FairyLandAI: Personalized Fairy Tales utilizing ChatGPT and DALLE-3
<|reference_start|>FairyLandAI: Personalized Fairy Tales utilizing ChatGPT and DALLE-3: In the diverse world of AI-driven storytelling, there is a unique opportunity to engage young audiences with customized, and personalized narratives. This paper introduces FairyLandAI an innovative Large Language Model (LLM) developed through OpenAI's API, specifically crafted to create personalized fairytales for children. The distinctive feature of FairyLandAI is its dual capability: it not only generates stories that are engaging, age-appropriate, and reflective of various traditions but also autonomously produces imaginative prompts suitable for advanced image generation tools like GenAI and Dalle-3, thereby enriching the storytelling experience. FairyLandAI is expertly tailored to resonate with the imaginative worlds of children, providing narratives that are both educational and entertaining and in alignment with the moral values inherent in different ages. Its unique strength lies in customizing stories to match individual children's preferences and cultural backgrounds, heralding a new era in personalized storytelling. Further, its integration with image generation technology offers a comprehensive narrative experience that stimulates both verbal and visual creativity. Empirical evaluations of FairyLandAI demonstrate its effectiveness in crafting captivating stories for children, which not only entertain but also embody the values and teachings of diverse traditions. This model serves as an invaluable tool for parents and educators, supporting them in imparting meaningful moral lessons through engaging narratives. FairyLandAI represents a pioneering step in using LLMs, particularly through OpenAI's API, for educational and cultural enrichment, making complex moral narratives accessible and enjoyable for young, imaginative minds.<|reference_end|>
@article{makridis2024fairylandai:,
    title={FairyLandAI: Personalized Fairy Tales utilizing ChatGPT and DALLE-3},
    author={Georgios Makridis, Athanasios Oikonomou, Vasileios Koukos},
    journal={arXiv preprint arXiv:2407.09467},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.09467},
    primaryClass={cs.AI}
}