Vol.13, No.1, February 2024.                                                                                                                                                                               ISSN: 2217-8309

                                                                                                                                                                                                                        eISSN: 2217-8333

 

TEM Journal

 

TECHNOLOGY, EDUCATION, MANAGEMENT, INFORMATICS

Association for Information Communication Technology Education and Science


Exploratory Data Analysis and the Rise of Large Language Models - Gaming Industry Insights

 

Denitsa Zhecheva

 

© 2024 Denitsa Zhecheva, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)

 

Citation Information: TEM Journal. Volume 13, Issue 1, Pages 561-569, ISSN 2217-8309, DOI: 10.18421/TEM131-59, February 2024.

 

Received: 15 September 2023.

Revised:   12 December 2023.
Accepted: 19 December 2023.
Published: 27 February 2024.

 

Abstract:

 

The applications of modern large language models are diverse and new at the same time. It is forecasted that the scientific society and businesses may experience a long period of time exploring all opportunities and challenges for using them which will allow analysis of the impact on how advanced generative artificial intelligence is changing work occupation activities and performance efficiency. Undoubtedly, today’s question that every business must answer is not if but how to implement large language models, due to their ability to transform numerous business processes. This study aims to give a better understanding on how large language models are contributing to the process of exploratory data analysis as they are not here to replace the traditional methods but to add generative artificial intelligence capabilities to the well-established ones. The results of this paper reveal high level of accuracy of the paired output between operation prompts in OpenAI’s large language model and human-mediated entry. However, such output comparison highlighs the need for more informative and specific input prompts to ascertain this accuracy. Further caveats that need to be placed in consideration refer to possible system downtimes, as well as the expenses incurred with every prompt execution. Nevertheless, the comparative speed of operation of large language models remains their most substantial competitive advantage. Overall, the findings in this paper contribute to understanding that large language models streamline with ease the desired extraction of insightful information which may further be used for better decision-making, good data management, and design of winning growth strategy as is the case of the gaming industry.

 

Keywords –Large language models, exploratory data analysis, gaming industry, generative artificial intelligence, natural language processing.

 

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