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Achieving 92.61% accuracy in bearing fault diagnosis with just 10% labeled data reveals a transformative approach to predictive maintenance in industrial settings.
Seedance 2.0 leapfrogs existing models by unifying multi-modal inputs (text, image, audio, video) into a single architecture for generating high-quality, longer-duration audio-video content.
