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Rethinking Video Storage for AI Training: Breaking Cross-Frame Dependencies for Efficient Random Access
Large-scale AI training increasingly relies on massive video datasets with random temporal sampling patterns. However, existing video storage paradigms are optimized for sequential playback and employ sophisticated inter-frame reference structures to maximize compression efficiency. When applied to
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