Group 1 - The "Xiaomiao" industrial model, developed by the Smart Building Materials Research Institute funded by China National Building Material Group, has been publicly launched, focusing on the cement sector as a testing ground [1] - The model integrates three core technologies: the fusion of time-series data with industrial mechanisms, multi-modal scenario collaboration, and decision-making fault tolerance, achieving over 1% reduction in cement batching costs [1] - After over two years of application, the model has established a mature engineering delivery capability, successfully implemented in nearly 100 cement enterprises, with data governance cycles reduced to as short as 14 days and model deployment within 7 days [1] Group 2 - China National Building Material Group's chairman believes AI will act as a "super accelerator" for new material research, significantly shortening development cycles and reducing trial-and-error costs [2] - The group is currently promoting AI's integration into strategic emerging industries for new materials, having built 231 scenario models covering the entire chain from core manufacturing to R&D and supply chain management [2] - In 2024, the State-owned Assets Supervision and Administration Commission will launch the "AI+" initiative for central enterprises, with several enterprises releasing industrial models, including China National Petroleum and State Grid [2]

放眼整个发电行业，拥抱人工智能早已是共识。和国家能源集团并称为"五大"的其它发电央企——中国 华能、中国华电、国家电投、大唐集团，也都在积极推进AI应用。大家普遍采用了像DeepSeek这样先 进的国产大模型作为技术基础，并在本地安全部署。当前的应用主要集中在利用AI提高办公效率（比 如智能处理公文、撰写报告、整理会议纪要）、辅助设备维护（预测设备可能出现的故障）以及构建企 业知识库等方面。这些应用都是非常有价值的尝试，显著提升了工作效率和管理水平。 然而，国家能源集团的"擎源"大模型，在深度和广度上迈出了更关键的一步。如果说其他集团目前主要 是在利用AI"优化工具"和"辅助管理"，那么国家能源集团则是利用"擎源"这个强大的"行业大脑"，尝试 对发电的核心业务流程——从电力市场交易博弈、到多能源协同生产调度、再到设备预测性维护和安全 风险管控——进行一场全链条的智能化重构和决策升级。它不仅仅是一个好用的工具，更在努力成为驱 动整个发电系统更智能、更经济、更安全运行的"中枢神经系统"。 未来已来，AI在能源领域的应用前景无比广阔。"擎源"大模型只是一个开始。国家能源集团计划在今年 年底前，将大模型的应用扩展到其 ...

Core Viewpoint - The launch of the "Qingyuan" power generation model, the first trillion-level model in China's power generation industry, aims to support safe, efficient, green, and intelligent operations in the energy sector [1] Group 1: Model Development and Features - The "Qingyuan" model integrates multi-dimensional data such as operational monitoring, equipment status, and meteorological conditions, boasting a parameter scale of trillions [1] - The model is a benchmark achievement for promoting the intelligent transformation of the energy industry and is expected to lead the sector towards digitalization [2] - Over 700TB of industry data was collected, resulting in a high-quality dataset of 450GB, covering various data types, which was annotated by 380 industry experts [3] Group 2: Application Areas - "Qingyuan" has been successfully applied in four major business areas: safety and environmental protection, electricity trading, production scheduling, and equipment maintenance, covering 13 scenarios and deploying 41 intelligent agents [4] - In the safety and environmental protection sector, "Qingyuan" enhances safety management efficiency and supports compliance in hazardous waste management [4] - In electricity trading, "Qingyuan" improves price prediction accuracy by 6.2% compared to traditional methods, leading to a 0.3% reduction in production costs and a 2% increase in profitability for a 600MW generator [5] Group 3: Challenges and Solutions - The power generation industry faces challenges in intelligent upgrades due to its strong specialization and the need for high-quality industry data [2] - There is a cognitive gap between power generation professionals and AI experts, necessitating close collaboration to align technology capabilities with industry needs [2] - To ensure data security, the company implements strict transmission and data management protocols, including one-way data flow and classified data control [6] Group 4: Future Plans - The company plans to advance the "Qingyuan" model through three phases: pilot verification, large-scale promotion, and ecosystem co-construction [7] - The goal is to create an open ecosystem for the power generation industry by unifying technical standards and integrating real-time data with expert knowledge [7]

