Why OpenAI Shut Down Sora: How AI Video Really Works

OpenAI shut down the Sora app, but the model lives on, and this video explains the real economics of AI video plus how text-to-video actually works. You will learn what really happened to Sora and why the headline that AI video failed is exactly backwards. We unpack the reported reason, compute economics, and why video is orders of magnitude more expensive than text or images. Then we go under the hood: why a video is a four-dimensional volume that must agree with itself over time, how models compress clips into latents, slice them into spacetime patches, and denoise random static with a diffusion transformer. We show how cross-frame attention creates temporal coherence, why that same mechanism makes video ruinously expensive, why the Sora model migrated to robotics as a world model, and where Veo, Runway, and Kling stand now. Chapters: 0:00 The headline is wrong 0:57 What actually happened 2:00 The real reason: economics 4:30 What AI video can do 5:38 A video is not a picture 6:35 Compress, slice, and denoise 9:00 Attention across frames 10:06 Why video costs a fortune 11:20 Physics and world models 12:46 The survivors and the moat 16:43 Myths and what it means 📺 More AI, explained simply: Subscribe to @HowAIWorksHQ for clear, honest explanations of how AI actually works. Sora, OpenAI Sora, AI video, AI video generation, text to video, Google Veo, Runway, Kling, diffusion transformer, temporal coherence, world model, how AI video works #Sora #OpenAI #AIVideo #TextToVideo #Veo #DiffusionTransformer #AIExplained #HowAIWorks