This paper presents a comprehensive survey of ChatGPT and GPT-4, state-of-the-art large language models (LLM) from the GPT series, and their prospective applications across diverse domains. Indeed, key innovations such as large-scale pre-training that captures knowledge across the entire world wide web, instruction fine-tuning and Reinforcement Learning from Human Feedback (RLHF) have played significant roles in enhancing LLMs' adaptability and performance. We performed an in-depth analysis of 194 relevant papers on arXiv, encompassing trend analysis, word cloud representation, and distribution analysis across various application domains. The findings reveal a significant and increasing interest in ChatGPT/GPT-4 research, predominantly centered on direct natural language processing applications, while also demonstrating considerable potential in areas ranging from education and history to mathematics, medicine, and physics. This study endeavors to furnish insights into ChatGPT's capabilities, potential implications, ethical concerns, and offer direction for future advancements in this field.

翻译：本文对GPT系列中最先进的大语言模型ChatGPT与GPT-4及其跨领域潜在应用进行了全面综述。事实上，大规模预训练（从万维网捕获知识）、指令微调及基于人类反馈的强化学习等关键创新，在提升大语言模型的适应性与性能方面发挥了重要作用。我们对arXiv上194篇相关论文进行了深度分析，涵盖趋势分析、词云表示及多应用领域分布分析。研究结果表明，学术界对ChatGPT/GPT-4的研究兴趣显著且持续增长，研究重心虽集中于直接的自然语言处理应用，但在教育、历史、数学、医学及物理学等领域亦展现出巨大潜力。本研究旨在深入剖析ChatGPT的能力、潜在影响及伦理问题，并为该领域的未来进展提供方向指引。