ZenRows’s whitepaper Real Data vs. Synthetic Data: Which Is Better for AI? explains that while synthetic data offers scalability, privacy, and cost advantages, over-reliance on it creates critical blind spots in AI systems. Synthetic data is artificially generated to mimic real-world patterns but may lack the authenticity and nuanced context of real data collected from actual events and interactions. Real data provides the foundation for reliable, high-performing language models by capturing true variability and rare cases. The best approach often combines both: real data ensures accuracy and contextual relevance, while synthetic data fills gaps and enables rapid iteration, improving overall AI robustness and performance.

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