Understand the fundamental trade-off between quality and stability in AI generation: sharp detail vs smoothness, expressive motion vs consistency, and visual richness vs reproducibility.
Discover situations where AI video generators fail: long-form videos, character-driven scenes, fast motion, camera movement, low light, and complex scenarios.
Explore the structural limitations of modern AI video generators: identity consistency, quality degradation, motion coherence, camera control, and prompt reliability challenges.
Learn why AI-generated characters change over time: identity drift, attribute drift, style inconsistency, and lack of persistent memory affecting character consistency.
Understand why AI-generated images vary: prompt interpretability, style inconsistency, attribute drift, sampling variability, and model routing affecting image consistency.
Even the best AI video generators are not limited by implementation quality alone, but by fundamental trade-offs inherent to generative modeling. Improving one dimension—such as stability, realism, or control—almost always comes at the expense of anot
Why do AI videos degrade over time? AI video generators fail due to structural limitations like identity drift, quality degradation, and motion incoherence.