The Commercialization Path of Large Language Models in Start-Ups

Recently, large language models (LLMs) have demonstrated strong performance in large-scale natural language processing tasks and have been widely adopted by many companies in the market. But in reality, for most start-ups, how to get their commercialization right is still a problem. This paper will analyze in detail the challenges posed to start-ups during the commercialization process of large language models, such as cost, economic constraints, compliance with relevant data protection laws, and adaptability to market demands, and provide solutions for technology integration, industry personalized design, and multiple commercialization models to help them successfully complete the commercialization process. In addition, it presents the benefits for start-ups in exploring new markets and globalization strategies. Finally, the paper summarizes the current commercialization status and future development trends of large language models and puts forward some perspectives and suggestions on the rational use of large language models to facilitate commercialization in start-ups.