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    ‘Candy’ viewer asks whether AI video could help robotics simulation

    A viewer praises the physical consistency of selected Seedance 2.5 shots in “Candy,” which they describe as a nine-minute sci-fi short by Didi_ok.

    RS
    1 Source, 19d ago, first seen 19d ago

    TLDR

    A viewer highlights coordinated ant movement, changing environments and lighting, explosions, shifting objects and camera motion in selected Seedance 2.5 shots in “Candy.” They ask whether video models that maintain this kind of physical consistency could eventually be useful for robotics simulation, scenario generation or synthetic data, adding: “Not saying we’re there yet.”

    Combined views

    18.6K

    1 Source, first seen 19d ago

    Combined views

    18.6K

    1 Source, first seen 19d ago

    90 likes
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    Today's Rank

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    90 likes
    22 comments
    10 saves
    8 reposts

    Sentiment

    Positive——Negative

    Summary

    Not enough discussion yet.

    No sentiment analysis available yet.

    22 comments
    10 saves
    8 reposts

    Sentiment

    Positive——Negative

    Summary

    Not enough discussion yet.

    No sentiment analysis available yet.

    1 Source

    @ScobleizerMost AI video demos focus on how good they look. I’m more interested in how consistently they behave. That’s what stood out to me in Candy, a 9-minute sci-fi short by Didi_ok. Ants moving together, changing environments and lighting, explosions, shifting objects and camera motion….all handled with Seedance 2.5 in selected shots. If a video model can maintain this kind of physical consistency, could it eventually be useful for robotics simulation, scenario generation or synthetic data? Not saying we’re there yet, but this is a direction worth watching. Honestly, Candy feels less like a model showcase and more like a glimpse at what happens when a talented filmmaker finally gets access to a much bigger production toolbox.

    1 Source

    @ScobleizerMost AI video demos focus on how good they look. I’m more interested in how consistently they behave. That’s what stood out to me in Candy, a 9-minute sci-fi short by Didi_ok. Ants moving together, changing environments and lighting, explosions, shifting objects and camera motion….all handled with Seedance 2.5 in selected shots. If a video model can maintain this kind of physical consistency, could it eventually be useful for robotics simulation, scenario generation or synthetic data? Not saying we’re there yet, but this is a direction worth watching. Honestly, Candy feels less like a model showcase and more like a glimpse at what happens when a talented filmmaker finally gets access to a much bigger production toolbox.