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This chapter revisits key themes and underpins the contributions of this book in a broader sense. The discussion includes the evolution of LLMs, from early developments to the widespread adoption of ChatGPT and other models, highlighting their impact on research and applications. The chapter summarizes the transformative potential of LLMs in NLA, emphasizing their role in supporting qualitative insights by extracting soft data, which is crucial for nuanced decision making. It also provides a rationale for emerging techniques such as fine-tuning, enrichment strategies, and the importance of addressing environmental, legal and ethical considerations. The chapter concludes by discussing future directions and implications of LLMs in both organizational and societal contexts, encouraging further exploration and responsible innovation in this rapidly evolving field.

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Conclusion

  • 章节

  • 发表日期：

    2025年

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  • Francisco S. Marcondes,
  • Adelino Gala,
  • Renata Magalhães,
  • Fernando Perez de Britto,
  • Dalila Durães,
  • Paulo Novais

摘要

This chapter revisits key themes and underpins the contributions of this book in a broader sense. The discussion includes the evolution of LLMs, from early developments to the widespread adoption of ChatGPT and other models, highlighting their impact on research and applications. The chapter summarizes the transformative potential of LLMs in NLA, emphasizing their role in supporting qualitative insights by extracting soft data, which is crucial for nuanced decision making. It also provides a rationale for emerging techniques such as fine-tuning, enrichment strategies, and the importance of addressing environmental, legal and ethical considerations. The chapter concludes by discussing future directions and implications of LLMs in both organizational and societal contexts, encouraging further exploration and responsible innovation in this rapidly evolving field.