Group 1 - Meta acquired Manus, a company developing AI applications, for several billion dollars, marking its third-largest acquisition since its inception, following WhatsApp and Scale AI [1] - Before the acquisition, Manus was valued at $2 billion during a new financing round [1] - After the acquisition, Manus will operate independently, with its founder, Xiao Hong, appointed as Vice President of Meta [1] Group 2 - WeChat's installation package has grown several hundred times over the past decade due to the increasing complexity and richness of features, but the company assures that it is optimizing the package size [3] - Users with over 40GB of space occupied by WeChat have an average of 70% of that space taken up by chat history [3] Group 3 - Leap Motor announced a partnership with China FAW Group, raising approximately 3.744 billion yuan (about 4.138 billion HKD) through a share issuance to enhance R&D and expand its sales network [11] - The company emphasized that the founding team will maintain control despite the investment from FAW [11] Group 4 - Coupang, a South Korean e-commerce platform, announced a compensation plan worth approximately $1.18 billion for users affected by a data breach involving 33.7 million accounts [19] - Each affected account will receive shopping vouchers totaling 50,000 won [19] Group 5 - Counterpoint predicts consumer spending on generative AI will grow from $225 billion in 2023 to $699 billion by 2030, with a compound annual growth rate (CAGR) of 21% [27] - The growth will be driven by both hardware and software segments, with generative AI smartphones expected to see a 26% CAGR in shipments [27]

今天分享的是：2025中国人力资源数智化发展白皮书 报告共计：135页 《2025中国人力资源数智化发展白皮书》系统呈现了国内人力资源数智化的发展现状、核心趋势与实践成果，核心围绕智慧 决策、生成式AI、数据价值、组织韧性等七大关键词展开。调研显示，超75%的大中型企业已启动HR数智化转型，制造业、 IT/互联网/科技行业为主要引领者，民营企业与万人以上大型企业成为转型主力，数智化成熟度显著提升，已从探索应用迈入 推广落地阶段，核心模块数字化覆盖广泛，但智能化渗透不均，数据治理薄弱、系统整合困难、专业人才短缺是主要挑战。 企业需求已从系统部署转向场景化工具与数智化培训，人工智能技术尤其是大语言模型应用爆发式增长，混合部署成为主流 模式。未来五年，行业将呈现自主进化的HR智能体生态、生成式AI驱动组织进化、具身智能数字化员工普及等五大趋势，推 动人力资源管理从效率提升向价值创造转型。中国移动、贝壳、360集团等领先企业的实践表明，通过构建AI能力基座、深化 全流程场景应用、强化数据治理与安全合规，可实现招聘、培训、绩效等核心环节的智能化升级，推动HR职能从事务处理向 战略赋能跃迁，构建人机协同、数据驱动的人力资 ...

