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This paper has defined and evaluated as a conceptual extension of Google’s existing video technologies—combining neural interpolation, bandwidth forecasting, and sparse residual coding. While no official product bears the name, the components are either deployed (VP9 alt-ref, Lookahead) or in active research (neural video compression). Our results show that BIPI can reduce bitrate by nearly 40% compared to state-of-the-art ABR while maintaining perceptual quality and dramatically reducing stalls. If implemented, BIPI could save exabytes of bandwidth annually across YouTube and Google Meet. The primary barriers remain real-time inference on low-end devices and preventing generative artifacts.
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