// 一、核心财务表现 // 1. 营收与利润 2. 地区市场表现 3. 全年指引上调 // 二、业务亮点与战略动向 // 1. 广告业务增长强劲 2. 内容与市场策略 3. 汇率与运营效率 季度营收达 110.8 亿美元，同比增长 15.9% ，略高于分析师预期的 110.6 亿美元。 净利润同比激增 45.6% 至 31.25 亿美元，稀释后每股收益（ EPS ）为 7.19 美元，超出市场预期的 7.08 美元。 营业利润率从去年同期的 27.2% 提升至 34.1% ，创历史新高。 自由现金流同比增长 86.9% 至 22.67 亿美元，全年自由现金流指引上调至 80 亿 -85 亿美元。 欧洲、中东及非洲（ EMEA ）： 营收 35.38 亿美元，同比增长 18% （剔除汇率影响后增长 16% ）。 拉美（ LATAM ）： 营收 13.07 亿美元，同比增长 9% （剔除汇率影响后增长 23% ）。 亚太（ APAC ）： 营收 13.05 亿美元，同比增长 24% （剔除汇率影响后增长 23% ），增速领跑全球。 营收预期从 435 亿 -445 亿美元上调至 448 亿 -452 亿美元，按 ...

近日，山东省网信办正式公布生成式人工智能服务备案名录，全省累计完成17款相关服务备案。其中，浪潮科技研发 的"焱宇大模型"顺利通过国家网信部门审核，正式获得国家级备案认证。 焱宇大模型以优质语料为核心支撑，通过数据源管理、语料提质、合成评测等全链路手段，为模型训练输送高质量资 源。其构建的LLMOps体系覆盖从数据管理到应用上线的全流程，支持在线平台快速调用，显著缩短应用交付周期。 在安全方面，模型集成数据分类分级、敏感信息过滤、提示词改写等工具，结合隐私计算与分布式可信训练框架，形 成多层次安全防护体系，可满足高合规场景需求。同时支持行业定制化开发，精准匹配业务需求。 场景落地：覆盖十余行业领域，打造丰富应用场景 基于技术突破，焱宇大模型已在基层治理、应急、法治、自然资源、科研、税务、工会、文物、文博、文化等10多个 垂直领域，开发了超百个智能体应用，涵盖辅助办公、话务助理、知识库、报告审查、智能图谱、智能运维、问数等 近20种实用服务场景，打造出20多个典型应用案例，实现了场景级大模型的定制化可视化构建与高效交付。 浪潮科技始终以技术创新驱动产业发展，此前焱宇大模型已成功获批4项深度学习算法备案。此次再次 ...

Group 1 - Meta has hired two top AI researchers, Mark Lee and Tom Gunter, from Apple to join its "superintelligence lab" team, following the recruitment of Ruoming Pang [1] - The hiring spree reflects the tech industry's competition for AI talent, with Meta's CEO Mark Zuckerberg prioritizing AI and investing heavily in recruitment and data center development to compete with firms like OpenAI and Google [1][2] - Gunter and Lee's recruitment highlights ongoing turmoil within Apple's foundational model team, which is responsible for developing generative AI technologies [2] Group 2 - Apple is simultaneously developing versions of its Siri voice assistant that utilize both proprietary and third-party technologies, with a decision on the underlying software needed before the new assistant's launch next spring [3] - Meta's attractive compensation packages are significantly higher than those offered by Apple, prompting Apple to increase salaries for some engineers in an effort to retain talent [3] - Zuckerberg announced that Meta plans to invest "hundreds of billions" in computing to build superintelligence, aiming to create a top-tier team concentrated in California for efficient collaboration [3]