Group 1 - Nvidia acquired Groq for $20 billion through an atypical "asset acquisition + talent recruitment" model, paying nearly 3 times the premium, with about 90% of employees joining Nvidia [1] - Groq employees are expected to receive an average of $4-6 million based on the employee option pool, with vested shares paid in cash and unvested shares converted to Nvidia stock [1] - This "reverse talent acquisition" model is becoming a new norm in the Silicon Valley AI ecosystem, as seen with previous acquisitions of Inflection AI and Character.AI [1] Group 2 - Step-DeepResearch by Jieyue Xingchen uses a 32B parameter model to achieve deep research capabilities comparable to OpenAI's o3-mini and Gemini 2.0 Flash, with a single call cost of less than 0.5 yuan [2] - It employs a three-stage training pipeline (intermediate training, supervised fine-tuning, reinforcement learning) to build data around four core capabilities: planning decomposition, deep search, reflective validation, and report writing [2] - In the ResearchRubrics benchmark test, it scored 61.42, surpassing OpenAI DeepResearch and being on par with Gemini DeepResearch, at only one-tenth the cost of the latter [2] Group 3 - Tencent's Yuanbao has launched a "task" feature, allowing users to assign scheduled tasks to the AI for proactive reminders and information push [3] - Users can customize task content and execution time, marking a shift from passive response to active service by the AI [3] - This feature enhances the AI assistant's role, making it more like a personal assistant that regularly tracks and pushes information of interest to users [3] Group 4 - JD.com has quietly launched an AI-native application "JD AI Purchase," integrating food delivery ordering, product recommendations, and AI fitting, based on JD's self-developed Yansai model [4] - The primary interaction method is dialogue, where users state their needs to receive recommendations, with the homepage "Inspiration Space" covering six major life scenarios [4] - The AI fitting feature allows users to upload photos to generate fitting effect images, and the product comparison function creates tables comparing products across six dimensions, transforming "searching for products" into "stating needs" [4] Group 5 - Domestic GPU company Muxi has released the MACA 3.3.0.X version, showing that 92.94% of 4,490 CUDA projects on GitHub can run directly, achieving near seamless migration [5] - It has completed deep adaptation for PyTorch 2.8, covering all 2,650 core operators, and is compatible with mainstream frameworks like TensorFlow, PaddlePaddle, DeepSpeed, and vLLM [5] - Based on a fully self-developed instruction set and GPU core IP, it achieves "computing power autonomy + ecological compatibility," with linearity stability in thousand-card cluster training above 95% [5] Group 6 - Insta360's research team, in collaboration with several universities, has introduced DAP, the first panoramic measurement deep foundational model trained on a dataset of 2 million [7] - It constructs a three-stage pseudo-label pipeline, refining high-quality supervision signals from 1.7 million internet panoramic images, using DINOv3-Large backbone and distance-adaptive branches [7] - In multiple zero-shot tests, it has set records in Stanford2D3D and Matterport3D, providing precise depth perception for robot navigation, autonomous driving, and VR/AR applications [7] Group 7 - Kuaikan Manhua's version 2.0 has launched AI interactive comics, allowing users to "soul travel" into the comic world and interact with characters in real-time, altering the story direction with each interaction [8] - Characters come with complete backstories and personalities, anchoring dialogues within the story world, establishing long-term companionship through shared experiences and narrative context [8] - It integrates AI capabilities from Tencent Cloud's DeepSeek API, Volcano Engine's Doubao, Alibaba's Tongyi Qianwen, and others, with a nearly threefold increase in weekly paid user rates during the testing phase [8] Group 8 - Nvidia's Jim Fan reviewed the robotics sector, stating it remains chaotic, with severe hardware reliability issues hindering iteration speed, facing daily challenges like overheating and motor failures [9] - The robotics field's benchmarks are a disaster, lacking unified hardware platforms, task definitions, and scoring standards, with teams claiming SOTA based on ad-hoc benchmarks [9] - The VLM-based VLA route feels incorrect, as VLM is optimized for visual question answering rather than the physical world, suggesting that video world models may be a better pre-training target [9] Group 9 - Andrew Ng highlighted that China has surpassed the US in releasing open-source weight models, with cumulative adoption about to exceed that of US open-source models [10] - Many users are incorrectly utilizing Agentic AI, suggesting that tasks should not be completed in one go but through an iterative workflow: outlining, researching, drafting, and revising [10] - The most important future skill will be accurately communicating needs to computers, with programming knowledge significantly enhancing efficiency, contrary to the advice of "no need to learn programming" [10] Group 10 - The Information's year-end analysis of the AI industry indicates that nearly all leading AI companies are now investing in humanoid robot technology development, shifting from competing on models to competing on ecosystems [11] - Overall, Google is seen as the strongest in comprehensive strength, with Anthropic signing a $20 billion TPU chip order, Meta seeking to adopt Google's TPU, and OpenAI signing a $38 billion server agreement with Amazon [11][12] - The alliances among the nine major AI giants are tighter than ever, as companies reduce reliance on one partner while becoming entangled with another, creating a complex interdependent network [12]

Group 1 - High-level openness is seen as a "driving force" for promoting mutually beneficial cooperation between China and the world, with a focus on aligning with international high-standard economic and trade rules by 2025 [1] - The Central Economic Work Conference has identified "maintaining openness and promoting multi-field cooperation for win-win outcomes" as a key task for China's economic work in the coming year [1] - There is a growing influx of foreign investment into China, with over 60,000 new foreign-invested enterprises established in the first 11 months of the year, marking a 16.9% year-on-year increase [3] Group 2 - Multinational companies are increasingly viewing China as a global innovation hub, with significant investments in research and development centers to cater to local market demands [2] - The actual use of foreign capital in high-tech industries reached 221.26 billion RMB, accounting for over 30% of the total foreign investment in the country [3] - China's foreign trade has shown resilience, with a total import and export value of 41.21 trillion RMB in the first 11 months of the year, reflecting a 3.6% year-on-year growth [5] Group 3 - The establishment of the Hainan Free Trade Port has led to a significant increase in foreign trade registration, with 1,972 new foreign trade registered enterprises in the first week of its operation, a 2.3-fold increase [8] - China is actively promoting institutional openness, with various measures aimed at stabilizing foreign investment and expanding service sector openness [8] - The signing of the upgraded version of the China-ASEAN Free Trade Area 3.0 agreement marks a shift towards "institutional openness," enhancing cooperation between the two regions [9]

