The construction of intelligent scientific research platforms in China has entered an accelerated expansion period. From the "15th Five Year Plan" outline proposing the construction of "scientific research intelligent platforms and high-quality scientific datasets", to universities and institutions investing heavily in the construction of scientific research intelligent platforms, and to artificial intelligence (AI) producing fruitful results in fields such as mathematics, chemistry, and pharmaceuticals, "AI+scientific research" is no longer a castle in the air, but has become a powerful assistant to effectively help scientists improve efficiency. However, at the same time, the lack of unified data standards, inconsistent data production methods, and prominent model barriers in scientific research intelligent platforms seriously hinder the effective integration of interdisciplinary knowledge and large-scale innovation. At the 801st academic symposium of the Xiangshan Science Conference held recently, attending experts suggested accelerating the construction of a universal standard for scientific research intelligent platforms and establishing a new ecosystem for scientific research intelligence. The difficulty in building standards that are compatible with different platforms is of utmost importance in the construction of scientific research intelligent platforms. However, experts present at the conference bluntly stated that the speed of building standards for scientific research intelligent platforms in China is seriously lagging behind the actual needs. Yang Jinlong, academician of the CAS Member and president of Tongji University, introduced that China has established an ecological alliance of intelligent scientists. At present, more than 40 alliance units have built scientific research intelligent platforms, and more than 50 units have actively prepared to build scientific research intelligent platforms. During this process, issues such as fragmented architecture, data barriers, and incompatible interfaces have become prominent in the research intelligent platforms. The biggest risk facing the current development of intelligent scientific research is not insufficient platforms, but the increasing number of platforms that are becoming increasingly incompatible with each other, "said Yang Jinlong, which will bring serious consequences. One issue is that the data cannot be aligned. Inconsistent data structures, metadata descriptions, naming conventions, and quality control standards across different platforms make it difficult for data to flow and aggregate across platforms. Secondly, the model is difficult to reuse. Due to the lack of a unified framework for model definition, calibration, validation, and deployment, research models often remain within local projects and are difficult to accumulate as national intelligent research assets. Thirdly, it is difficult for devices to collaborate. Due to the closed interfaces between different manufacturers, workstations, and automation systems, it is difficult to form a unified scheduling network. Fourthly, the platform is difficult to expand. Due to the lack of unified security rules, service standards, and capability evaluation mechanisms, it is difficult for platforms to connect and form a trustworthy open ecosystem. The deeper problem is that if this fragmented state continues, even if China has a large number of platforms and demonstration scenarios, it may fall into the dilemma of 'quantity prosperity and system fragility'. Locally advanced intelligent laboratories may eventually solidify into 'digital chimneys' rather than forming a national research infrastructure network that is interconnected, capable, and data sharing. ”Yang Jinlong said. It is necessary to establish a unified "code of conduct" to establish standards for scientific research intelligent platforms, just like teaching different "dialects" of scientific research platforms to speak "Mandarin" and establishing a unified "code of conduct" for them. This allows scientists to directly use data, models, etc. from different platforms without having to spend a lot of time on data cleaning, model adaptation, and other tasks. In the view of Wang Kun, Secretary of the Party Committee and President of the China Institute of Standardization, only with unified standards can AI truly become the engine of scientific research, allowing innovation to "soar". Standards indicate the direction of evolution for emerging technologies, which helps to avoid resource waste caused by 'multiple investments and repeated wheel building'. At the same time, it can consolidate industry consensus and help innovative entities form a joint force when the technological roadmap has not yet converged, promoting collaborative research and development within the consensus framework, "said Wang Kun. The standard is the "protective net" that ensures the security of intelligent scientific research. In terms of physical security, by establishing relevant operating standards, it is possible to prevent robots from misoperating in an unmanned state, laying a solid first line of defense for industrial scientific research; In terms of data security, defining scientific data classification, access permissions, and flow rules can prevent core scientific research data from being stolen or abused in automated interactions; In terms of ethical safety, setting a scientific ethical red line for the "black box" operation of models can ensure that intelligence releases value within a controllable range. The standard is an "overpass" that connects intelligent research islands. It enables the aggregation, sharing, reuse, and mutual recognition of laboratory data