Research Article
Open access
Published on 26 November 2024
Download pdf
Tian,Y. (2024). The Application and Practice of Artificial Intelligence in the Entertainment Field. Applied and Computational Engineering,110,50-54.
Export citation

The Application and Practice of Artificial Intelligence in the Entertainment Field

Yuang Tian *,1,
  • 1 Faculty of Animation, Arts & Design, Sheridan College, Oakville, ON L6H 2L1 Canada

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2755-2721/110/2024MELB0098

Abstract

Artificial intelligence (AI) technology has witnessed unprecedented advancements and a gradual penetration into civilian applications. This paper aims to thoroughly investigate the application of AI in the entertainment industry, with a particular focus on the principles and cross-disciplinary implementations of 3D real-life scanning, AI for non-player characters (NPCs), and AI video generation. By synthesizing how these technologies streamline content creation processes, lower technical barriers, and inspire novel approaches to game design, we observe that AI is not only reshaping the ecosystem of the entertainment sector but also facilitating the entry of newcomers into game development. However, alongside the benefits, this study identifies several challenges and limitations associated with current AI technologies, such as accuracy, cost-effectiveness, and ethical concerns, which require attention and resolution in future research and practice. Through a detailed examination and synthesis of these phenomena, this research provides a reference for practitioners and suggests directions for subsequent studies.

Keywords

Artificial intelligence, 3D scanning, game design, 3D modeling, NPC.

[1]. Arts, E. (2023). Procedural Terrain in EA SPORTS PGA Tour. Electronic Arts Inc. https://www.ea.com/frostbite/news/procedural-terrain-in-ea-sports-pga-tour

[2]. Kasapakis, V., Gavalas, D., & Dzardanova, E. (2024b). 3D Modelling Through Photogrammetry in Cultural Heritage. In Springer eBooks (pp. 23–26).

[3]. Verykokou, S., & Ioannidis, C. (2023). An Overview on Image-Based and Scanner-Based 3D Modeling Technologies. Sensors, 23(2), 596.

[4]. Chapinal-Heras, D., Carlos, D., Natalia, G., Sergio, E., Lucía, P. S., De Corselas Manuel, P. L., & Elías, R. Z. M. (2024). Photogrammetry, 3D modelling and printing: The creation of a collection of archaeological and epigraphical materials at the university. Digital Applications in Archaeology and Cultural Heritage, e00341. https://doi.org/10.1016/j.daach.2024.e00341

[5]. Arts, E. (2019). Photogrammetry and Star Wars Battlefront - Frostbite. Electronic Arts Inc. https://www.ea.com/frostbite/news/photogrammetry-and-star-wars-battlefront

[6]. Arts, E. (2023). Procedural Terrain in EA SPORTS PGA Tour. Electronic Arts Inc. https://www.ea.com/frostbite/news/procedural-terrain-in-ea-sports-pga-tour

[7]. Park, J. S., O’Brien, J. C., Cai, C. J., Morris, M. R., Liang, P., Bernstein, M. S. (2023). Generative Agents: Interactive Simulacra of Human Behavior. arXiv.org. https://arxiv.org/abs/2304.03442

[8]. Cho, J., Puspitasari, F. D., Zheng, S., Zheng, J., Lee, L., Kim, T., Hong, C. S., Zhang, C. (2024). Sora as an AGI World Model? A Complete Survey on Text-to-Video Generation. arXiv.org. https://arxiv.org/abs/2403.05131

Cite this article

Tian,Y. (2024). The Application and Practice of Artificial Intelligence in the Entertainment Field. Applied and Computational Engineering,110,50-54.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

Disclaimer/Publisher's Note

The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of EWA Publishing and/or the editor(s). EWA Publishing and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

About volume

Volume title: Proceedings of CONF-MLA 2024 Workshop: Securing the Future: Empowering Cyber Defense with Machine Learning and Deep Learning

Conference website: https://2024.confmla.org/
ISBN:978-1-83558-739-3(Print) / 978-1-83558-740-9(Online)
Conference date: 21 November 2024
Editor:Mustafa ISTANBULLU, Ansam Khraisat
Series: Applied and Computational Engineering
Volume number: Vol.110
ISSN:2755-2721(Print) / 2755-273X(Online)

© 2024 by the author(s). Licensee EWA Publishing, Oxford, UK. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license. Authors who publish this series agree to the following terms:
1. Authors retain copyright and grant the series right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this series.
2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the series's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this series.
3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See Open access policy for details).