Abstract
This paper explores the rapidly evolving domain of Artificial Intelligence Language Models (LLMs). It delves into the impact of these models on technology and society, highlighting their applications and potential future developments. The study offers insights into how LLMs are reshaping the landscape of communication, information processing, and AI interactions. At the forefront of modern technological advancements, LLMs such as GPT-4, BERT, and T5 have redefined the boundaries of human-computer interaction through their ability to understand, generate, and engage in human language with remarkable proficiency. Through a comprehensive literature review and analysis of these models, this study sheds light on the historical development, underlying technologies, and current capabilities of LLMs. Employing a mixed-methods approach, the paper synthesizes both quantitative data and qualitative insights to reveal the transformative impact of LLMs across various sectors, including education, healthcare, and business communication. Key findings indicate not only a significant advancement in natural language understanding and generation but also highlight the challenges and ethical considerations inherent in the rapid development of these models. The paper concludes by discussing the potential future trajectory of LLMs, underscoring the necessity for continued innovation balanced with ethical and responsible AI development. This study aims to contribute to the broader understanding of AI LLMs, offering insights into their current applications and charting a course for future research in this dynamic field.
The paper concludes by discussing the potential future trajectory of LLMs, underscoring the necessity for continued innovation balanced with ethical and responsible AI development. This study aims to contribute to the broader understanding of AI LLMs, offering insights into their current applications and charting a course for future research in this dynamic field.
References
- Chaitanya K, Rolla KJ. The Evolution and Impact of Large Language Models in Artificial Intelligence. InAlgorithms in Advanced Artificial Intelligence 2024 Jul 8 (pp. 410-417). CRC Press.
- Ashish V. Attention is all you need. Advances in neural information processing systems. 2017;30: I. https://doi.org/10.48550/arXiv.1706.03762
- Kasneci E, Seßler K, Küchemann S, Bannert M, Dementieva D, Fischer F, Gasser U, Groh G, Günnemann S, Hüllermeier E, Krusche S. ChatGPT for good? On opportunities and challenges of large language models for education. Learning and individual differences. 2023 Apr 1; 103:102274. https://doi.org/10.1016/j.lindif.2023.102274
- Radford A, Wu J, Child R, Luan D, Amodei D, Sutskever I. Language models are unsupervised multitask learners. OpenAI blog. 2019 Feb 24;1(8):9.
- Hadi MU, Qureshi R, Shah A, Irfan M, Zafar A, Shaikh MB, Akhtar N, Wu J, Mirjalili S. Large language models: a comprehensive survey of its applications, challenges, limitations, and future prospects. Authorea preprints. 2023 Nov 16;1(3):1-26. https://doi.org/10.36227/techrxiv.23589741.v1
- Tayan O, Hassan A, Khankan K, Askool S. Considerations for adapting higher education technology courses for AI large language models: A critical review of the impact of ChatGPT. Machine Learning with Applications. 2024 Mar 1; 15:100513. https://doi.org/10.1016/j.mlwa.2023.100513
- Alqahtani T, Badreldin HA, Alrashed M, Alshaya AI, Alghamdi SS, Bin Saleh K, Alowais SA, Alshaya OA, Rahman I, Al Yami MS, Albekairy AM. The emergent role of artificial intelligence, natural learning processing, and large language models in higher education and research. Research in social and administrative pharmacy. 2023 Aug 1;19(8):1236-42. https://doi.org/10.1016/j.sapharm.2023.05.016
- Turing AM. Computing machinery and intelligence (1950). Mind. 2021 Feb 2;59(236):33-60. http://dx.doi.org/10.1093/mind/LIX.236.433
- Devlin J, Chang MW, Lee K, Toutanova K. Bert: Pre-training of deep bidirectional transformers for language understanding. InProceedings of the 2019 conference of the North American chapter of the association for computational linguistics: human language technologies, volume 1 (long and short papers) 2019 Jun (pp. 4171-4186). https://doi.org/10.18653/v1/N19-1423
- Johnsen M. Developing AI Applications with Large Language Models. Maria Johnsen; 2025 Jan 18.
- Zhao WX, Zhou K, Li J, Tang T, Wang X, Hou Y, Min Y, Zhang B, Zhang J, Dong Z, Du Y. A survey of large language models. arXiv preprint arXiv:2303.18223. 2023 Mar 31;1(2). https://doi.org/10.48550/arXiv.2303.18223
- Chang Y, Wang X, Wang J, Wu Y, Yang L, Zhu K, Chen H, Yi X, Wang C, Wang Y, Ye W. A survey on evaluation of large language models. ACM transactions on intelligent systems and technology. 2024 Mar 29;15(3):1-45. https://doi.org/10.1145/3641289
- Shen Y, Heacock L, Elias J, Hentel KD, Reig B, Shih G, Moy L. ChatGPT and other large language models are double-edged swords. Radiology. 2023 Jan 26;307(2): e230163. https://doi.org/10.1148/radiol.230163
- Fatima M. Revolutionizing Interaction: Exploring the Impact of ChatGPT in Education. International Journal of Advances in Business and Management Research (IJABMR). 2023 Dec 12;1(2):19-30. https://doi.org/10.62674/ijabmr.2024.v1i02.003
- Bharathi Mohan G, Prasanna Kumar R, Vishal Krishh P, Keerthinathan A, Lavanya G, Meghana MK, Sulthana S, Doss S. An analysis of large language models: their impact and potential applications. Knowledge and Information Systems. 2024 Sep;66(9):5047-70. https://doi.org/10.1007/s10115-024-02157-9
- Myers D, Mohawesh R, Chellaboina VI, Sathvik AL, Venkatesh P, Ho YH, Henshaw H, Alhawawreh M, Berdik D, Jararweh Y. Foundation and large language models: fundamentals, challenges, opportunities, and social impacts. Cluster Computing. 2024 Feb;27(1):1-26. https://doi.org/10.1007/s10586-023-04203-7
- Chakraborty S. A Study on Hybrid Recommender Systems for Effective Targeted Marketing in E-Commerce Platforms. International Journal of Advances in Business and Management Research (IJABMR). 2025 Jun 12;2(4):54-64. https://doi.org/10.62674/ijabmr.2025.v2i04.006
