Core Insights - The research team from the Victoria Museum in Australia has created a global distribution and evolutionary relationship map of the sea snake tail, revealing that marine life connections in the deep sea are more intricate than previously thought [1][2] - The study, published in the latest issue of Nature, indicates that the sea snake tail, an ancient polychaete that has existed for 480 million years, can be found from shallow waters to depths exceeding 3,500 meters [1] - The analysis of 2,699 specimens from 48 natural history museums, collected during 332 scientific expeditions, has uncovered the migration mysteries of this deep-sea animal [1] Research Findings - Sea snake tails, which lack fins and wings, can migrate across oceans via deep-sea currents, with their larvae's extended survival in cold water being crucial for this "free ride" [1] - The study provides a new perspective on marine evolution, suggesting that the deep sea is not an isolated environment but rather a "biological highway" with extensive connectivity [1] - Notably, temperate deep-sea communities exhibit remarkable global interconnections, such as the close evolutionary ties between species in southern Australian waters and their "distant relatives" in the North Atlantic [1] Environmental Implications - The research highlights that deep-sea ecosystems are not entirely homogeneous; while species are dispersing, environmental changes and geological events continue to shape unique biodiversity patterns [1] - The findings underscore the importance of protecting deep-sea life in the face of threats from deep-sea mining and climate change [1][2]

Group 1 - The National Healthcare Security Administration (NHSA) is promoting the application of artificial intelligence and big data in the healthcare insurance sector, transitioning from traditional methods to intelligent and precise fund supervision [1][2] - The healthcare insurance data encompasses 1.33 billion insured individuals, 50 million employers, 1.14 million hospitals and pharmacies, 17,900 medical supply companies, and 376,000 medical products, supporting an annual revenue and expenditure of approximately 3 trillion yuan and 10 billion medical service transactions [1] - The 2025 National Smart Healthcare Insurance Competition will adopt an open model without specific tracks, focusing on various fields such as healthcare, innovative drug development, financial insurance, and academic research [2] Group 2 - Participants in the competition will have access to real patient data regarding medical treatment, settlement, fund operation, and drug usage, which will enhance the feasibility and practicality of their proposals [2] - The competition marks the first attempt to integrate healthcare insurance data with data from other industries, facilitating interconnectivity and collaboration among healthcare institutions, research institutes, universities, and corporate R&D centers [2] - The Shanghai government will provide a secure and compliant local healthcare insurance data verification environment and computational resources for projects aiming for local implementation [3]

Core Insights - Harvard University researchers have developed a new optical device called "metasurface" that can perform complex quantum operations on a single plane, addressing scalability issues in photon quantum information processing [1][2] - The metasurface integrates multiple traditional optical component functions, potentially revolutionizing quantum computing and quantum communication at room temperature [1][2] Group 1: Metasurface Technology - The metasurface is a nanometer-thick optical element with micro-nano structures smaller than the wavelength of light, allowing precise control over light's phase and polarization [2] - This technology condenses complex quantum optical systems into a miniaturized platform, significantly enhancing system stability and interference resistance [2] Group 2: Design and Production - The research team utilized graph theory to model multi-photon interference paths, translating these abstract graphs into actual nanoscale structures on the metasurface [2] - This method closely links metasurface design with quantum optical states, providing a systematic approach for constructing specific quantum state devices [2] - The integrated design of the device greatly reduces optical loss, which is crucial for maintaining quantum information integrity [2] - The device can be mass-produced using existing semiconductor manufacturing processes, indicating potential for low-cost and replicable production models [2] Group 3: Broader Applications - The potential applications of this technology extend beyond quantum computing, with prospects for advancements in quantum sensing and fundamental research, offering new tools akin to "chip laboratories" [2]

Core Insights - Zhejiang University has launched a new generation of neuromorphic brain-like computer named "Wukong," which is the first in the world to exceed 2 billion neurons based on dedicated neuromorphic chips [1][2] - "Wukong" features over 2 billion spiking neurons and more than 100 billion synapses, closely resembling the scale of a macaque brain, with a typical operating power consumption of approximately 2000 watts [1] - The previous largest neuromorphic brain-like computer was Intel's Hala Point system, which had a neuron scale of 1.15 billion [1] Group 1 - "Wukong" is equipped with 960 self-developed Darwin 3rd generation brain-like computing chips, organized into 15 blade-type neuromorphic brain-like servers [1] - Each chip supports over 2.35 million spiking neurons and hundreds of millions of synapses, along with a dedicated instruction set for brain-like computing and an online learning mechanism [1][2] Group 2 - The research team has developed the Darwin brain-like operating system alongside "Wukong," which can run intelligent applications such as DeepSeek brain-like models for logical reasoning, content generation, and mathematical problem-solving [2] - "Wukong" offers a new computational paradigm with its large scale, high parallelism, and low power consumption, providing a computational foundation for artificial intelligence development and serving as a simulation tool for neuroscientists [2]

