" AI for Science " (AI4S) is a new scientific research paradigm that deeply integrates AI technology with scientific research to promote the discovery of new knowledge and the solution of scientific problems. As the application of AI4S in the natural sciences and humanities and social sciences advances, its development line, opportunities and challenges, needs and tasks, and ways of realization deserve further discussion. In order to advance AI4S research, promote scientific and technological (S&T) innovation and progress, and facilitate the effective strengthening of the discipline of information resources management, our journal has invited seven experts to organize this academic conversation on AI4S. 1) Supporting knowledge services for AI4S: In the current landscape of intelligent knowledge services, the requirements for supporting AI4S have increased, including the need for multi-level knowledge discovery and acquisition, cross-disciplinary research and innovation, and user-friendly participatory services. In addition, knowledge service scenarios are moving towards diversification, complexity, depth, specialization, and personalization in ubiquitous knowledge discovery, generative content services, and multi-round interactive service exploration. In response, professional science and technology information organizations need to reassess the role of knowledge services in the AI4Science environment and their significance in comprehensively supporting the S&T innovation process. This involves establishing a broad literature perspective, deepening full-text knowledge elements, balancing universal and specialized depth, autonomously developing core products, and deeply engaging with professional fields to support interdisciplinary innovation. 2) As a knowledge base for AI4S: In the development of AI4S, S&T literature serves as a high-quality corpus of great importance and utility. The Documentation and Intelligence Center of the Chinese Academy of Sciences has developed the concept and general framework for an AI4S knowledge base utilizing S&T literature. It is dedicated to building four types of knowledge bases to support intelligent services such as evidence-based retrieval, situational awareness, inference prediction, and insight generation required for AI4S applications. In addition, to advance the AI for Science knowledge base, it is essential to actively promote the construction of an intelligent data system, develop an AI engine for technical literature knowledge, conduct key technology research on in-depth mining and intelligent analysis of S&T literature, and promote collaboration with scientific research units across various fields, leading AI companies, and teams of field scientists. This approach aims to fully exploit the innovative and developmental value of the discipline of information resource management. 3) Powering AI4S with scientific data: Effective aggregation of scientific data is the foundation for unleashing the powerful capabilities of AI4S. This is essential for libraries to adapt their roles and functions in the AI era and is a crucial prerequisite for catalyzing the transformation of scientific research services, deepening scientific research support, and accelerating S&T innovation. Currently, libraries face various macro and meso challenges in effectively aggregating valuable scientific data to provide support for AI4S. To address these challenges, the following ways can be pursued: defining the roles and functions of libraries in scientific data management; promoting a conducive environment for scientific data management; establishing a collaborative network for scientific data management; and enhancing the service capacity of scientific data management. 4) AI4S and intelligent language modeling for classical literature: AI4S technology can be used to analyze documents and texts, enabling a faster and more comprehensive understanding of a vast amount of historical documents and cultural materials. The development of intelligent language modeling for classical literature represents a significant breakthrough in the field of ancient literature research, bringing new opportunities and challenges. With the increasing popularity of multimodal and generative GPT models in the context of AI4S, the intelligent language modeling of classical literature will focus on integrating diverse information, enhancing adaptability, improving knowledge representation, and addressing a wider range of application scenarios. 5) Library Digital Scholarly Services for AI4S: The concept of using LLM-based AI4S and AIGC to drive the development of smart libraries is consistent with the vision for digital scholarly services in libraries, and presents both opportunities and challenges. Given the trends towards AI4S platformization and the characteristics of "middle-end" digital scholarly service, as well as the longstanding tradition of libraries in serving scholarly research, the reengineering path for the library's digital scholarly services platform includes three approaches: building an AI4S service platform independently, purchasing and utilizing third-party AI4S platforms, and promoting embedded knowledge services as a component of scientific intelligence. This innovative approach addresses the dilemmas of financial resources, human resources, cognitive and practical gaps, and emphasizes the importance of user needs in the AI4S environment. It also focuses on knowledge organization and service delivery to meet user needs in the AI4S landscape. 6) Historical evolution and logical structure of the scientific intelligence paradigm (AI4S): AI4S is a scientific paradigm change dominated by the full application of AI technology to various disciplines, and its logical structure includes "data+model"-driven, knowledge ecology created by machine conjecture, and application scenarios expanded by algorithmic thinking. In the era of digital civilization, AI4S-driven scientific progress and social development must carry forward the value of science and technology for the good, effectively select the theoretical arguments and proposals for extending AI4S to the field of social sciences and humanities, and improve the series of mechanisms for integrating human decision-making and machine intelligence. 7) Development opportunities and prospects of AI4S in the era of generative AI: With the advances in generative AI, pre-training algorithms and large-scale pre-trained models have provided significant opportunities for AI4S in various disciplinary domains. These technologies have shown immense potential and value for applications in diverse fields such as industrial inspection, robotics, and medicine. Additionally, it is crucial to emphasize the importance of key factors such as the constraints of technical implementation conditions for large pre-trained models, the sustainability of data/computing resources, and the transparency, fairness, and accessibility of the technology.

