I watched a robot keep up with a live air-hockey puck at real speed, and it predicts the play instead of just reacting

I've been going down a rabbit hole on robot control models, and one distinction finally clicked for me. Most of the robot arms you see in demos are reactive. A camera frame comes in, the model spits out the next motor command, repeat. It works, but on anything fast or long-horizon the robot tends to lag or lose the thread, because it's only ever thinking about the current instant. The newer idea is to give the robot something closer to imagination. Instead of mapping the camera straight to an action, the model first predicts how the scene is about to change over the next moments, then picks actions inside that predicted future. Every time a real camera frame comes back, it corrects the prediction so it doesn't drift off into fantasy. So it becomes a fast predict-then-correct loop rather than pure reaction. The clip that made this concrete for me is a model called LingBot-VA 2.0, running this on real robots at normal speed. In one clip a robot keeps up with a live air-hockey puck, and in another it picks objects off a moving conveyor belt, both of which punish a laggy reactive policy. It also adapts to a new task from only 10 to 15 demonstrations, and can pick up a task by watching a short human video instead of being told in words. Two honest caveats so this doesn't read like a press release. The only outside benchmark they report is a simulation one, RoboTwin, where it averages about 93.6 percent on two-arm tasks. The eye-catching real-world tasks are their own in-house tests shown as bar charts, not a shared benchmark, so treat those as demos rather than independently verified. And as always with robot videos, uncut at 1x doesn't prove zero retries off camera. I'll drop the source and the full caveats in a comment. Still, the shift from react to predict-then-act is the part I think is genuinely worth watching, because it's the same idea that makes long or fast tasks tractable. Curious whether people here think prediction-based control is the direction, or whether reactive policies with enough data close the gap anyway.