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Video can be reimagined as a dynamic interplay of stable contexts and evolving events, revolutionizing real-time interaction capabilities in AI.
Many robotic policies that seem successful in manipulation tasks actually compromise safety, with SoftVTBench revealing a stark contrast between goal completion and physical safety metrics.
Higher resolution in real-time audio-visual interactions can be achieved without sacrificing latency, enabling clearer agent representation in conversations.
Sub-second duplex audio-visual communication is now achievable with a single, unified model that eliminates the latency of traditional cascaded systems.
Ditch slow, multi-step video generation: S-VAM distills the structured generative priors of multi-step denoising into a single forward pass for real-time robot action prediction.
