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      "statement": "# AWS–Reactor: hardware-tuned streaming video inference on Trainium\n\nOptimized a Rolling Forcing streaming pipeline with NKI kernels for3D rotary embeddings and cache copies, fused attention transposes, hybrid head/sequence sharding and batching of common denoise/cache-update work.\n\n## Scientific scope\n\nCompany technical account supports the integration, not a new Rolling Forcing algorithm, invention of NKI/parallelism or independently certified real-time performance. Kernel latency and full-pipeline frame rate are different metrics; reported single-chip results depend on model, resolution and configuration. Article writer Stephen Zorio is not asserted to be a complete technical-inventor list; corporate project groups retained.\n\n## Reading status\n\nThis is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.\n\n## People and systems\n\n\n\nSource-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.\n\n\n\n## Original sources\n\n- [A kernel-centric path to real-time video generation on Trainium](https://www.amazon.science/blog/a-kernel-centric-path-to-real-time-video-generation-on-trainium)\n",
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