
Tech • AI • Robotics
Filmmakers are rapidly integrating AI into production and storytelling, enabling large-scale films, interactive narratives, and new creative workflows while reshaping industry jobs.
Director Doug Liman described artificial intelligence as the natural evolution of tools that have always shaped cinema, comparing it to earlier innovations like high-speed film stock that enabled low-budget productions. He positioned AI as a continuation of that trajectory, allowing filmmakers to attempt projects previously constrained by cost or logistics.
Liman completed a feature film titled “Bitcoin”, starring Casey Affleck, Gal Gadot, and Pete Davidson, created through an AI-centered pipeline. Initially expected to require 40 years of post-production, technological advances reduced that timeline to roughly six months, bringing it in line with traditional film schedules.
AI removed traditional production constraints, allowing the film to depict approximately 150 global locations, far beyond the typical 30–40 scenes in conventional filmmaking. This shift changed how scripts are written, eliminating the need to condense stories around budget limitations and enabling more expansive narratives.
Despite heavy AI use, the production relied on real actors and performance capture rather than synthetic performances. Liman emphasized that preserving authentic acting was essential, with AI used to enhance environments and workflows rather than replace core human elements.
The company 30 Ninjas, co-founded by Liman, Jed Weintrob, and Julina Tatlock, operates across two areas: AI-powered film production and interactive storytelling. The studio combines engineers and filmmakers to build new pipelines that merge traditional cinema with emerging technologies.
Projects like “ASTEROID” blend linear films with interactive extensions, allowing audiences to converse with characters using generative AI. After the film ends, viewers can engage in real-time dialogue with a stranded character, effectively continuing the narrative beyond its original format.
Contrary to assumptions about automation, AI-driven characters require substantial human input. Creating a single interactive character involved around 1,000 pages of writing, including backstory, behavioral rules, and safeguards to maintain narrative consistency during live interactions.
The filmmaking process combined performance capture, AI-generated visuals, and iterative editing. Teams continuously adapted to evolving tools, blending structured film pipelines with agile, software-like development cycles where production, editing, and post-production increasingly overlap.
Liman noted a decline in traditional film production, with fewer large-scale projects being made. However, AI studios are hiring displaced professionals such as editors and writers, suggesting a redistribution of work rather than outright elimination of roles.
Early stages of AI filmmaking involved significant uncertainty, with filmmakers committing to processes before tools were fully developed. This experimentation has been compared to navigating unknown terrain, requiring both risk tolerance and collaboration with technology developers.
Creators were encouraged to experiment with AI tools while maintaining originality. Rather than relying on AI to generate complete work, filmmakers should use it to amplify their own voice and explore new styles, including intentionally pushing tools beyond their default outputs.
AI is transforming filmmaking by expanding creative possibilities and altering production models, but its most effective use remains rooted in human storytelling, performance, and artistic direction.
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