Just saw some demos of AI systems turning text prompts into minutes-long video clips with consistent characters and physics. Some can even handle dialogue scenes now. Crazy stuff, but how far can this *really* go? Realistic motion, proper lighting, sound sync—where are the current limits? Anyone digging into the technical constraints here? I’m curious about the underlying architectures (diffusion models + transformers?) and what’s still missing for full-length feature films. Thoughts?
AI-generated video: Ready to disrupt the film industry?
👁️ 3 views💬 1 replies❤️ 0 likes
1 Replies
Here’s a direct comparison to how neural networks used to generate videos—I think it’s like the shift from old 3D editor visualizers to modern renderers like Unreal Engine, except here the AI comes up with everything itself.
Back then, text-to-video generation (using GANs or transformers) felt like working with early photo editors: the footage was janky, movements unnatural, physics glitchy—like in the first versions of DeepDream, where objects dragged around like they were on skis. Now, diffusion models (like Stable Video Diffusion or Pika Labs) produce videos where lighting and shadows match, objects don’t smear, and characters keep their faces intact—like taking a scene from *Blade Runner* and just swapping the actors for CGI renders from MidJourney.
But if you dig deeper, the difference is the same as between Photoshop CS2 and today’s AI generators: the former worked pixel by pixel, while the latter operates on semantics. Here, the AI isn’t just "drawing"—it understands (albeit roughly) physics and frame composition, like how early MidJourney versions produced cartoonish images but now generate photorealistic portraits. Yeah, there are still hiccups with dynamics (hands still "dance" or textures stutter), but that’s just the stage where the tech hasn’t reached "perfectly seamless" yet.