Vision and Opinion Open access

AI in the era of large language models: current state, applications, limitations, and future

Authors

  • Yiqun Zhang School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China.
  • Yiu-ming Cheung Corresponding author Email https://orcid.org/0000-0001-7629-4648 Department of Computer Science, Hong Kong Baptist University, Hong Kong, China.
Published
December 5, 2025
Section
Vision and Opinion
DOI
10.4081/peasa.68

Abstract

Have you noticed how Artificial Intelligence (AI) has suddenly shifted from sci-fi movies to our daily text messages? Today, tools like ChatGPT, DeepSeek, and Gemini allow us to chat, create, and solve problems as if talking to a knowledgeable friend. But what exactly are these Large Language Models (LLMs), and are they equivalent to AI? This article demystifies how AI has entered a new era of "Daily Conversation", guides you through its powerful applications and risks, and finally looks ahead to a future of AI. Are you ready to dance with AI? Let's find out what these super digital brains really are!

Keywords

References

  1. Das BC, Amini MH, Wu Y (2025). Security and privacy challenges of large language models: A survey. ACM Comput Surv 57:1-39. DOI: https://doi.org/10.1145/3712001
  2. European Commission (2021). Proposal for a Regulation of the European Parliament and of the Council laying down harmonised rules on artificial intelligence (Artificial Intelligence Act) and amending certain union legislative acts. 2021. Available from: https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A52021PC0206
  3. Zamfirescu-Pereira JD, Wong RY, Hartmann B, Yang Q (2023). Why Johnny can’t prompt: how non-AI experts try (and fail) to design LLM prompts. Proc. 2023 CHI Conf. on Human Factors in Computing Systems. New York, Association for Computing Machinery; 2023. pp. 1-21. DOI: https://doi.org/10.1145/3544548.3581388
  4. Zhang Y, Zhao M, Zhang Y, Cheung YM (2025). Trending applications of large language models: a user perspective survey. IEEE Trans Artif Intell. Online Ahead of Print. DOI: https://doi.org/10.1109/TAI.2025.3620272

Metrics

Citations and online attention from Dimensions, Altmetric and PlumX.

PlumX Metrics

Downloads

Download data is not yet available.

License

Copyright (c) 2025 The Author(s)

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

PAGEPress has chosen to apply the Creative Commons Attribution NonCommercial 4.0 International License (CC BY-NC 4.0) to all manuscripts to be published.