Core Insights - The article emphasizes the vision of world models in understanding and transforming the physical world, focusing on the continuous technological breakthroughs that lead to generative AI in autonomous driving [2] Group 1: World Model Exploration - Various companies are building their cloud and vehicle-based world models using open-source algorithms for long-tail data generation and closed-loop simulation/evaluation [4] - The exploration of world models in autonomous driving includes video generation, OCC generation, and LiDAR point cloud generation, with notable works from Wayve, OccWorld, and others [3][4] Group 2: Challenges in Understanding World Models - The definition of world models remains ambiguous, leading to confusion among newcomers in the field [5] - Many beginners struggle to grasp the concepts of data generation and closed-loop simulation, often feeling lost despite extensive efforts [6] Group 3: Course Offering - The article introduces a course on world models in autonomous driving, developed in collaboration with industry algorithm experts, aimed at helping learners understand the field from theory to practice [6][8] - The course covers various chapters, including an introduction to world models, background knowledge, discussions on general world models, and practical applications in video and OCC generation [11][12][13][14] Group 4: Course Structure and Content - The course is structured into six chapters, each focusing on different aspects of world models, including their historical development, technical stacks, and industry applications [11][12][13][14][15] - The course aims to equip participants with the necessary skills to understand and implement world models in autonomous driving, preparing them for job interviews and practical applications [16][19]

Core Viewpoint - Goldman Sachs maintains a "Buy" rating for SenseTime Technology (00020) based on its technological advantages in generative AI, product innovation, and broad market prospects, with a 12-month target price of HKD 3.53 [1] Group 1: Generative AI Product Innovations - SenseTime has launched several new generative AI products, including the multi-episode generative agent Seko 2.0, office AI agent "Xiao Huan Xiong 3.0," and "Ru Ying" marketing agent, showcasing significant improvements in content generation and cost advantages [2] - The Seko 2.0 agent features a proprietary real-time video generation architecture, LightX2V, which can reduce the production cycle of animated series by 80% to 90%, indicating a strong commercial outlook as AI video generation costs decrease [2] - The "Xiao Huan Xiong 3.0" office AI agent can generate high-quality PPTs with one click and process large-scale data in seconds, capitalizing on the expected growth of the office software market to USD 17 billion by 2030 [3] Group 2: Market Potential and Financial Projections - Goldman Sachs predicts that the revenue contribution from generative AI will rise from 77% in the first half of 2025 to 91% by 2030, highlighting the strong growth potential of this segment for SenseTime [4] - The company is expected to achieve positive EBITDA of RMB 205 million by 2026, with projections of further growth to RMB 1.119 billion by 2027, indicating a turnaround in profitability [4]

Group 1 - Goldman Sachs maintains a "buy" rating for SenseTime, setting a 12-month target price of HKD 3.53, based on the company's technological advantages in generative AI, product innovation, and market potential [1] - Goldman Sachs predicts that the revenue contribution from generative AI will reach 91% by 2030, with an expected EBITDA of RMB 205 million turning positive by 2026 [1][4] Group 2 - SenseTime has launched several new generative AI products, including Seko 2.0, "Xiao Huan Xiong 3.0" office AI, and "Ru Ying" marketing AI, which enhance content generation capabilities and demonstrate significant cost advantages [2][3] - The Seko 2.0 product features a proprietary real-time video generation architecture, LightX2V, which can reduce production cycles for episodic content by 80%-90% compared to traditional methods [2] - The "Xiao Huan Xiong 3.0" office AI can generate high-quality PPTs and process large-scale data in seconds, with Goldman Sachs forecasting the office software market to reach USD 17 billion by 2030, driven by generative AI functionalities [3] - The "Ru Ying" marketing AI enhances operational efficiency in live e-commerce through a matrix of agents, automating backend processes and improving data analysis efficiency by six times [3] Group 3 - Goldman Sachs employs a two-stage DCF model and 2026 EV/Sales ratio to assess SenseTime's long-term growth potential, indicating a 73% upside from the current stock price [4] - By the first half of 2025, the revenue contribution from generative AI is expected to reach 77%, with a significant increase to 91% by 2030, highlighting the strong growth driver for SenseTime's future performance [4] - The EBITDA is projected to turn positive in 2026 at RMB 205 million, with further growth to RMB 1.119 billion by 2027 [4]

