国家知识产权局信息显示，联想（北京）有限公司申请一项名为"频率调整方法及电子设备"的专利，公 开号CN121029375A，申请日期为2025年7月。 本文源自：市场资讯 作者：情报员 声明：市场有风险，投资需谨慎。本文为AI基于第三方数据生成，仅供参考，不构成个人投资建议。 专利摘要显示，本公开提供了一种频率调整方法及电子设备，所述方法包括：获得针对电子设备运行应 用的核心调用指令；核心调用指令用于表征电子设备运行应用需要调用的处理器核心；其中，处理器核 心包括第一核心和第二核心；第一核心的最大工作频率大于第二核心的最大工作频率；响应于核心调用 指令，确定目标核心；目标核心为第一核心或第二核心的任意一个类型；根据目标核心的工作频率，调 整环形总线的工作频率以执行应用。 天眼查资料显示，联想（北京）有限公司，成立于1992年，位于北京市，是一家以从事计算机、通信和 其他电子设备制造业为主的企业。企业注册资本565000万港元。通过天眼查大数据分析，联想（北京） 有限公司共对外投资了107家企业，参与招投标项目5000次，财产线索方面有商标信息1751条，专利信 息5000条，此外企业还拥有行政许可238个。 ...

本文源自：市场资讯 作者：情报员 国家知识产权局信息显示，联想（北京）有限公司申请一项名为"一种智能检测方法及装置"的专利，公 开号CN121029590A，申请日期为2025年8月。专利摘要显示，本申请公开了一种智能检测法及装置， 其中，所述方法包括：接收第一显示区域中用户输入的业务执行指令，智能解析所述业务执行指令，得 到智能解析结果；基于所述智能解析结果，确定可用于运行所述业务执行指令的第一执行代码，利用第 二显示区域展示所述第一执行代码，其中，所述第一执行代码是经智能解析之后，调用预设代码库中与 所述业务执行指令匹配的目标代码生成的，所述第一执行代码用于生成检测工具以执行所述业务执行指 令；利用所述第二显示区域展示所述检测工具执行智能检测的过程。 天眼查资料显示，联想（北京）有限公司，成立于1992年，位于北京市，是一家以从事计算机、通信和 其他电子设备制造业为主的企业。企业注册资本565000万港元。通过天眼查大数据分析，联想（北京） 有限公司共对外投资了107家企业，参与招投标项目5000次，财产线索方面有商标信息1751条，专利信 息5000条，此外企业还拥有行政许可238个。 声明：市场有风险 ...

国家知识产权局信息显示，联想（北京）有限公司取得一项名为"摘要生成方法和装置"的专利，授权公 告号CN114661893B，申请日期为2022年3月。 声明：市场有风险，投资需谨慎。本文为AI基于第三方数据生成，仅供参考，不构成个人投资建议。 本文源自：市场资讯 天眼查资料显示，联想（北京）有限公司，成立于1992年，位于北京市，是一家以从事计算机、通信和 其他电子设备制造业为主的企业。企业注册资本565000万港元。通过天眼查大数据分析，联想（北京） 有限公司共对外投资了107家企业，参与招投标项目5000次，财产线索方面有商标信息1751条，专利信 息5000条，此外企业还拥有行政许可238个。 作者：情报员 ...

Core Points - A significant fire occurred in Hong Kong's Tai Po district, resulting in major casualties and prompting over 100 companies and foundations to donate for emergency relief and community recovery efforts, with total donations exceeding HKD 1.2 billion [2][4]. Donation Summary - Major companies such as Yuexiu Group donated HKD 10 million, while China Overseas and China State Construction contributed HKD 20 million [3]. - Tencent donated HKD 30 million, and Alibaba made an initial donation of HKD 20 million [3]. - Other notable contributions include HKD 30 million from the Li Ka Shing Foundation and HKD 12 million from the Chaozhou Association [4]. - The total amount of donations has surpassed HKD 1.2 billion as of the latest reports [4].