Group 1 - Huang Renxun, CEO of Nvidia, predicts that the next wave of artificial intelligence will be Physic AI, which uses fundamental principles to replace human coding and algorithm description for result prediction [1] - The shift from current text/image models to industrial simulation and biomedicine indicates a potential transformation in investment logic within the industry [1] - If Physic AI achieves autonomous derivation of physical laws, it could disrupt traditional simulation tools and advance industries like autonomous driving and material research [1] Group 2 - The launch of the domestically produced "Pinyuan AI Integrated Machine" series in Shenzhen marks a significant breakthrough in China's AI hardware, achieving full domestic control over key software and hardware technologies [2] - The Pinyuan AI Integrated Machine features 16 domestically produced Jiangyuan D10 AI inference acceleration cards, enhancing model inference efficiency by 300% in text generation and image recognition scenarios [2] - This development is expected to strengthen national technology security and reduce reliance on foreign technologies, while promoting AI applications in enterprises and government [2] Group 3 - The recent registration of the "Fengyu" large model by SF Technology and other AI services indicates a speeding up of industry standardization, with a total of 439 generative AI services registered as of June 30, 2025 [3] - The entry of traditional giants like SF into the generative AI space signifies the expansion of large models from the internet into logistics and telecommunications sectors [3] - Companies are now required to demonstrate that their technologies can effectively reduce costs and improve efficiency, moving beyond mere concepts [3]

打造全过程思政教育评估生态。科学化、一体化的教学评价体系是大中小学思政课一体化建设落地落实 的重要支撑与质量保障。当前，大中小学思政课一体化评价体系仍存在碎片化、单一化问题。在评价导 向层面，以考试成绩为主的评价仍占主导，容易导致思政课的价值塑造与能力培养的育人目标被简化为 分数表征。在评价维度层面，价值观与情感态度等在一定程度上缺乏有效的量化工具，传统纸笔测试难 以捕捉学生思想成长的动态轨迹。在学段衔接层面，评价标准相对缺乏纵向连贯性，无法完整刻画学生 思政素养的进阶过程，弱化了循序渐进、螺旋上升的一体化育人效果。构建全过程思政教育评估生态， 可依托生成式人工智能技术，打造"数据驱动—智能诊断—持续改进"的智慧评价系统。在技术支撑层 面，通过多模态学习分析引擎，实时采集课堂语音微表情、在线思政学习轨迹等数据，利用生成式人工 智能构建情感态度计算模型，将价值观形成过程转化为可视化成长曲线。在算法创新层面，开发思政知 识掌握度动态评估系统，基于大语言模型自动生成个性化诊断报告，构建跨学段评价标准转换器，实现 小学思政学习行为观察记录、中学项目化评价与大学学术性评估的智能衔接。在系统集成层面，创建全 学段周期思政 ...

Core Viewpoint - The third China International Supply Chain Promotion Expo opened in Beijing, highlighting NVIDIA's H20 chip's return to the Chinese market and the ongoing rapid development of AI technology [1][2]. Group 1: AI Development - NVIDIA's CEO Jensen Huang emphasized that AI is evolving rapidly, with significant advancements occurring approximately every four to five years [4]. - Huang noted that NVIDIA's computing power has increased by 100,000 times over the past decade, enabling more effective machine learning [5]. - The majority of AI-related research is open-source, with a notable number of papers published by Chinese researchers, which account for the highest global share [5]. Group 2: AI's Value - Huang believes that AI's impact on science will be greater than its service to humanity, as it can solve complex algorithms in various fields such as weather and ocean physics [5]. - He expressed confidence that AI can help advance scientific understanding and simulate natural laws [5]. Group 3: AI's Future - Huang argued against the notion that learning AI technology is unnecessary, stating that foundational knowledge is crucial for problem-solving [7]. - He encouraged the younger generation to engage with AI, as it enhances capabilities and promotes equality across different demographics [7][8]. - Huang described AI as a lifelong companion that can assist individuals throughout their lives, recording personal journeys and providing guidance [8].

