Abstract

Open Language Models (OLMs) and edge intelligence have become pivotal in Natural Language Processing (NLP), showcasing significant potential in language generation, text classification, machine translation, and human–computer interaction. This paper focuses on ChatGPT, an open-source large dialogue model based on OpenAI's GPT architecture. It is an emerging trend in the field of artificial intelligence, which aims to expand the language model capabilities on powerful central servers to edge devices, thereby achieving more efficient and flexible applications. Utilizing a Transformer-based encoder–decoder framework with multi-head self-attention mechanisms, ChatGPT excels in generating natural, contextually-aware language responses, akin to human conversation. Edge intelligence combined with ChatGPT can provide more intelligent and personalized services. Despite its advancements, challenges remain regarding model complexity and data demands. We propose enhancements in training methodologies, model architecture, and application domains to foster more intelligent and fluid dialogue systems. Our research highlights ChatGPT and edge intelligence's contributions to both academic inquiry and practical innovation, positioning it to deliver high-quality AI services across various fields.

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Cite this article

@article{cai-7816,
  author  = {Xiaokui Liu and Wenting Wu},
  title   = {Exploration of ChatGPT Open Large Language Model and Edge Intelligence},
  journal = {Computing and Informatics},
  volume  = {45},
  number  = {3},
  pages   = {726--747},
  year    = {2026},
  issn    = {1335-9150},
  doi     = {10.31577/cai_2026_3_726}
}
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