Artistic Features of Neural Networks: Image and Video Generation in the Context of Museum Practice

The article explores the role of neural networks in museum practice, popularization of art and preservation of cultural heritage, with special attention paid to technologies such as Flux and KlingAI. These neural networks are actively used to create photorealistic images and animations, introducing interactive elements into museum exhibits and making them accessible to a wide audience, including online. The author examines the features of such neural networks as Flux 1.1 Pro, designed to generate images based on text queries and supports post-processing of images in the «Ultra RAW» mode. Its functions expand the capabilities of museum and cultural organizations in creating visually exciting content. The article also describes the KlingAI neural network, which allows converting images and text queries into short videos and animations, which is especially useful for creating video content based on classical works of art. The advantage of KlingAI as the ability to integrate with Flux is emphasized. The combination of technologies is becoming a powerful tool for museum marketing and attracts the attention of the audience, creating interactive posters and unique videos for social networks and art exhibitions, neural networks are also used in the restoration of cultural heritage. An example of the use of neural networks in the Vesuvius Challenge project to decipher the charred scrolls of Herculaneum is also given. The neural network analyzes tomographic data, which allows you to «unfold» the scroll virtually and read the text without damaging the fragile material. This approach minimizes the risk of destruction of artifacts and preserves cultural values for subsequent research. The article also considers the ethical issues associated with the use of neural networks in working with cultural heritage, including the need for strict expert verification of the results of their work, the prevention of errors and distortions, as well as compliance with the boundaries between original works and reconstructions. Particular attention is paid to the importance of developing ethical standards and a regulatory framework for the responsible use of neural networks that ensure the protection of the rights of all participants and minimize possible risks.