每经记者｜徐肖逍 每经编辑｜张海妮 ESG发布 我国清洁能源投资规模占全球比重达1/3 6月28日发布的《中国能源生态报告》显示，2024年，我国清洁能源投资规模达到6250亿美元，占全球 比重的1/3。光伏、风电装机容量连续10年位居全球首位，十年间，中国对全球非化石能源消费增量贡 献率超过45%。 点评：这彰显了中国在清洁能源领域的强大实力和引领作用，为全球能源转型贡献了重要力量。 上海、重庆、浙江、福建实现新能源100%消纳 7月2日，全国新能源消纳监测预警中心发布2025年5月全国新能源并网消纳情况：5月，全国光伏发电利 用率为94.2%，风电为93.2%。其中，上海、重庆、浙江、福建实现风电和光伏新能源100%消纳。 点评：这表明我国新能源发展成效显著，消纳能力不断提升，为能源转型和绿色发展奠定了坚实基础， 也为实现"双碳"目标提供了有力支撑。 我国纺织业碳排放强度持续下降 近日，中核田湾（北京）核电股权投资基金合伙企业（有限合伙）成立，执行事务合伙人为中核产业基 金管理有限公司和广州金宏资产管理有限公司，出资额15.01亿元。合伙人信息显示，该基金由中国人 寿、中国核电等共同出资。 点评：15.0 ...

本报北京电(记者廖睿灵)记者从国家能源集团获悉，模型参数达千亿级别的"擎源"发电大模型日前正式 发布，这是全球首个千亿级发电行业大模型，融合了运行监测、设备状态、气象环境等多方面数据。 比如，在电力交易领域，"擎源"可以担任"智慧交易参谋"，精准预测气象变化，预警水情风险，分析市 场形势，为现货交易决策提供支持。一台600兆瓦的发电机组，生产成本可下降0.3%，盈利能力提升 2%。在设备检修领域，"擎源"能够敏锐感知机组状态，智能制定检修策略与派单，推动检修模式从传 统的"被动故障处理"向"预防性状态检修"转变。 国家能源集团电力产业部运行分析处经理王安介绍，"擎源"发电行业大模型的发布，是落实国家数字经 济战略、推动能源行业智能化转型的标杆性成果，安全管控从以人防、物防为主的传统方式，转变为 AI赋能的主动防护体系；运维模式从"事后维修、定期检修"变为"预测性维护、状态检修"；交易决策从 依赖经验和局部信息的传统决策模式，转变为基于海量数据（603138）融合、多模型寻优的智能辅助决 策与自动寻优决策并行模式；调度运行从人工判断、单点优化的调度方式，升级为融合气象水情、市场 供需、设备状态等多维信息的全局协 ...

Core Insights - The State Energy Group has officially launched the "Qingyuan" power generation model, a billion-level model aimed at creating an intelligent decision-making system covering safety, environmental protection, electricity trading, production regulation, and equipment maintenance [1][2] Group 1: Innovations and Features - The "Qingyuan" model achieves three major innovative breakthroughs: 1. It integrates multi-source heterogeneous data such as operational monitoring, equipment status, and meteorological conditions to create a full-stack product matrix of "model-intelligent agent-application," enabling efficient dynamic collaboration across business units [1] 2. It provides a comprehensive AI solution specifically designed for the power system, covering "source-network-load-storage" scenarios, achieving vertical integration of power production through intelligent technology [1] 3. It utilizes a fully domestic technology stack, combining reinforcement learning and multi-modal fusion technology to establish an adaptive training and decision-making framework, creating a closed-loop verification system covering the entire lifecycle of power generation [1] Group 2: Application and Impact - The "Qingyuan" model has been successfully applied in four major business areas: safety and environmental protection, electricity trading, production regulation, and equipment maintenance, covering 13 scenarios and deploying 41 intelligent agents, effectively addressing pain points such as high safety risks, difficult trading decisions, complex multi-energy coordination, and passive equipment operation and maintenance [1] - In the area of equipment maintenance, the model has been applied in 179 pilot power stations, where it has detected 2,633 defects over six months by monitoring real-time data and sensing minute changes, overcoming challenges related to early defect detection and quantification [2] - The State Energy Group plans to advance the "Qingyuan" model through three phases: pilot verification, large-scale promotion, and ecosystem co-construction, gradually opening API interfaces to industry chain partners to build an open ecosystem for the power generation industry [2]

