature of Stable Diffusion, one of the leading generative tools, could make industry-wide adoption of SynthID or any similar solution a tall order: It already has countless custom builds that can run on local PCs out in the wild. Regardless, Google hopes to make SynthID available to third parties “in the near future” to at least improve AI transparency industry-wide.

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While Getty has seemingly been on an anti-AI bent — it’s also suing Stable Diffusion maker Stability AI over scraping its data — it’s no surprise the company has figured out a way to get into the market. Competing photography services have already announced their own AI solutions: Shutterstock is tapping into Open AI’s DALL-E model, while Adobe’s Stock is relying on its own Firefly tool as well as accepting some AI generated art.

Getty’s Generative AI tool is powered by NVIDIA’s Edify AI model from its Picasso cloud service. It’ll be interesting to see how those results compare against the improved DALL-E 3 model, but for now it’s basically just a way for Getty to dip a toe into the world of AI. As part of this new endeavor, Getty is also launching a “contributor compensation model for AI licensing,” Gizmodo reports. Creators will be paid based on the amount of images they’ve uploaded, together with their existing licensing earnings.

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Whether or not you’ve ever thought about what’s at the top of your playlist, designing and adding an image is pretty simple. All you need to do is click the playlist’s edit button and then on the existing main image. YouTube Music will then bring you to a range of categories, such as nature, humor and animals. Each one will generate a random set of pictures upon selection, such as a dog in a specific art style, that you can change. Just toggle through the options, and when you find one you like, save it as your playlist’s new cover photo.

YouTube Music’s other update set to roll out is a feature called speed dial that lets you jump right back into recent listens, like specific artists and playlists. The format is very reminiscent of the top of Spotify’s homepage, but YouTube appears to show more options than its competitor.

These features follow other recent attempts by YouTube Music to compete with more established services, such as adding a comments section and timed lyrics to follow along with songs. AI-powered custom playlist art is available now to English language accounts in the United States, with plans to roll out globally in the future, while speed dial will be available in the coming months.

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