Synthetic data generation is another innovative way AI and machine learning can respect user privacy without losing efficiency. By creating artificial datasets that mimic the statistical properties of real-world data, machine learning models can be trained effectively without accessing sensitive information. This approach not only preserves privacy but also ensures the diversity and richness of training data, maintaining the efficiency and accuracy of AI systems.
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