The next generation of AI-driven robots like humanoids and autonomous vehicles depends on high-fidelity, physics-aware training data. Without diverse and representative datasets, these systems don��t get proper training and face testing risks due to poor generalization, limited exposure to real-world variations, and unpredictable behavior in edge cases. Collecting massive real-world datasets for��
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