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Scaling up robot data and closing the loop with state decoding and automated reward scoring allows a 2B parameter video world simulator to outperform larger, dedicated robotic world models in real-world policy transfer.
Unlock human-like data efficiency: Zero-shot World Models learn complex physical understanding from a single child's egocentric experience.