Core Viewpoint - The launch of China's first trillion-level power generation industry model, "Qingyuan," marks a significant advancement in the energy sector, aiming to lead the industry towards intelligence and digitalization [1][2]. Group 1: Model Overview - "Qingyuan" is developed by the State Power Investment Corporation and encompasses 15 business domains and 75 key application scenarios, integrating various aspects of power generation including construction, operation, maintenance, and fuel management [1]. - The model aims to leverage AI and big data to reshape the energy industry, utilizing the vast data assets of the State Power Investment Corporation, which is the largest power generation company globally [1]. Group 2: Innovations and Features - "Qingyuan" introduces three major innovations, including a multi-energy collaborative dynamic optimization engine that integrates operational monitoring, equipment status, and environmental data [2]. - The model features a full-stack product approach, allowing efficient collaboration among different business intelligent agents, and provides intelligent optimization solutions for the entire power generation process [2]. - It establishes a fully autonomous and controllable intelligent decision-making system based on domestic technology, utilizing reinforcement learning and multi-modal fusion methods [2]. Group 3: Application and Impact - Currently, "Qingyuan" has been successfully applied in various business areas such as safety and environmental protection, power trading, and equipment maintenance, covering 13 scenarios and deploying 41 intelligent agents [2]. - The model addresses long-standing challenges in the power generation industry, including high safety risks, complex multi-energy coordination, and passive equipment maintenance, thereby supporting safe, efficient, green, and intelligent power generation [2].

21世纪经济报道新质生产力研究院综合报道 当地时间6月28日，马斯克的Neuralink在一场发布会上公布了公司最新进展和未来规划。目前， Neuralink 已有七名志愿者完成脑机接口植入，他们能够通过脑信号控制玩马里奥赛车、使命召唤等游 戏，甚至用意念操控机械臂写字。Neuralink同时公布了打造"全脑接口"的长远愿景。全脑接口是指在大 脑任意区域实现神经元监听与写入，通过无线高速传输实现生物大脑与机器的深度连接。 【巨头风向标】 马斯克称2028年实现"全脑接口"计划 早上好，新的一天又开始了。在过去的24小时内，科技行业发生了哪些有意思的事情？来跟21tech一起 看看吧。 华为宣布开源盘古7B稠密和72B混合专家模型 6月30日，华为宣布开源盘古70亿参数的稠密模型、盘古Pro MoE 720亿参数的混合专家模型和基于昇腾 的模型推理技术。此举是华为践行昇腾生态战略的又一关键举措。据悉，盘古Pro MoE 72B模型权重、 基础推理代码和基于昇腾的超大规模MoE模型推理代码，已正式上线开源平台。盘古7B相关模型权重 与推理代码将于近期上线开源平台。 特斯拉Model Y完成自己上路、自动交付 6月 ...

实现重要突破 01 刚刚过去的周末 我国清洁能源、科技等多个领域 纷纷传出好消息 全球首艘首航成功 "氨晖号"解锁多项关键核心技术 6月28日 全球首艘纯氨燃料 内燃机动力示范船"氨晖号" 在安徽合肥成功首航 标志着氨燃料 在船舶领域的工业化应用取得重大突破 为航运业节能减排、绿色发展 开辟了一条切实可行的 全新路径 经过两年多的潜心研究 研发团队攻克了 纯氨燃料等离子点火技术 纯氨燃料持续燃烧技术 氨气高效催化裂解产氢等 多项关键核心技术 纯氨动力示范船的成功运行 充分验证了氨氢融合燃料 未来可推广应用到多个领域 将助力我国"双碳"目标的实现 02 我国首个发电行业大模型发布 6月28日 我国首个发电行业 专业大模型"擎源"在京发布 这也是全球首个千亿级发电行业大模型 有效提升了模型的推理能力 为发电行业实现 安全、高效、绿色、智慧发电 提供"超级大脑" 03 我国首条以新能源为主的 模型参数达千亿级 电力外送通道开始送电 6月29日 "宁电入湘"工程 圆满完成168小时试运行 已具备400万千瓦送电能力 开始向湖南送电 将为湖南迎峰度夏提供清洁电力保障 "宁电入湘"工程 线路全长约1616公里 是我国首条 ...

Group 1 - The article discusses a unique event in Detroit where a helicopter dropped a large amount of US dollar bills, which were collected by excited citizens [1] - The money drop was a gesture from the son of a car wash owner who recently passed away from Alzheimer's disease, fulfilling his father's wish to bless the community [1] Group 2 - The article does not contain relevant information regarding companies or industries.