A wave of déjà vu washes over me as Elias Roman, vice president of product management at Google Labs, demos a new “avatar” feature for Flow, the company’s tool that lets users generate and remix AI videos and images. He previously scanned his likeness to create a digital clone of himself. Now, he can insert himself into any AI-generated videoclip he wants using Google’s new Omni Flash model.

“This is for creators who want to bring themselves into their content but don't want to have to shoot themselves,” Roman says.

This specific style of social-first, selfie deepfake is reminiscent of a quintessential feature from OpenAI’s now-defunct Sora app—rather than cameos or characters, Google calls them avatars. These avatars are also available through the Gemini app and YouTube. Google announced the new feature at its annual I/O developer conference in Mountain View, California.

Google launched Flow last year under its experimental Labs division. “Google has never had a product line for creative work before,” Roman says. “Productivity, definitely. Developers, absolutely. Video consumption, yes. Not for creative work.” He sees this as Google’s attempt to build tools for the next generation of creators.

Similar to other announcements from Google I/O surrounding Google Search, many of the new changes to Flow are part of the company’s larger attempt to make AI agents, essentially automated software taskmasters, and vibe coding, building bespoke features with natural language prompts to AI, more mainstream for a broader audience. For example, users can repeat custom instructions when generating videos and create automated workflows that sort similarly styled clips into folders.

One of the most immediately noticeable changes to Flow is the new video-generation model powering the experience: Omni Flash, succeeding Veo. Similar to how Google’s Nano Banana model brought more context about the world into the AI image-creation process, the Omni Flash model overhauls video generation with richer detail throughout clips.

Flow users can generate characters in AI videos with more consistency via the Omni Flash model. Roman says this is a major improvement over the weakness in past versions of Flow, where created characters could warp during successive video generations. Also, a key character that Flow users can now generate in an AI scene after an AI scene? Themselves.

Users set up an “avatar” of themselves by going into the settings of their Flow account and scanning a QR code on their phone. Then, Google asks users to record themselves saying a string of numbers aloud and move their head around to capture every angle. This selfie-capture style will feel familiar to anyone who signed up for the Sora app, which OpenAI launched last year as an AI-first social media platform where people can generate and share clips of themselves. OpenAI startlingly wound it down after less than seven months.

Unlike the Sora app, where users could generate videos of other users depending on the person’s settings, Google’s initial focus with its avatars is to let users create AI versions of themselves only, not other people. Every video generated with the Omni model, including those with your avatar, includes Google’s SynthID watermark.

“You can capture your voice and your visual identity from multiple angles and have that show up with pretty high levels of fidelity,” Roman says. He generated a tongue-in-cheek video of himself roasting the Flow team in front of a dumpster fire, with an AI version of himself that looked lifelike and sounded like him. Then he used Flow to request changes to the generation, like a new background setting and a different-colored shirt, and Omni Flash adjusted the clips while preserving the avatar’s details.

This isn’t the first time Google has rolled out a version of self-controlled deepfake video tools for creators—last month, YouTube Shorts added a limited option for users to make similar AI avatars that can be inserted into clips on that platform. Other Silicon Valley companies are also looking for ways to transform creators’ outputs using generative AI. For example, last year, Meta rolled out an AI feature that can seamlessly translate Instagram Reels into different languages, even adjusting creators’ lips to match the different voices.

While these AI tools may streamline aspects of the content production pipeline for creators—you don’t even have to get out of bed now to generate sassy vertical videos—generative AI is increasingly polarizing audiences who see these videos as inauthentic or not aligned with their values. Well, that’s if they actually clock the videos as AI.