国家知识产权局信息显示，联想（北京）有限公司取得一项名为"一种信息确定方法、电子设备和计算 机可读存储介质"的专利，授权公告号CN114596134B，申请日期为2022年2月。 作者：情报员 天眼查资料显示，联想（北京）有限公司，成立于1992年，位于北京市，是一家以从事计算机、通信和 其他电子设备制造业为主的企业。企业注册资本565000万港元。通过天眼查大数据分析，联想（北京） 有限公司共对外投资了107家企业，参与招投标项目5000次，财产线索方面有商标信息1751条，专利信 息5000条，此外企业还拥有行政许可238个。 声明：市场有风险，投资需谨慎。本文为AI基于第三方数据生成，仅供参考，不构成个人投资建议。 本文源自：市场资讯 ...

本文源自：市场资讯 作者：情报员 天眼查资料显示，联想（北京）有限公司，成立于1992年，位于北京市，是一家以从事计算机、通信和 其他电子设备制造业为主的企业。企业注册资本565000万港元。通过天眼查大数据分析，联想（北京） 有限公司共对外投资了107家企业，参与招投标项目5000次，财产线索方面有商标信息1751条，专利信 息5000条，此外企业还拥有行政许可238个。 声明：市场有风险，投资需谨慎。本文为AI基于第三方数据生成，仅供参考，不构成个人投资建议。 国家知识产权局信息显示，联想（北京）有限公司申请一项名为"控制方法、装置及电子设备"的专利， 公开号CN121028586A，申请日期为2025年8月。专利摘要显示，本公开提供了一种控制方法、装置及 电子设备，涉及智能家居技术领域。其中，控制方法包括：响应于目标对象出现于目标场景，获取所述 目标对象的身份信息和动作信息；将所述目标对象的身份信息和动作信息输入至识别模型，以确定所述 目标对象处于所述目标场景下的目标行为意图；确定所述目标行为意图对应的至少一个目标控制指令； 所述至少一个目标控制指令匹配于所述目标对象的身份信息；输出所述至少一个目标控制 ...

Core Viewpoint - The integration of hardware, software, and data is driving the emergence of a new generation of technology companies, with firms that successfully merge personal and enterprise solutions becoming core assets in the AI wave [6][8]. Financial Performance - Lenovo Group reported a 15% year-on-year revenue growth in Q2 of FY2026, reaching 146.4 billion RMB, significantly exceeding market expectations. Adjusted net profit grew by 25% to 3.66 billion RMB, outpacing revenue growth [6][7]. - The IDG smart device business group achieved revenue of 108.1 billion RMB, a 12% increase, while the ISG infrastructure solutions group saw revenue rise by 24% to approximately 29.3 billion RMB, driven by strong AI infrastructure demand [7][15]. AI Infrastructure Investment - Global investment in AI infrastructure is unprecedented, with estimates ranging from 400 to 600 billion USD in 2023, surpassing previous industrial revolutions [9]. - The AI narrative has significantly impacted capital markets, with AI data center ecosystem-related stocks accounting for 75% of S&P 500 returns since the launch of ChatGPT in November 2022 [10]. Market Position and Strategy - Lenovo is one of the few Chinese tech companies fully covering personal and enterprise terminals, software, and hardware within the AI ecosystem [8]. - The company is leveraging AI infrastructure investments to enhance its "one body, multiple ends" strategy, creating highly intelligent and personalized enterprise and personal solutions [8][19]. AI Product Development - Lenovo's AI PC market share reached 31.1%, maintaining its position as the global leader, with AI PC revenue contributing significantly to overall growth [18][19]. - The Tianxi AI system, now at version 3.5, is set to release version 4.0, enhancing user experience through a personal AI twin concept [20][24]. Competitive Advantage - Lenovo's B2B business model provides a strong risk mitigation strategy, particularly in the face of supply chain fluctuations affecting competitors like Dell and HP [29]. - The company's unique position in both B2B and B2C markets allows it to benefit from the ongoing AI wave, with a dual focus on enterprise infrastructure and consumer AI products [26][35].

