Let’s Practice Better... on Cats: Description and Visualisation of Artistic Images in Generative AI Models

Artificial Intelligence (AI) plays an increasingly prominent role in various spheres of life in today’s world, including generation of a variety of visual content from selfie stream processing to creating works of digital art. The present paper raises the question of whether AI is capable of creating real art or it just imitates its external form. The paper examines the specificity of prompts: from concrete named ones to interpretive descriptive queries in linguistic, artistic and socio-cultural contexts. The article dwells upon some important aspects of evaluating the quality of keyword extraction algorithms and their relation to artistic practice. The authors rely on semiotic analysis to uncover encoded meanings and imports in the text. The article emphasises that the literary text is at the top of the hierarchy of cultural texts; it is characterised by intentionality and coherence and represents a complex semantic field where key words and images interact with the explicit and implicit contexts. The study examines and analyses the visualised images of Cheshire Cat, Cat Behemoth and Tomcat Murr created by the authors with the use of three generative neural networks: Stable Diffusion, Dall‑E and Kandinsky. Understanding and visualising the literary text by generative systems and models realising specific algorithms requires the ability to reveal its multilayered semantics and connection with the cultural context, which ultimately helps to understand the in-depth meanings of the work and its place in culture. Consideration of the operational quality of algorithms for keyword system extraction and image generation is deemed possible from the point of view of their structural organisation. Generative algorithms create an imitative reality, while the immanence of the artistic value determines the uniqueness and meanings of the created figurative world. The article can be useful to anyone interested in the substance and specificity of digital art, the relationship between technological innovations and socio-cultural context, the creation and visualisation of artistic images in generative AI models, their conceptualisation and interpretation.