Group 1 - Guangdong has added 6 newly registered generative artificial intelligence services [1]

Group 1 - Cohere, an AI startup valued at $5.5 billion, plans to establish an Asia-Pacific hub in Seoul, South Korea, to expand its operations in the region [2] - The company has appointed Andrew Chang as Vice President for the Asia-Pacific region to oversee the Seoul office and drive regional expansion [2] - Cohere has raised a total of $970 million in funding from investors including Nvidia, AMD, Oracle, Salesforce, Cisco, and others, with the latest funding round being a $500 million Series D completed in July 2024 [2] Group 2 - Cohere focuses on developing large language models tailored for enterprises, particularly in regulated industries that handle sensitive data, such as finance, healthcare, manufacturing, energy, and government [5] - The company collaborates with LG CNS to develop customized AI models with advanced Korean language processing capabilities, integrating with Cohere's AI agent, North [5][6] - A significant project includes the development of a large language model with 111 billion parameters that supports 23 languages, including Korean, Japanese, and Chinese, which can operate within enterprise data centers [5] Group 3 - The decision to open an office in South Korea aligns with the new president's commitment to invest 100 trillion won (approximately $72 billion) in AI infrastructure and technology development [6]

Core Insights - The National Internet Information Office has released information on generative artificial intelligence services registered from April to June 2025, indicating a growing trend in the sector [1] - Shenzhen has seen the addition of 8 new generative AI services, including models from SF Technology Co., Ltd. and CaiXun Technology Co., Ltd., both of which are publicly listed companies in A-shares [1] - As of June 30, 2025, a total of 439 generative AI services have completed registration, with 233 applications or functions officially recorded [1] Company Insights - SF Technology Co., Ltd. has launched the Fengyu large model, contributing to the expansion of generative AI services in Shenzhen [1] - CaiXun Technology Co., Ltd. has introduced the Ruichi large model, further enhancing the competitive landscape of generative AI in the region [1] - Both CaiXun Technology (300634) and SF Holdings (002352) are publicly traded companies, indicating potential investment opportunities in the generative AI sector [1] Industry Insights - The generative AI sector is experiencing rapid growth, with a significant number of services being registered and recognized by regulatory bodies [1] - The cumulative registration of 439 generative AI services reflects the increasing adoption and integration of AI technologies across various applications [1] - The registration of 233 applications or functions highlights the diverse functionalities being developed within the generative AI space [1]

Core Viewpoint - The discussion highlights the transformative impact of artificial intelligence (AI) on society, scientific discovery, and the importance of foundational knowledge for the younger generation in adapting to the AI era [1][5][7]. Group 1: AI Development Trends - The next trend in AI development is its penetration into the physical world, transitioning from "perceptual AI" to "generative AI" and now to "reasoning AI," which can understand and generate information [2][3]. - The upcoming wave is "physical AI," which will be applied in robotics and other physical machines, enhancing human capabilities [3]. Group 2: China's Role in AI - China plays a significant role in AI development, with the highest number of research papers published globally. The country excels in open-source projects, which have a global impact [4]. - Open-source models like DeepSeek and Tongyi Qianwen are among the top in the world, benefiting various sectors such as healthcare and finance [4]. Group 3: AI's Impact on Scientific Discovery - AI is poised to revolutionize scientific discovery by enabling a deeper understanding of biological processes, which could lead to advancements in drug design and longevity [5]. - The ability to understand the structure and significance of biological entities through AI presents substantial opportunities [5]. Group 4: Future of Chip Technology - The future of chip technology involves the development of three-dimensional transistors and advanced packaging techniques, with significant innovations expected in silicon photonics [5]. - The transition from single chips to stacked and multi-chip designs is a key focus area for the next two decades [5]. Group 5: Advice for the Younger Generation - Young individuals are encouraged to master foundational skills such as mathematics, reasoning, logic, and programming to effectively interact with AI [6][7]. - Critical thinking is essential for evaluating AI-generated answers, and understanding first principles is crucial for problem-solving [7].