Core Insights - The global DRAM market is experiencing a supply-demand imbalance, leading to rapid price increases for storage chips, particularly driven by the surge in AI infrastructure demand [1][2][3] Group 1: Market Dynamics - The price of 512GB storage has increased by nearly 500 yuan compared to the previous month, indicating significant price inflation in the storage chip market [2] - Counterpoint Research reports that memory prices have risen by 50% this year, with an expected additional 50% increase by Q2 2026 due to critical chip shortages [4][5] - Major PC manufacturers like Dell and HP are issuing warnings about potential price hikes for their products due to rising storage chip costs and supply constraints [2][3] Group 2: Company Responses - Lenovo's chairman predicts that the shortage and price increases of components, including storage, will persist throughout 2026, prompting the company to secure optimal contracts with suppliers [3] - Xiaomi has proactively signed supply agreements for 2026 to mitigate the impact of rising storage costs and may consider price adjustments and product upgrades to alleviate cost pressures [3] - SK Hynix and Micron are adjusting their production strategies in response to the increased demand for advanced memory, with expectations of significant production growth in the coming years [5][6] Group 3: Future Outlook - The semiconductor industry is entering what analysts describe as a "super cycle," with manufacturers aggressively stockpiling memory chips amid soaring demand [6] - The shift in demand from traditional LPDDR4 to advanced memory types like HBM is causing market disruptions, with significant implications for supply chains [4][5] - Analysts predict that the price of DDR5 memory modules could double by the end of 2026 due to the ongoing supply constraints and heightened demand from major players like NVIDIA [5][6]

ICT行业首座生态级零碳工厂落地90个减碳场景 本报讯 （记者贾丽）11月28日，在2025世界智能制造大会举办期间，国际智能制造联盟（ICIM）正式 发布了"2025世界智能制造十大科技进展"。联想集团有限公司（以下简称"联想"）创新产业园（天津） （以下简称"联想天津工厂"）成功入选该榜单。 主办方评价认为，联想天津工厂整体设计贯彻绿色零碳、智能制造两大定位，是业内高水准的零碳智造 工厂。其中，工厂自身减排及绿电绿能占工厂运营总碳排放量90%以上，此外深度融合高自动化产线和 全领域智能化场景应用，自动化率达到行业最高的60%。 世界智能制造大会由江苏省人民政府与国际智能制造联盟共同主办，是汇聚全球智能制造领先企业、权 威机构与前沿专家的顶级交流平台。"世界与中国智能制造十大科技进展"作为大会的核心发布内容，聚 焦智能制造技术前沿性与创新性成果，旨在表彰对推动产业升级、提升制造效能、促进绿色发展具有实 际价值，推动全球及中国智能制造发展积极贡献力量的创新成果。 此外，工厂还拥有一座高达24米的零碳黑灯智慧化立体库。该立体库综合应用了无人拣选、视觉识别及 势能回收等43个智能场景，实现了仓储占地节省超过70% ...

Core Viewpoint - Lenovo's innovative RNL technology addresses long-standing challenges in load balancing for AI training and inference scenarios, particularly in RoCE networks, as recognized by its acceptance at the IEEE CyberSciTech 2025 conference [1][2]. Group 1: Technology Innovation - The RNL technology incorporates a closed-loop system of "multi-dimensional perception + path load balancing + incremental migration," combining algorithmic innovation with practical value [2]. - The multi-dimensional perception mechanism allows real-time awareness of network topology, AI task network demands, and RoCE link load status, providing a data foundation for dynamic scheduling [2]. - Path load balancing optimization utilizes virtual-physical network mapping and path scoring algorithms to intelligently select optimal data transmission paths, maximizing bandwidth utilization [2]. - Incremental flow migration employs a strategy to avoid instantaneous delays during link traffic adjustments, ensuring business continuity [2]. Group 2: Future Plans - Lenovo plans to extend the RNL technology to high-performance storage and HPC scenarios, incorporating deep learning algorithms to enhance congestion prediction capabilities [2]. - The company aims to validate the comprehensive performance of RNL technology in large AI clusters with thousands to tens of thousands of nodes, continuously driving innovation and iteration in AI network technology [2].