from different sources and modalities on a unified platform, breaking down data silos. By developing interface specifications, communication protocols, and interoperability requirements for autonomous experimental systems, a "plug and play, freely combinable" device collaborative ecosystem can be achieved; By building interconnected standards across laboratories and institutions, domestic research platforms and overseas partners can collaborate on research under unified rules, forming an intelligent research network that is physically dispersed and logically unified. Standards are still the "engine" driving the large-scale development of the intelligent scientific research industry. In Wang Kun's view, a unified standard can reduce the manufacturing cost of hardware equipment, as well as the cycle and cost from demand docking to implementation, providing users with a reliable procurement basis and promoting intelligent scientific research from "laboratory bonsai" to "industrial landscape". Standards are the 'golden key' to mastering the discourse power of the global value chain. Standards are not only technical documents, but also the 'operating system' of the industrial ecosystem. International standards that dominate key areas can attract global developers to innovate in our standard system, enabling China to transition from a 'participant' to a 'definer', "said Wang Kun. Standards are not end of pipe ancillary work, but the fundamental system for the scale, networking, and ecological evolution of intelligent scientific research. Standardization is not a constraint on innovation, but an amplification of innovation capability. It is a key mechanism for transforming local explorations into systematic capabilities and laboratory results into national competitiveness. ”Yang Jinlong said. In Yang Jinlong's view, the most urgent task at present is not to continue building new isolated platforms, but to establish a national level scientific research intelligent platform standard system as soon as possible. We need to strengthen the top-level design of national standards, accelerate the revision of basic, data, security, service and other national standards, and form a backbone standard system as soon as possible. At the same time, we need to promote the implementation of standards in demonstration projects and real scenarios, "said Yang Jinlong. Wang Kun believes that in the face of the fast pace of "AI models iterating every few months and robot hardware upgrading every six months", the traditional standard setting rhythm of "project initiation drafting soliciting opinions review and release" that takes 18-24 months is no longer suitable. In this regard, forward-looking and guiding pre standards should be released in advance when the technology is not fully mature and the industrial ecosystem is not yet finalized. Pre standard is not only a technical document, but also a process of industry consensus building. It can guide the direction of emerging industries, reduce trial and error costs, provide a channel for early recognition and consensus building for original innovation, and form a positive cycle of 'innovation standardization wider innovation', "said Wang Kun. In addition, the standardization of scientific research heavily relies on original innovation, thus requiring the comprehensive involvement of national strategic scientific and technological forces and leading technology enterprises. To this end, Wang Kun suggests establishing a national standardization working group for scientific research intelligent platforms, gathering core scientific research forces such as national laboratories, top universities, and leading enterprises to lead the revision of national standards. Building a talent pool is equally important. Wang Kun said that intelligent scientific research is an emerging field, and the technological roadmap has not yet converged. Scientific paradigms are being reshaped, so standardization is not only the business of the industry, but also closely related to cutting-edge basic research, because the most knowledgeable talents are the most qualified to define rules. To strengthen the construction of intelligent scientific research standard composite leading talents, Wang Kun suggests establishing a dual track evaluation mechanism of "standard+academic", and incorporating the contribution of international standards into the evaluation of academic influence; At the same time, provide top scientists with "low threshold, high return" participation channels and mechanisms, and encourage them to actively participate in standard setting work. The formulation and implementation of standards cannot be separated from a good ecology. We should participate in global governance with a more open and constructive attitude, build an open, inclusive, and agile international intelligent scientific research standardization alliance, explore new paradigms of international cooperation, jointly build an inclusive and inclusive intelligent scientific research rule ecology, promote global scientific discovery, and accelerate the transformation of scientific research paradigms, "said Wang Kun. The major leap in scientific development has never been the victory of a single technology, but the result of the co evolution of institutions, facilities, knowledge, and organizational methods. We should not only be followers of platform construction, but also the makers of the rule system, the shapers of the ecological pattern, and the pioneers of the future scientific era. ”Yang Jinlong said, "Only by building a foundation with standards can we achieve synergy and symbiosis; only through synergy and symbiosis can we win the next era of science