Practical Applications of Large Language Models in Enterprise-Level Applications

Abstract

As a key achievement in the field of artificial intelligence, the Large Language Model (LLM) has great potential for development in enterprise applications. This study explores the widely used big language models and elaborates on their application capabilities in processing natural language, creating text content, and data parsing. It also analyzed the key issues that enterprises encounter when utilizing big language models, such as data security vulnerabilities, accuracy errors, system integration difficulties, and employee adaptability. A series of response strategies are proposed to address these issues, such as developing standardized frameworks, strengthening data privacy protection, conducting model refinement and validation, balancing cloud services and localized deployment, and increasing acceptance of new technologies through employee education. Provide reference and operational guidelines for enterprises to efficiently and securely implement large-scale language models.