The field of large language models (LLMs) is rapidly evolving, driving significant shifts in research priorities across diverse conferences and fields. Recent studies have highlighted the potential of LLMs to automate data engineering tasks, generate human-like text, and promote equity in academic writing. However, LLMs also face substantial limitations in real-world enterprise scenarios, resulting in significant accuracy drops. The increasing importance of LLMs is expected to lead to a considerable increase in network traffic, requiring network operators to be prepared to address the resulting demands. Noteworthy papers include: The study on analyzing 16,193 LLM papers, which provides a comprehensive analysis of the publication trend of LLM-related papers in top-tier computer science conferences. The report on ChatGPT as a linguistic equalizer, which demonstrates that ChatGPT significantly enhances lexical complexity in non-native English-speakers' authored abstracts.