谷歌同时在arXiv预印本平台上传了一篇尚未经同行评审的论文。文中称，该模型在准确性和数据密度 方面均优于同类AI模型，同时能显著降低计算时间和能耗。 谷歌表示，谷歌"地球引擎"平台此前已托管了农业、森林砍伐、天气等主题的独立数据集，AlphaEarth 将这些数据集整合在一起，生成统一产品，便于科学家进行探索。 （文章来源：科技日报） 据英国《自然》网站7月31日消息，谷歌发布了一款"AlphaEarth"人工智能（AI）模型，其如同"虚拟卫 星"，能够整合海量的异构观测数据（包括卫星图像、雷达数据等），追踪地球陆地和浅海区域的变 化。该模型获得了科研人员高度评价，但他们也呼吁谷歌提供更多测试细节，并提醒相关研究人员，仍 需自行验证该工具生成的地图数据。 谷歌称，这款模型可在"任何地点、任何时间"进行地理绘图。卫星获取的只有颜色、云层等单一属性信 息，而AlphaEarth会将这些信息处理成名为"嵌入向量"的数字表示，从而能使研究人员轻松检索出树 种、建筑物、地下水等特征。研究人员可以利用该模型寻找清洁能源项目的最佳选址，研究气候变化对 生态系统的影响，监测森林砍伐等。处理后的数据被封装为一个个边长10米的 ...

Core Insights - The article discusses the emergence of AI Virtual Cells (AIVC) as a revolutionary approach in biological and medical research, leveraging AI to simulate cellular behavior and explore life mechanisms [1][2]. Group 1: AIVC Technology Overview - AIVC utilizes AI to simulate cellular behavior, potentially transforming various fields such as gene regulation and drug development [1]. - A collaborative research team from Stanford University, Genentech, and the Chan-Zuckerberg Initiative is advocating for the global scientific community to adopt AI technology for creating virtual cells [2]. - AIVC can significantly accelerate research processes, allowing for rapid results that previously took weeks to obtain, such as tumor cell responses to drugs [2]. Group 2: Research and Development Trends - A global competition for life digitization is underway, with significant funding flowing into AIVC research from venture capital and organizations like the Chan-Zuckerberg Initiative [4]. - The AI system "STATE," developed by Arc Institute and other institutions, can accurately predict responses of stem cells, cancer cells, and immune cells to various interventions, utilizing a vast dataset of 170 million observations [4][5]. - The construction of virtual cells is seen as a foundational advancement in life sciences, with ongoing projects like the "Alpha Cell" model expected to be released by 2026 [4]. Group 3: Future Implications - AIVC may enable personalized medicine by allowing doctors to simulate treatment plans on patients' digital twins, leading to faster, more economical, and safer healthcare solutions [3]. - The potential for AIVC to replace traditional laboratory experiments with computational simulations could lead to a paradigm shift in biological research, with predictions suggesting that 90% of future research may rely on simulations [2]. Group 4: Challenges and Limitations - Current AIVC models face limitations in predictive generalization and primarily rely on single-cell sequencing data, necessitating the inclusion of diverse data types for improved accuracy [7]. - The lack of interpretability in deep learning models poses challenges for understanding the reasoning behind AI-generated conclusions, which may hinder the translation of research findings into medical applications [7]. - Ethical concerns regarding patient data privacy and the need for new data management paradigms are critical issues that must be addressed as AIVC technology advances [7].

