The Development History, Technological Optimization, and Multi-Domain Applications of Large Language Models

Large language model is one of the most popular research directions in the world.In view of its rapid development and far-reaching impact on society, this paper systematically reviews the development process, technology optimization and its application of large language model (LLMS).From the early natural language processing (NLP) rule-driven stage to the Transformer architecture revolution based on deep learning, LLMs have achieved a paradigm breakthrough in language understanding through parameter scale expansion and pre-training technology innovation.Large models represented by GPT series and BERT show strong generalization ability and emergent characteristics, but they are faced with challenges such as computational resource consumption, insufficient interpretability and ethical alignment.The optimization technique covers pre-training, cue learning, and fine-tuning, which significantly improves the efficiency of the model in task adaptation.In terms of applications, LLMs have penetrated into education, finance, health care and manufacturing to promote intelligent upgrading, while addressing issues such as data privacy, professional field adaptation and reliability in high-risk scenarios.The rapid development of China's big models (such as Wenxin, Tongyi, DeepSeek, etc.) marks the rise of local technology, but international competition and sustainable development still need to be continuously explored.