Shengshu Technology on July 3 officially released Vidu S1 at the 2026 Global Digital Economy Conference, pushing video generation from "one-shot film" to "infinite-duration real-time interaction". Technically, S1 uses an autoregressive + diffusion (AR + Diffusion) hybrid architecture: predicting the next segment frame-by-frame based on the already-generated picture, voice input, and dialogue context, breaking the fixed-duration constraint, and outputting 540P @ 25 FPS (up to 42 FPS) real-time video stream on consumer-grade GPUs. The underlying inference stack combines Shengshu's self-developed TurboDiffusion, 8-bit SageAttention, and SLA/SpargeAttention sparse attention, with the TurboServe inference engine dynamically scheduling compute, pushing the usually-server-cluster-required real-time video conversation down to single-card level. On the interaction level, S1 doesn't just drive lip shapes, but directly parses semantics, intent, and emotion in voice, synchronously generating expressions, eye direction, hand gestures, and body movements; character creation is also compressed to a single image + a voice timbre, no modeling, binding, or separate training needed. S1's direction is more worth watching: Sora and Kling previously took the "full-segment denoising" route, where real-time and infinite duration are natural short boards; AR + Diffusion puts "continuous generation + online response" on equal footing with image quality. AI video is moving from "content production tool" to "persistently existing interactive agent", with structural impact on virtual streamers, AI companions, interactive games, and XR scenarios.