Abstract: The emergence of ChatGPT marks the advent of the era of artificial intelligence powered by large language models ( LLM ). Based on large-scale datasets for pre-training, LLMs demonstrate exceptional adaptability and creativity, becoming a critical driving force in advancing society and playing a significant role in systematic artificial intelligence. Given the limitations of existent reviews in analyzing the challenges faced by LLMs, their key attributes, and engineering implementation aspects. The framework is rediscussed and reconstructed from three dimensions: technical connotations, industry applications, and major challenges. The focus is on elucidating the connotation on the level of technical aspects of LLMs, including system architecture, training strategies, model scale, compression, multimodal fusion, prompting, and planning. It also explores the application prospects in various fields such as education, scientific research, healthcare, finance, and justice. Additionally, the discussion covers the current state of research on the reliability, controllability, and security of LLMs, as well as the dual challenges LLMs face on both technical and societal levels. It envisions the role of LLMs in systematic artificial intelligence and identifies alignment points in research directions, aiming to provide new perspectives and ideas for the research and application of LLMs.

Key words: large language models, multimodal models, trustworthiness, controllability, systematic artificial intelligence