Recently, the 801st academic symposium of Xiangshan Science Conference, with the theme of "Intelligent Scientific Research New Ecology: Standard Foundation Building, Collaborative Symbiosis", was held in Beijing. Experts attending the meeting pointed out that artificial intelligence (AI) is driving a paradigm shift in scientific research, but the unified standards of various platforms are seriously lagging behind, which has restricted the large-scale promotion and application of intelligent research platforms. It is urgent to accelerate the construction of a national level standard system for intelligent research platforms, and provide a unified technical framework and normative foundation for their development. Against the backdrop of the rapid development of AI for Science, AI and automation technologies have significantly improved research and development efficiency in fields such as batteries, photovoltaics, and catalytic materials. They have also significantly shortened the target screening and efficacy prediction cycles in innovative drug development. ”Director Ouyang Hongwei of Liangzhu Laboratory said. Ouyang Hongwei emphasized that compared to the above-mentioned fields, the research and development of biomaterials involves three interrelated links: chemical synthesis, structural construction, and biological response. Moreover, the biological verification cycle is long and the feedback cost is high, making it difficult to directly replicate existing paradigms. The use of AI assisted biomaterials research and development is still in its infancy. Xie Zaiku, an academician of the CAS Member and the chief scientist of Sinopec, combined with his research and development experience in the field of methanol to olefin molecular sieve industrial catalytic materials, pointed out that the high-throughput intelligent scientific research platform showed significant advantages: the experimental screening efficiency was significantly improved, the research and development cost was effectively reduced, and the research and development cycle was significantly shortened, which promoted the whole process innovation from material design, material screening, performance evaluation to process amplification. In recent years, driven by the synergy of artificial intelligence, large-scale models, automated experimental equipment, and high-performance computing technology, the paradigm of scientific research is undergoing profound changes, and its industrialization path is constantly being clarified. From a policy perspective, China has made systematic arrangements for empowering scientific research with artificial intelligence at the national level, explicitly requiring AI to lead the paradigm shift in scientific research and accelerate breakthroughs in technological innovation in various fields. In August 2025, the "Opinions of the State Council on Deepening the Implementation of the 'Artificial Intelligence+' Action" was officially released, which clearly stated the need to accelerate the process of scientific discovery, drive innovation in technology research and development models, and improve efficiency. The arrival of the AI era has completely changed the paradigm of traditional scientific research. ”Liu Tieyan, Secretary of the Party Committee and Dean of Beijing Zhongguancun College, pointed out that the efficiency of scientific discoveries has achieved a significant leap. Whether it is the digital simulation of new materials, structural prediction, or high-throughput output of independent laboratories, a large number of "new discoveries" have been generated with a flux of "hundreds of thousands, hundreds of millions". Liu Tieyan emphasized that the human ability to verify and digest these "new discoveries" has always maintained a linear growth, forming a huge speed difference between the two, which is a new challenge that has never appeared in the traditional scientific research paradigm in the past 300 years. In the face of the scientific research revolution in the AI era, the core breakthrough point is not to continue improving the efficiency of AI tools, but to reconstruct scientific evaluation standards, clarify talent training directions, and establish efficient achievement screening mechanisms. ”He said. At present, it is a critical period for the coordinated development of unified standards. Although China has made significant progress in the construction of intelligent scientific research platforms, it must be soberly recognized that the biggest risk facing the current development of intelligent scientific research is not the lack of platforms, but the increasing number of platforms that are increasingly incompatible with each other, with each acting independently, fragmented architecture, data barriers, and incompatible interfaces, which have become direct obstacles to cross institutional collaboration and large-scale innovation. ”Yang Jinlong, academician of the CAS Member and president of Tongji University, pointed out at the meeting. At present, the construction of intelligent scientific research platforms in China is in a period of strategic opportunities for rapid development, but the pattern of 'multiple heads advancing simultaneously' has also led to fragmented industrial ecology. ”Professor Jiang Jun from the National Key Laboratory of Precision and Intelligent Chemistry at the University of Science and Technology of China stated that standardization, as a key means to ensure the "soft power" of scientific and technological innovation, is the only way to lead intelligent research platforms to break