Abstract: Currently, the technology of large language models is evolving rapidly and accelerating its integration in geological disaster prevention and control. It has been expanding the application scenarios and breaking the limitations in data analysis and complex modeling capabilities as well as innovating the traditional research paradigm. To further promote new breakthroughs in AI technologies in the intelligent prevention and control of geological disasters, this article reviews the evolution characteristics of large language model technology and the application scenarios in multiple fields, and also discusses the key technologies including small sample learning, multimodal data fusion, lightweight model and transfer application, as well as expert knowledge embedding and human-computer collaboration, which are also the main ideas and research focus directions for achieving intelligent identification of geological disaster hazards. The article also proposes an "AI + geological disasters" research framework, technical ideas and typical application scenarios based on core elements including "application scenarios, key issues, mechanism of action, data modalities, sample characteristics, model development, expert knowledge, and human-computer collaboration". This highlights the important value of AI technology in geological disasters research in solving the dealing with multi-dimensional, multi-scale, nonlinear and complex relationship modeling problems. The purpose of this article is to promote AI technologies to integrate into geological disaster prevention and control work at a deeper level, from data, models, and knowledge, and also better leverage AI technology to promote the development of disaster prevention and mitigation towards a greater precision and intelligence.