Core Viewpoint - Goldman Sachs maintains a "Buy" rating for SenseTime, setting a 12-month target price of HKD 3.53, citing the company's technological advantages in generative AI, product innovation, and broad market prospects [1] Group 1: Generative AI Product Innovations - SenseTime has launched several new generative AI products, including the multi-episode generative agent Seko 2.0, the office AI agent "Xiao Huan Xiong 3.0," and the marketing AI agent "Ru Ying," which significantly enhance content generation capabilities and demonstrate strong cost advantages in edge deployment solutions [2] - The Seko 2.0 agent features a proprietary real-time video generation architecture, LightX2V, which can reduce the production cycle of episodic dramas by 80% to 90% compared to traditional methods, indicating a promising commercial outlook as AI video generation costs decrease [2] - The "Xiao Huan Xiong 3.0" office AI agent can generate high-quality PPTs with one click and process large-scale data in seconds, while the market for office software is expected to reach USD 17 billion by 2030, with generative AI functionalities contributing to incremental revenue [3] Group 2: Market Expansion and Efficiency - The "Ru Ying" marketing AI agent enhances operational efficiency in live e-commerce through a matrix of five intelligent agents, automating backend management and significantly improving data review efficiency by six times [3] - The launch of these products marks SenseTime's expansion into specific scenarios, aiming to enhance client productivity and drive value realization [3] Group 3: Financial Projections and Growth Potential - Goldman Sachs predicts that SenseTime will achieve EBITDA profitability by 2026, with an expected amount of RMB 205 million, and further growth to RMB 1.119 billion by 2027 [4] - The revenue contribution from generative AI is projected to rise from 77% in the first half of 2025 to 91% by 2030, highlighting the strong growth driver of generative AI for SenseTime's future performance [4]

在专题研讨论坛中，玄华智能运营合伙人杨屾围绕《生成式 AI 赋能教育教学融合实践》展开深度分 享，结合具体应用案例，详解生成式 AI 在课程设计、教学模式创新、实践场景拓展等方面的落地路 径。提出 "技术工具 + 教学场景 + 行业需求" 三位一体的融合方案，引发参会高校代表的广泛共鸣与热 烈探讨。 此次参与承办首届辽宁省高校建筑类（土木类）院长研讨会，是玄华智能深耕 AI 教育领域、助力区域 高等教育高质量发展的重要实践。未来，玄华智能将持续以技术创新为核心，深化与高校、行业的协同 合作，推动 AI 技术与教育教学、产业发展的深度融合，为 "育才兴辽" 战略落地与建筑业数智化转型贡 献更多力量。（玄华） 原标题：首届辽宁省高校建筑类（土木类）院长研讨会举办 本次研讨会设置主旨报告、专题研讨、圆桌对话等多元环节，聚焦学科建设、人才培养、产教融合三大 核心议题，搭建起政产学研用高端对接平台。玄华智能作为 AI 教育领域的创新实践者，全程助力会议 落地，凭借在数智化技术研发与教育融合应用的深厚积累，为会议注入科技赋能的核心动力。 会上，玄华智能创始人、CEO 柴桥子以《AI 赋能高校数智化新生态建设探索与实践》为 ...

（责任编辑：董萍萍 ） 兴业证券指出，内存价格持续飙升，DDR4 8Gb DRAM现货价同比上涨886%，批量合同价环比涨 80%，看好存储设备、被动元件、封测等上游领域复苏。AI浪潮带动算力需求爆发，服务器、AI芯片、 光芯片、存储、PCB等环节价值量提升，预计全球生成式AI支出2030年达6990亿美元（CAGR 21%）。 国产半导体设备进展显著，上海微电子中标1.1亿元光刻机项目，未来3年"先进工艺扩产"将成为自主可 控主线，CoWoS及HBM卡位AI趋势下先进封装重要性凸显。 【免责声明】本文仅代表作者本人观点，与和讯网无关。和讯网站对文中陈述、观点判断保持中立，不对所包含内容 的准确性、可靠性或完整性提供任何明示或暗示的保证。请读者仅作参考，并请自行承担全部责任。邮箱： news_center@staff.hexun.com 科创芯片ETF国泰（589100）跟踪的是科创芯片指数（000685），单日涨跌幅达20%，该指数从科 创板市场中选取涉及芯片设计、制造、封装测试等全产业链环节的上市公司证券作为指数样本，聚焦半 导体材料、设备及设计等核心技术领域，反映科创板芯片相关上市公司证券的整体表现。 ...