Large Language Models (LLMs) like GPT-3 and GPT-4 have emerged as groundbreaking innovations with capabilities that extend far beyond traditional AI applications. These sophisticated models, trained on massive datasets, can generate human-like text, respond to complex queries, and even write and interpret code. Their potential to revolutionize software development has captivated the software engineering (SE) community, sparking debates about their transformative impact. Through a critical analysis of technical strengths, limitations, real-world case studies, and future research directions, this paper argues that LLMs are not just reshaping how software is developed but are redefining the role of developers. While challenges persist, LLMs offer unprecedented opportunities for innovation and collaboration. Early adoption of LLMs in software engineering is crucial to stay competitive in this rapidly evolving landscape. This paper serves as a guide, helping developers, organizations, and researchers understand how to harness the power of LLMs to streamline workflows and acquire the necessary skills.

翻译：以GPT-3和GPT-4为代表的大型语言模型（LLMs）已成为突破性创新，其能力远超传统人工智能应用范畴。这些基于海量数据集训练的复杂模型能够生成类人文本、响应复杂查询，甚至编写与解释代码。它们彻底变革软件开发的潜力已引起软件工程（SE）社区的广泛关注，并引发了关于其变革性影响的激烈讨论。本文通过对技术优势、局限性、实际案例研究及未来研究方向的批判性分析，论证了LLMs不仅正在重塑软件开发方式，更在重新定义开发者的角色。尽管挑战依然存在，但LLMs为创新与协作提供了前所未有的机遇。在软件工程领域尽早采用LLMs对于在这快速演进的环境中保持竞争力至关重要。本文可作为指导手册，帮助开发者、组织及研究人员理解如何运用LLMs的力量来优化工作流程并掌握必要技能。