The AI revolution is running out of data. What can researchers do?

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The increasing reliance of AI systems on vast amounts of data is hitting a critical point as the availability of useful data diminishes. Researchers are now exploring ways to acquire more data, including data augmentation techniques, synthetic data generation, and improved privacy-preserving methods for using real-world data effectively. The comments reflect a growing concern regarding the ethical implications of data usage by AI and privacy protection, leading individuals to reconsider how and where they share their data. This is indicative of a trend towards prioritizing data sovereignty and security over openness in data sharing practices, which could pose challenges for AI researchers looking for diverse datasets.
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