Neill Blomkamp’s new zombie AI ‘film’ is just slop warmed over

Neill Blomkamp has officially entered the generative AI film space with a new project called Nightborne. The thirteen-minute sci-fi short is loosely based on Peter Watts’ novel Echopraxia and serves as a proof of concept for his new venture, Barley Studios. According to The Verge, every single shot in the film was generated using ByteDance’s Seedance 2.0 text-to-video model. This marks a significant moment in the industry as high-profile directors begin to publicly experiment with fully AI-driven production pipelines.

The visual approach relies on characters whose faces and voices are modeled after human actors. This technique aims to bridge the uncanny valley by providing consistent identity markers for the AI-generated subjects. However, the reliance on a single model for the entire runtime exposes the inherent instability of current generative video technology. The result is a visual experience that feels more like a moving slideshow than a cohesive cinematic work.

Blomkamp described the project as a test start intended to demonstrate what generative AI can currently achieve. He expressed ambitions to tackle a full-length feature using these tools in the future. This statement signals a growing confidence among established filmmakers that AI will eventually replace traditional production methods. It also suggests that the industry is moving past the novelty phase into a more serious evaluation of practical application.

Critics and audiences have largely dismissed the short as slop warmed over. The term highlights a common frustration with AI video content that lacks narrative depth or emotional resonance. While the technology can replicate visual styles, it struggles to maintain logical continuity or character development. This disconnect between technical spectacle and storytelling remains the biggest hurdle for AI cinema.

The use of Seedance 2.0 underscores the rapid pace of innovation in the video generation sector. ByteDance is competing fiercely with other major players to establish dominance in this new medium. The success of such projects will likely depend on their ability to solve consistency issues rather than just generating impressive individual frames. Investors and studios are watching closely to see if these tools can scale to meet professional demands.

For creators and entrepreneurs, this release serves as a cautionary tale about the current state of AI video. It is crucial to understand that while the technology is advancing quickly, it is not yet ready for complex narrative tasks. The focus should remain on using AI for specific elements like background generation or style transfer rather than entire productions. This approach allows for better control and higher quality output.

What this means for you is that you should approach AI video tools with realistic expectations. Use them for prototyping concepts or creating visual assets rather than final narrative content. To improve your workflow, try using an AI assistant to break down a script into individual scene descriptions. Then generate those scenes separately and edit them together in a traditional video editor. This hybrid approach leverages AI creativity while maintaining human oversight over the story structure.