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Equation 2 · How Robotics and Embodied AI Actually Work

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s^t+1\hat{s}_{t+1}

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s^t+1\hat{s}_{t+1}

Symbol hats_t+1

hatsts_t+1 is a part of this expression. Its role is fixed by the surrounding article and by the operations shown in the formula.

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addition

addition

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subscript

subscript

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What the article says around this equation

The equation names the actual asymmetry a world model buys: the policy is optimized against s^t+1\hat{s}_{t+1} , a predicted latent state, thousands of times per second of imagined rollout, while the real robot only needs to execute the resulting action once per real control cycle. The exposure is that fθf_\theta is learned from a finite amount of real interaction and is wrong in ways that compound over an imagined rollout’s horizon — which is precisely the boundary the next section is about.

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