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Synthetic Data in AI: Challenges and the SynthVision Advantage
As AI development advances, synthetic data has emerged as a promising alternative to overcome the scarcity and limitations of real-world data. The paper Synthetic Data in AI: Challenges, Applications, and Ethical Implications highlights both the potential and the challenges of synthetic data, especially regarding representativeness, bias, and ethical issues. But how do these challenges compare…
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Synthetic Data: Advantages of Full Simulation vs. Generative AI – An Analysis of MIT’s Study
An Analysis of MIT’s Study In the field of computer vision, synthetic data generation has emerged as an efficient solution for training machine learning models. A 2022 study from MIT introduced an innovative technique using generative AI to create highly realistic synthetic data. While this study was groundbreaking at the time, it now serves as…
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September 2024
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- SynBalance: balancing rare classes with synthetic data
- Synthetic Data in Computer Vision: From Scientific Revolution to Industrial Applications
- ROSE: Object Removal in Videos Powered by Synthetic 3D Data
- DAViD by Microsoft: A Public Milestone in Computer Vision with Synthetic Data
- Is AI “shutting down” our brains? A reflection beyond the hype
