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  5. Google Research

    Google Research proposes a multi-agent framework that automatically generates long-video narratives

    Google Research has released a unified multi-agent framework for automatically generating temporally coherent long-video narratives, addressing identity drift and cascading failures in existing linear pipelines. Built on top of Gemini and Veo as an orchestration layer, the framework consists of four parts: AI video co-director uses multi-armed bandits for global creative search, CANVAS plans multi-shot visual continuity through persistent visual memory, A²RD generates segment by segment autoregressively while maintaining multimodal video memory, and VQQA uses visual question answering to generate semantic gradients for closed-loop prompt optimization. Evaluations show that AI video co-director reaches a peak quality score of 81.4 on GenAD-Bench, CANVAS improves scene-reappearance continuity on ST-Bench and HardContinuityBench, A²RD reduces layout drift on VBench-Long and LVBench-C, and VQQA achieves quality gains on T2V-CompBench, VBench2, and VBench-I2V.

    A man and woman sit at a table looking at a glowing blue 3D holographic projection of a house emerging from a blueprint.

    Google Research has released a unified multi-agent framework for automatically generating temporally coherent long-video narratives, addressing identity drift and cascading failures in existing linear pipelines. Built on top of Gemini and Veo as an orchestration layer, the framework consists of four parts: AI video co-director uses multi-armed bandits for global creative search, CANVAS plans multi-shot visual continuity through persistent visual memory, A²RD generates segment by segment autoregr

    Matched fieldsSummary、Body

    #lab#Model releases#Multimodal#Video

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  2. Latent Space

    John Platt on AI for Science: How Google ERA Automatically Solves Scorable Scientific Problems

    Google's John Platt introduced Empirical Research Assistance (ERA), developed by his team. It uses Gemini to maintain an experiment tree, selects and mutates notebooks in a manner similar to Monte Carlo tree search, and automates the solving of scientific problems that can be written as scoring functions. It has already produced at least ten papers. ERA underwent a qualitative leap between Gemini 2.0 and 2.5, going from completely unusable to highly effective, and has been used in climate change research such as aircraft contrails.

    Google's John Platt introduced Empirical Research Assistance (ERA), developed by his team. It uses Gemini to maintain an experiment tree, selects and mutates notebooks in a manner similar to Monte Carlo tree search, and automates the solving of scientific problems that can be written as scoring functions. It has already produced at least ten papers. ERA underwent a qualitative leap between Gemini 2.0 and 2.5, going from completely unusable to highly effective, and has been used in climate change

    Matched fieldsSummary、Body

    #newsletter#Industry news#Google#English text is being prepared.

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