Core Insights - Ore Energy, a Dutch startup, has developed an iron-air battery that can sustainably store energy for over 100 hours, marking it as the first iron-air battery to be successfully integrated into the grid at Delft University of Technology in the Netherlands [1] - This technological breakthrough offers a new pathway for renewable energy to replace fossil fuels and is expected to significantly enhance the stability of power systems [1] Group 1: Technology and Innovation - The iron-air battery operates by utilizing the rusting and derusting processes to store and release energy, where electrical energy reduces iron oxide (rust) to metallic iron for energy storage, and the metallic iron reacts with oxygen in the air to regenerate rust, thus releasing stored energy [1] - Compared to current grid batteries, primarily lithium iron phosphate batteries, which typically provide power for only 4-6 hours and are costly, the iron-air battery demonstrates significant advantages with its over 100-hour energy storage capability and the use of inexpensive, readily available materials [1] Group 2: Market Potential and Deployment - Iron is the most abundantly mined metal on Earth, and air is an inexhaustible free resource, making the iron-air battery a cost-effective solution by combining the two most economical elements found in nature [1] - The battery employs a water-based electrolyte, which not only reduces costs but also significantly lowers the risk of fire [1] - Iron-air batteries are housed in standard 12-meter containers, with each container capable of storing several megawatt-hours of electricity, indicating a scalable deployment model [2] - Form Energy, a company based in Massachusetts, USA, is also advancing similar projects, planning to deploy this technology in New England and the Midwest [2]

Core Insights - The research team at Kunming University of Science and Technology has made significant breakthroughs in the intersection of "Artificial Intelligence + Materials" by proposing a "Continuous Transfer" machine learning framework, addressing the technical bottleneck of multi-performance prediction of materials with small datasets [1][2] - The framework allows for the efficient development of new functional materials, demonstrating the universality of transfer learning in optimizing multiple material properties [2] Group 1: Research Achievements - The team successfully constructed a "Continuous Transfer" learning strategy that first trains a high-precision base model using extensive formation energy data, followed by sequential predictions of key material properties such as stability, bandgap, and bulk modulus [1] - In a shear modulus prediction task with only 51 data points, the team utilized a bulk modulus model as a "stepping stone" for secondary transfer, significantly enhancing prediction reliability in small datasets [1] Group 2: Material Discovery - Using the framework, the research team rapidly screened over 18,000 candidate materials, identifying 54 inorganic double perovskite coating materials with high stability and excellent ductility [2] - Among these, cesium copper hexafluoroiridate exhibited outstanding performance, with a bandgap suitable for photovoltaic applications and a high ductility indicated by the ratio of shear modulus to bulk modulus [2] Group 3: Implications for the Industry - This research not only provides a candidate material library for fields such as perovskite solar cells and photocatalysis but also offers a scalable computational tool to address the challenges of data scarcity in material development [2] - The advancements in material informatics signify a crucial step in solving the "few data, many tasks" dilemma in material research, providing an efficient computational paradigm for multi-performance optimization [2]

Core Insights - The 27th Annual Conference of the China Association for Science and Technology (CAST) was held in Beijing from July 1 to 31, focusing on "Tracing Technological Frontiers to Support Innovative Development" [1] - The conference attracted over 7,000 participants, including more than 110 academicians, with 57% of attendees being young scientists under 40 years old [1] - A total of over 990 high-level academic reports were presented during the conference [1] Group 1 - One highlight of the conference was the deep involvement and leadership of young scientists in frontier discussions [2] - The conference fostered an atmosphere of equal communication, allowing young scholars to directly question academicians and experts, which is beneficial for breaking cognitive biases and enhancing problem understanding [4] - The design of forums encouraged embracing uncertainty in research and promoted non-consensus viewpoints, creating a more inclusive and open academic environment [4] Group 2 - Participants engaged in discussions on cutting-edge topics such as "Sim2Real challenges" and "multimodal perception fusion" in the "Embodied Intelligent Robots" forum, inspiring new research directions [3] - The "Key Technologies for Commercialization of Controlled Nuclear Fusion" forum attracted diverse participants from academia, industry, and technology sectors, facilitating in-depth discussions on uncertain topics related to nuclear fusion [4] - The conference emphasized the importance of fostering divergent thinking and academic innovation through collaborative discussions among participants of varying expertise and age [4]

Group 1 - The core viewpoint of the article highlights the successful launch of mass production at the largest offshore wind power industrial base in northern China, established by Goldwind Technology in Qinhuangdao [1] - The project was completed in just 10 months under a "land immediately construction" model, showcasing the impressive "Qinhuangdao speed" [1] - The assembly plant is equipped with advanced intelligent systems, including a 500-ton crane and AI bolt detection, significantly enhancing production efficiency and quality [5] Group 2 - The first phase of the Goldwind offshore wind power base has an annual production capacity of 2 GW, capable of producing 100-150 sets of 14 to 20 MW large units [5] - The base is strategically located to serve a 500-kilometer radius, covering the Bohai Sea, northern Yellow Sea, and Northeast regions [5] - Once fully completed, the base will become the largest manufacturing and export hub for offshore wind power equipment in northern China, marking a milestone for high-end equipment manufacturing in Hebei's renewable energy sector [5]