  In recent years, Generative Artificial Intelligence (GenAI) has undergone a
profound transformation in addressing intricate tasks involving diverse
modalities such as textual, auditory, visual, and pictorial generation. Within
this spectrum, text-to-image (TTI) models have emerged as a formidable approach
to generating varied and aesthetically appealing compositions, spanning
applications from artistic creation to realistic facial synthesis, and
demonstrating significant advancements in computer vision, image processing,
and multimodal tasks. The advent of Latent Diffusion Models (LDMs) signifies a
paradigm shift in the domain of AI capabilities. This article delves into the
feasibility of employing the Stable Diffusion LDM to illustrate literary works.
For this exploration, seven classic Brazilian books have been selected as case
studies. The objective is to ascertain the practicality of this endeavor and to
evaluate the potential of Stable Diffusion in producing illustrations that
augment and enrich the reader's experience. We will outline the beneficial
aspects, such as the capacity to generate distinctive and contextually
pertinent images, as well as the drawbacks, including any shortcomings in
faithfully capturing the essence of intricate literary depictions. Through this
study, we aim to provide a comprehensive assessment of the viability and
efficacy of utilizing AI-generated illustrations in literary contexts,
elucidating both the prospects and challenges encountered in this pioneering
application of technology.
