On a film set in Lower Manhattan, actress Audrey Corsa held nothing in her arms. The baby she appeared to cradle was not on set. It would be created later by an artificial intelligence model trained on hundreds of photographs and one woman’s first memory. That memory was the moment of her own birth.

Sascha Brodsky, Staff Writer, IBM

The film is Ancestra, a new short directed by Eliza McNitt, and it features a simulated version of McNitt herself, modeled after photographs taken by her father on the day she was born. These are the same images used to create the baby in the opening scene. When actress Audrey Corsa holds that newborn onscreen in the climactic final scene, she is in fact holding a digitally generated human being, a kind of hallucinated memory projected into being by software and intention. For McNitt, that gesture is more than cinematic sleight of hand. It is an act of emotional excavation.

Noted filmmaker Darren Aronofsky introduced McNitt to generative AI, an experience she says sparked the idea for Ancestra. He invited her to explore what these new tools could do and ended up producing the film. The result is a deeply personal short about a mother’s emergency delivery that fuses live action performance with AI-generated imagery rooted in cosmic and corporeal transformation.

“My mom had to have an emergency C-section when I was born,” McNitt told me during a recent conversation from her home in New York City. “She walked into the hospital for a checkup, and everything changed. That moment became the seed of Ancestra.”

The film tells the story of a mother who, during an emergency delivery, reaches across time and memory to connect with the women who came before her and with the unborn daughter she hopes to save. Ancestra fuses traditional live action and pioneering AI-generated imagery into a narrative that feels at once deeply intimate and dizzyingly cosmic. It also hints at where filmmaking could be going, using AI not to replace human creativity, but to build on it.

McNitt is quick to stress that this isn’t a film about AI. “It’s a film about my mother,” she said. But her use of generative models developed by Google DeepMind, including the video generator Veo and image models like Imagen and LoRA, offers a glimpse of what could very well prove to be a new kind of cinematic language—one built not solely from camera lenses and location scouts, but from prompts, neural networks and deeply personal data.

Veo is an advanced text-to-video system capable of generating short 1080p clips with high temporal coherence, object consistency and stylized rendering. But achieving those results requires carefully written prompts, multiple iterations, and an understanding of how the model interprets visual instructions. McNitt and her collaborators worked within the platform’s constraints—clip length, fidelity, prompt responsiveness—by fusing Veo’s outputs with motion path references and custom 3D scenes built in VR. The team first built animated previsualizations to map out the timing, then used them as a guide for the AI-generated footage.

To keep the film’s look consistent, McNitt’s team built their own companion style transfer model called LoRA. It was not a Google tool but a system they developed specifically for Ancestra to carry the same visual style through every scene.