Current AI development reveals a technical paradox between advancing computational infrastructure and declining content quality in deployed applications. While researchers optimize data transfer bottlenecks and training efficiency, widespread AI-generated content exhibits significant quality issues stemming from architectural limitations in temporal consistency, cross-modal alignment, and physics-aware generation.
