In the imperfect light of real-world spaces—where cameras blur, sensors noise, and compression fragments—artificial intelligence has long struggled to see clearly. Researchers have now developed a training framework called PDAD that teaches detection models to understand corruption itself, not merely endure it, equipping them with degradation awareness during training that is then quietly discarded before deployment. The result is a system no heavier or slower than before, yet far more resilient—a quiet but meaningful step toward AI that can function not in ideal conditions, but in the world a