Version 1
: Received: 13 September 2024 / Approved: 13 September 2024 / Online: 14 September 2024 (10:37:03 CEST)
How to cite:
Li, Y.; Yang, Y.; Zhao, C.; Cao, C. Large Language Models in Entrepreneurship: A Survey. Preprints2024, 2024091085. https://doi.org/10.20944/preprints202409.1085.v1
Li, Y.; Yang, Y.; Zhao, C.; Cao, C. Large Language Models in Entrepreneurship: A Survey. Preprints 2024, 2024091085. https://doi.org/10.20944/preprints202409.1085.v1
Li, Y.; Yang, Y.; Zhao, C.; Cao, C. Large Language Models in Entrepreneurship: A Survey. Preprints2024, 2024091085. https://doi.org/10.20944/preprints202409.1085.v1
APA Style
Li, Y., Yang, Y., Zhao, C., & Cao, C. (2024). Large Language Models in Entrepreneurship: A Survey. Preprints. https://doi.org/10.20944/preprints202409.1085.v1
Chicago/Turabian Style
Li, Y., Chaoran Zhao and Chunling Cao. 2024 "Large Language Models in Entrepreneurship: A Survey" Preprints. https://doi.org/10.20944/preprints202409.1085.v1
Abstract
Large Language Models (LLMs) have emerged as powerful tools in the domain of artificial intelligence, specifically enhancing natural language processing capabilities. These models leverage extensive datasets and sophisticated algorithms to automate and enhance tasks traditionally performed by humans, thereby revolutionizing innovation and entrepreneurship. LLMs accelerate product development, streamline business operations, and enable precise and rapid decision-making, all of which are crucial for maintaining competitiveness in dynamic markets. This paper categorizes the applications of LLMs in innovation and entrepreneurship into three main areas: technological innovation, strategic decision-making, and process automation. By exploring various integrations of LLMs in entrepreneurial ventures, this work offers both theoretical insights and practical examples, underscoring the transformative impact of LLMs in shaping modern business landscapes.
Keywords
Large Language Models; Entrepreneurship
Subject
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