[Purpose/Significance] The continuous development of metaverse technology marks the transition of mankinds from information society to information civilization. How to understand the relationship between human beings, physical space and information space in the future society has become a key problem of the era. The mixed reality (MR) Technology is a new intelligent technology that integrates the advantages of augmented reality (AR) and virtual reality (VR), makes virtual objects coexist in the physical world, and integrates the functions of human perception, computer processing and environmental input. The new generation of MR technology has improved the traditional global understanding of digital reality interaction, and also has been bringing technological innovation opportunities for the development of smart libraries. Exploring the new application scenarios of MR technology is helpful in expanding the depth and breadth of the research on smart libraries. [Method/Process] By using the methods of literature review, content analysis and website analysis, this paper reviews the current research status of MR Technology in the field of library science at home and abroad. In addition, through practical cases, this paper summarizes the relevant experience and existing gaps in the application of MR Technology in domestic and foreign libraries. Therefore, it is clear that the research of this paper aims to further stimulate and release libraries' demand and potential for MR Technology. Specifically speaking, by examining the characteristics of high realism, more intelligent and omni-directional MR technology, this paper further explores the ability of smart libraryies in four dimensions of service, knowledge, experience and collaboration, which will contribute to building a new application scenario of smart libraries with the vision of MR technology. It is hoped that this paper can promote the formation of a new type of smart libraries that combines dynamic and static, actively data, blending virtual-real and multi-dimensional expansion. [Results/Conclusions] In the wave of rapid innovation of VR, the construction of smart libraries should be considered in four dimensions: problem orientation, theoretical supports, talent management and subject co-creation. It can provide a better understanding of the future smart libraries with the possible risks, urgent internal and external needs. It is expected to build a future ecological picture of the integration of smart libraries and MR technology. However, due to the limitation of the author's knowledge level and the lack of practical ability, this paper provides a relatively macro guidance. Libraries vary in their application of MR technology. On specific issues, we need specific analysis and different solutions. Therefore, in the future research, we will continuously improve and refine the research in this aspect, and provide reference basis and application value for the effective practice of MR technology in the smart libraries.

[Purpose/Significance] Investigating the influencing factors in the general requirements of public digital cultural service in Fujian Province can provide reference for its sustainable development in this field. Referring to the previous research, this paper took the lead in using the binary logistic regression model to study public demand for digital cultural services in Fujian Province, and selecting universities in Fujian Province as the research object. It provides a significant practical reference basis for the construction of public digital cultural service in Fujian Province, and also has a certain theoretical reference value for research related to public digital cultural service. [Method/Process] Culture is related to people's well-being and the all-round development of people. In order to meet the people's growing need for a better life and protect the people's basic cultural rights and interests, there are more urgent requirements. Public digital cultural service, in the form of digitalization, breaks the restrictions of time and space, and serves as an important magic weapon to get through the "last mile" of public cultural service and improve the accessibility of the service. Digital construction helps to enhance the accessibility of public cultural service, improve the coverage and dissemination efficiency of the service, and promote public cultural participation. On the basis of the relevant literature, the article intends to discuss the impact and mechanism of public digital cultural service, that is, which factors have an impact on public cultural needs? How do these factors affect the public digital cultural service? What is the impact? Under what conditions is the impact more significant? This study was carried out by combining the methods of literature survey, quantitative and qualitative analysis, and obtaining sample data of users through the questionnaire to analyze the statistics with the SPSS 21 software and verify relevant research hypotheses and regression models. [Results/Conclusions] It is found that resource, subject, platform, infrastructure, and service efficiency can effectively strengthen the requirements for the public digital cultural service in Fujian Province. In view of this, we suggest establishing diversified platforms for digital service, integrating cultural resources, enhancing the establishment of service personnel, strengthening promotion and popularization, optimizing the facility and equipment of public culture, and improving the environment of the places. In the analysis of the influencing factors of public digital cultural service, this study is not comprehensive enough. In the future, it is possible to sort out the factors affecting public digital cultural service more comprehensively, and a more comprehensive sample can be used in our study.