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：本文全面综述了ChatGPT和GPT-4——GPT系列中最先进的大语言模型（LLM）及其在各领域的潜在应用。实际上，大规模预训练（可捕获全球互联网知识）、指令微调以及基于人类反馈的强化学习（RLHF）等关键创新，在提升LLM的适应性和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入分析，涵盖趋势分析、词云表示以及不同应用领域的分布分析。研究结果表明，ChatGPT/GPT-4研究呈现出显著且持续增长的兴趣，主要集中在直接的自然语言处理应用领域，同时在教育、历史、数学、医学和物理学等领域也展现出巨大潜力。本研究旨在深入解析ChatGPT的能力、潜在影响和伦理问题，并为该领域的未来发展指明方向。