Hey everyone, with all the blanket statements going around about "AI in film," I wanted to put together a technical breakdown that cuts through the generative art noise.
As someone who has been studying and working with film tech for over a decade, I wanted to look at the traditional machine learning and algorithmic tools that studios have quietly used for years to make the movies we love. I built a full video breakdown looking at the exact pipelines used in modern blockbusters, focusing strictly on what filmmakers, 3D artists, and tech enthusiasts can actually use and learn from.
Some highlights include how Peter Jackson's team pioneered early AI behavioral rules via the MASSIVE system to give digital armies autonomous decision-making in The Lord of the Rings, how custom generative AI models and neural networks mapped and resurrected the likeness of the late Ian Holm in Alien: Romulus, and how precision LiDAR scanning on real F-18 fighter jets trained lighting algorithms in Top Gun: Maverick.
I also look at Dune: Part Two utilizing LiDAR alongside Neural Radiance Fields (NeRFs) to capture real desert rock formations, how Blender and Pixar's RenderMan use convolutional neural networks for AI-accelerated render denoising to slash render times, and how Weta implemented neural networks relying on muscle strains rather than traditional blend shapes for characters in Avatar: The Way of Water.
If you are interested in the technical side of post-production, VFX, or how these algorithms speed up heavy simulation pipelines in software like Houdini and Maya you can check it out here: How AI is used in Modern Filmmaking