A Compact Guide to Large Language Models

This white paper provides a comprehensive examination of large language models (LLMs), which are artificial intelligence systems designed to process and analyze extensive natural language data. The document begins with a definition of LLMs and outlines their significance in various applications, including natural language processing and machine translation. It presents a brief historical overview of LLM development, highlighting key advancements from the 1990s to 2023, such as the introduction of GPT-3 and GPT-4 by OpenAI and BERT by Google. The paper explains how LLMs function, detailing their training processes and the importance of human feedback. It also discusses the practical applications of LLMs in organizations, including customer support, sentiment analysis, and content generation. Furthermore, the document contrasts proprietary LLM services with open-source models, addressing the trade-offs between performance, cost, and data privacy. The conclusion emphasizes the necessity of a strong data foundation for effective LLM implementation.