从文本到变革：大语言模型多功能性的综合综述
From Text to Transformation: A Comprehensive Review of Large Language Models' Versatility
AI总结：
本文系统综述了GPT、BERT等大语言模型在技术、金融、医疗、教育等领域的应用，并重点识别其在健身健康、城市规划、气候建模和灾害管理等尚未充分开发领域的潜力与研究方向。
摘要：
这项开创性研究探讨了大语言模型（LLMs）的广阔应用范围，例如生成式预训练Transformer（GPT）和来自Transformer的双向编码器表示（BERT），涵盖从技术、金融、医疗保健到教育等多个领域。尽管这些LLMs在自然语言处理（NLP）领域已展现出公认的能力，但尚未被系统地研究其对健身与整体健康、城市规划、气候建模以及灾害管理等领域的潜在影响。除对LLMs在不同领域中广泛用途的广度和程度进行全面分析外，本综述还识别了研究空白以及LLMs潜力尚未被充分发掘的领域。本研究揭示了LLMs在健身与健康、城市规划、气候建模和灾害响应等领域留下印记的创新方式，这些发现有望为上述方向的未来研究和应用提供启发。
英文摘要：
This groundbreaking study explores the expanse of Large Language Models (LLMs), such as Generative Pre-Trained Transformer (GPT) and Bidirectional Encoder Representations from Transformers (BERT) across varied domains ranging from technology, finance, healthcare to education. Despite their established prowess in Natural Language Processing (NLP), these LLMs have not been systematically examined for their impact on domains such as fitness, and holistic well-being, urban planning, climate modelling as well as disaster management. This review paper, in addition to furnishing a comprehensive analysis of the vast expanse and extent of LLMs' utility in diverse domains, recognizes the research gaps and realms where the potential of LLMs is yet to be harnessed. This study uncovers innovative ways in which LLMs can leave a mark in the fields like fitness and wellbeing, urban planning, climate modelling and disaster response which could inspire future researches and applications in the said avenues.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
