Study on the Design of a ChatGPT-Based Metaverse Platform Model

Hyoeun Lee, Honam Shim
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Abstract

Interactivity is the most critical factor in the success of metaverse platforms, which can provide a unique user experience through interaction with digital avatars and engagement in a shared space. As a conversational artificial intelligence (AI) service, ChatGPT is considered a promising approach to dramatically improve the quality of interactions with computational agents on existing metaverse platforms. The ability of large language models (LLMs) to understand and respond to human communication can be expected to enable more immersive and realistic experiences. Therefore, in this study, we developed a computational model to enhance interaction with AI agents on a virtual campus on the Korea Polytechnics University metaverse platform by using ChatGPT. In future research, we plan to create an LLM with unique domain data related to Korea Polytechnic University and the National Competency Standards (NCS) along with industrial and personal data and implement the model by fine‑tuning a specially designed architecture with a pretrained framework. We plan to apply this system to the virtual Polytech Metaverse Campus for testing and monitoring. We will also perform quantitative and qualitative analyses based on advice from technical experts and the results of objective evaluations.
基于chatgpt的元宇宙平台模型设计研究
互动性是虚拟世界平台成功的最关键因素,它可以通过与数字化身的互动和共享空间的参与提供独特的用户体验。作为一种会话式人工智能(AI)服务,ChatGPT被认为是一种有前途的方法,可以显著提高现有元宇宙平台上与计算代理的交互质量。大型语言模型(llm)理解和响应人类交流的能力可以实现更加身临其境和现实的体验。因此,在本研究中,我们开发了一个计算模型,通过ChatGPT在韩国理工大学的虚拟校园中增强与AI代理的交互。在未来的研究中,我们计划创建一个LLM,其中包含与韩国理工大学和国家能力标准(NCS)相关的独特领域数据以及工业和个人数据,并通过微调带有预训练框架的特别设计架构来实现该模型。我们计划将该系统应用于虚拟理工大学的虚拟校园进行测试和监控。我们还将根据技术专家的建议和客观评估的结果进行定量和定性分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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