With the iterative development of artificial intelligence technology, AI generated video models have emerged, which can generate videos based on textual descriptions. Works such as "Sanxingdui: Apocalypse of the Future", "Shanhaiqi Mirror: Splitting Waves", and "Hero" have applied this AI video generation technology to stages such as planning, rehearsal, live action, and post production, profoundly changing the production mode of film and television creation. However, while the industry is actively trying to use new technologies to create smart film and television content and develop the smart film and television industry, it should also have a deep understanding of the risks and challenges that AI video generation technology may bring to the development of the film and television industry. Recently, many creators have reported that they often make jokes when using AI to generate video content related to Chinese historical reality. For example, they input instructions and ask AI to generate a video with a Chinese university campus as the scene. The students in the video scene are all foreigners' faces; Input commands to generate a video of a Chinese street, in which the text on the signs on both sides of the street is not Chinese characters, but some strange symbols, like a "heavenly book". If the errors that occur in the AI cultural video model when generating videos with Chinese realistic themes are obvious, easy to identify and correct, then it is more likely to encounter some hidden and difficult to identify errors when generating videos with Chinese historical and cultural themes. For example, if we ask AI to generate a video that tells the story of ancient China, the content we receive is likely to include ancient landscapes from other countries, such as traditional clothing, hats, and patterned designs. If the creator's knowledge reserve is insufficient, it is difficult to identify the problems. The low-level errors that often occur in AI generated videos are closely related to the limitations of their generation logic and training data. The AI generated video model relies on computer deep learning to learn existing images and video resources in the database and those fed by users, combined with user input text descriptions, to generate new video content. So, the quality and diversity of training models directly affect the accuracy and cultural adaptability of generated content. Currently, there is a lack of video materials reflecting Chinese cultural characteristics in the training data of a large number of AI cultural video models in China. So, when generating content related to Chinese culture, there may be distortion or errors. For example, when a user inputs instructions to request AI to generate a video that reflects the artistic conception of the ancient poem "The Song of Pipa", the generated result may show scenes of ancient people holding guitars instead of pipa. This type of error is often caused by AI's lack of deep training on the pipa image, resulting in the random combination of unrelated materials in the database during content generation. If a large amount of erroneous video content emerges, it will not only affect the artistic and cultural value of the work, but may also mislead the audience, especially the youth group. This reflects the shortcomings of AI video generation technology in cultural adaptation, and the industry needs to further optimize training data. Therefore, in order to address the issues of distortion and errors that may occur when AI video generation technology generates video content related to Chinese historical reality, it is necessary to build a database that is accurate in information, well researched, and reflects Chinese culture. This should include images, videos, and other resources that have been reviewed and certified by professional institutions and reflect China's history and reality, used to train AI cultural and biological video models, thereby ensuring the authenticity and high quality of China's digital film and television content production. However, high-quality database construction is not achieved overnight, but requires the joint efforts of government departments, relevant universities and research institutions, film and television production institutions, and other sectors. Firstly, government departments should play a leading role in establishing platforms for the identification, dissemination, and promotion of image and video resources, supporting the construction of databases that collect Chinese cultural image and video resources, encouraging co creation and sharing among all sectors, and exploring long-term models for the creation and production of digital film and television content. Secondly, relevant universities and research institutions need to leverage their research transformation capabilities, deeply explore the historical origins, characteristics, aesthetic features, and cultural connotations of Chinese culture, systematically sort out the Chinese cultural context and related elements such as characteristic landscapes, cities, architecture, cultural relics, and figures, and provide profound theoretical support for the research of existing image and video resources and the development of new resources. Once again, film and television production institutions should organically combine cutting-edge digital technology with historical, cultural, and artistic resources in the process of promoting the construction of databases reflecting Chinese culture, to assist in the creative development of excellent traditional Chinese cultural IP, and to enhance the dissemination and influence of digital film and television content brands based on excellent traditional Chinese cultural IP. In short, in the era of artificial intelligence, China's digital film and television industry has great potential, and high-quality databases reflecting Chinese culture are the key "infrastructure" of the digital film and television industry. Therefore, we should attach importance to the construction of databases that reflect Chinese culture and apply them to the training of AI cultural video models. On this basis, by deeply integrating technology and cultural creativity, we can create more high-quality digital film and television content, forming a digital aesthetic paradigm with Chinese characteristics, thereby helping the stable and far-reaching development of China's digital film and television industry. (New Society)