through silos and move towards high-quality and orderly development. However, problems such as the lack of core technology testing and evaluation, insufficient sharing of scientific research data, and difficulties in interconnecting experimental facilities are becoming bottlenecks that restrict the leap of intelligent research towards scale and industrialization. Wang Kun, Secretary of the Party Committee and President of the China Institute of Standardization, also believes that intelligent scientific research is at a critical stage of transitioning from "laboratory bonsai" to "industrial landscape". However, the current industrial scale still faces multiple obstacles: firstly, expensive equipment, complex systems, and high thresholds for user procurement decisions; Secondly, the technology routes are scattered, the product forms are diverse, and the market transaction costs remain high; The third is the lack of a unified quality evaluation system, which makes users "afraid to buy, unable to use, and unable to use well", resulting in a "bottleneck" for the expansion of the industry scale. Standards play an important role in reducing manufacturing costs, transaction costs, and establishing trust mechanisms. ”Wang Kun further stated that with unified standards, components produced by different manufacturers can be plug and play, which not only reduces the difficulty of system integration, but also promotes the shift of hardware equipment from "customized development" to "large-scale production". And interface interoperability standards not only allow users to avoid worrying about being bound by vendors, but also enable suppliers to avoid repeatedly adapting system interfaces for each customer. Standards are like the "universal language" of market transactions, which can significantly reduce the cycle and cost from demand matching to implementation. Only when users firmly believe that 'products that meet standards can be used and are easy to use', can the market truly move from 'individual case procurement' to 'scale application'. To efficiently promote the standardization of intelligent scientific research, a national standardization working group for intelligent scientific research platforms should be established as soon as possible, bringing together core scientific research forces such as national laboratories, top universities, and leading enterprises to lead the formulation and revision of relevant national standards in China. ”Wang Kun believes that the working group needs to closely follow the evolution of the industry and comprehensively carry out the development of national standards in core dimensions such as basic commonality, multi-source data interoperability, security, and ethics. Wang Kun pointed out that "pre standardization" can be used as an important means to promote the standardization of intelligent scientific research, building a channel for early recognition and consensus building for original innovation, and forming a positive cycle of "innovation standardization re innovation". At the same time, we need to explore new paradigms for international cooperation, jointly build an inclusive and inclusive ecosystem of intelligent scientific research rules, and accelerate the construction of a standardized "tripod shaped" composite leading talent team for intelligent scientific research. The most urgent task at present is not to continue building new isolated platforms, but to establish a national level intelligent research platform standard system as soon as possible. ”Yang Jinlong also believes that. Specifically, Yang Jinlong proposed four suggestions: firstly, to elevate the standardized construction of intelligent scientific research platforms to the core task of national new scientific research infrastructure construction; Secondly, accelerate the full chain collaboration of data, models, equipment, and processes; Thirdly, relying on the standardization working group of the national intelligent scientific research platform, we will quickly form a standard white paper and systematic standard framework; Fourthly, we must adhere to the unity of openness, sharing, autonomy, and controllability, and shape a new order, new capabilities, and new ecology of intelligent scientific research in China through collaborative construction. He emphasized that "co construction, sharing, and win-win" is not a general vision for cooperation, but should become the basic principle for the future construction of intelligent scientific research ecology in China. It is worth mentioning that the "White Paper on Intelligent Research Platform Standards" (2026 version) jointly compiled by the University of Science and Technology of China and the China Institute of Standardization has established six core sections covering basic universality, data, model and AI base, experimental infrastructure, platform security, and platform ecosystem construction, forming the "four beams and eight pillars" that support the development of intelligent research. With the improvement of the standardization system and the establishment of cross platform collaboration mechanisms, resource barriers between different research institutions and disciplines will be further broken down, forming an open, shared, and interconnected global scientific research ecosystem. Innovative elements such as computing power, data, models, and equipment will flow freely and be efficiently configured, promoting deep interdisciplinary and cross regional collaboration and accelerating joint tackling of major scientific challenges. ”Jiang Jun stated. (New Society)