报告强调，该研究反映的是"潜在风险"，而非实际的失业人数。技术限制、基础设施等方面的差异和 技能储备不足意味着不同国家和行业的情况将存在巨大差异。 报告认为，在劳动领域，生成式人工智能本身并无好坏之分，其社会经济影响在很大程度上取决于对 技术普及的管理方式。 报告呼吁各国政府、雇主和工人组织参与社会对话，制定积极主动、具有包容性的战略，以提高生产 力和就业质量，特别是在受生成式人工智能影响的行业。 微信编辑 | 夏木 2025.05. 20 本文字数：471，阅读时长大约1分钟 据新华社消息，国际劳工组织20日发布一份有关生成式人工智能与就业的报告表示，全球四分之一 的工作岗位可能受到生成式人工智能影响。 报告显示，高收入国家就业岗位受生成式人工智能影响的比例更高，达到34%。由于生成式人工智能 理论上能实现多种任务的自动化，文职类工作面临的风险最为显著。这些岗位曾是发展中国家增加女 性就业的途径，因此女性就业更易受到生成式人工智能影响。 报告说，随着生成式人工智能能力的持续扩展，媒体、软件开发和金融等高度数字化的工作岗位也面 临日益增长的风险。 推荐阅读 中方正告：必将付出沉重代价！ ...

国际劳工组织5月20日发布一份有关生成式人工智能与就业的报告表示，全球四分之一的工作岗位可能 受到生成式人工智能影响。（新华社） ...

Group 1 - As of the end of 2024, there are 302 generative AI services registered in China, with over 4,700 companies and more than 600 million registered users [1] - Quantipai, a leading provider of scenario-based digital solutions in China, has submitted an updated prospectus to the Hong Kong Stock Exchange to accelerate its IPO process [1] - The company has over 8 years of experience in customer profiling and has developed its AI-related solutions and algorithms internally [1] Group 2 - By June 30, 2024, the company maintained over 51.8 million registered end customers through its proprietary applications, indicating significant customer base growth [2] - The company has achieved business scale growth, with over 133,100 inventory units and more than 2,600 business partners on its application [2] - In the context of explosive growth in generative AI technology, Quantipai is positioned as a key player in the consumer market precision matching sector, leveraging its self-developed AI algorithm matrix and a user base of over 50 million [2]

Core Insights - NVIDIA is transitioning from a chip manufacturer to a leader in AI infrastructure, emphasizing the transformative impact of AI and accelerated computing on the computing industry, which is driving the "Fourth Industrial Revolution" [1][2] - The company is focusing on building data centers and developing specialized libraries to accelerate applications across various fields, including telecommunications and robotics [1][2] - NVIDIA's new products, such as the GeForce RTX 50 series and the Grace Blackwell system, are designed to enhance AI computing capabilities for developers and enterprises [2][21] AI Infrastructure Development - NVIDIA is collaborating with Foxconn and TSMC to build a giant AI supercomputer, showcasing its commitment to advancing AI infrastructure [2][30] - The introduction of NVLink Fusion technology aims to support the construction of semi-custom AI infrastructure, allowing for flexibility in system design [30][32] - The company is positioning itself as a critical infrastructure provider for AI, similar to how electricity and the internet became essential infrastructures in the past [7][8] Product Innovations - The Grace Blackwell system features significant performance improvements, including a 1.5x increase in inference performance and enhanced memory capacity [22] - NVIDIA's new DGX Spark and DGX workstation products are designed for AI developers, providing powerful computing capabilities for prototyping and development [34][36] - The company is emphasizing the importance of libraries, such as CUDA and cuDNN, as foundational elements for accelerating various applications in AI and computing [9][13] Future Outlook - NVIDIA anticipates that AI will become an integral part of infrastructure across all sectors, with a projected market value in the trillions [8][9] - The company is committed to continuous innovation, with plans to enhance its platforms and products annually, ensuring they remain at the forefront of AI technology [21][23] - The integration of quantum computing into NVIDIA's offerings is expected to further enhance computational capabilities, positioning the company for future advancements in AI [15][20]

Group 1: Investor Relations Activity Overview - The investor relations activity was an earnings briefing held on May 16, 2025, via the "Investor Relations Interactive Platform" [3] - Key attendees included the Chairman, General Manager, CFO, and Board Secretary of the company [3][4] Group 2: Industry Performance and Company Growth - In 2025, China's intelligent computing power is expected to reach 1,037.3 EFLOPS, a 43% year-on-year increase [4][31] - The compound annual growth rate (CAGR) for China's intelligent computing power from 2023 to 2028 is projected at 46.2% [4][31] - The company achieved a revenue of 654.62 million yuan in 2024, with a 48.27% increase in computing power service revenue [5][10] Group 3: Financial Performance - The net profit attributable to shareholders in 2024 was 12.06 million yuan, marking a turnaround from losses [5][10] - In Q1 2025, the company reported a revenue of 198.27 million yuan, a 51.68% increase year-on-year [8][10] - The gross margin for computing power services was 32% in 2024, decreasing to 27% in Q1 2025 due to changes in service mix [11] Group 4: Accounts Receivable and Debt - As of the end of 2024, accounts receivable over three years amounted to 7.42 million yuan, representing about 7% of total accounts receivable [7] - The company's debt ratio stood at 76.53%, primarily due to contract liabilities and bank loans [12] Group 5: Customer Base and Market Position - The top five customers contributed 26.48% of total revenue in 2024, indicating a reasonable level of customer concentration [16] - The company has a sufficient order backlog and is actively pursuing large clients in the computing power service sector [13][14] Group 6: Research and Development - As of the end of 2024, the company employed 83 R&D personnel, accounting for 19.58% of total employees [24] - The company has no PhD holders among its R&D staff, with 12.05% holding master's degrees [24] Group 7: Future Outlook - The company anticipates continued growth driven by expanding business scale and improving operational efficiency [28] - The intelligent computing service market is expected to mature, with increasing demand for high-performance computing infrastructure [27][28]

当前，我国生成式人工智能产业发展迅速，相关企业数量已经超过4500家。然而，生成式人工智能与实 体经济融合的深度和广度仍有待提升，其巨大潜力尚未充分释放。究其原因，一方面在于生成式人工智 能技术本身仍处于快速发展期，成熟度有待提高；另一方面，不同产业因其自身特性和发展阶段的差 异，对生成式人工智能技术的需求呈现显著差异。为此，提升生成式人工智能技术的通用性和适用性、 推动科技创新与产业创新深度融合成为当务之急。 二是商业转化临界点尚未到来，行业落地较为缓慢。当前，生成式人工智能技术大规模商业化应用的路 径不畅，在算力资源紧张与训练成本高企的背景下，企业在实际部署中对生成式人工智能创新的投入回 报比不够理想，不同产业类型的生成式人工智能商业落地路径呈现出明显梯度。传统产业整体数字化水 平有限，模型与业务系统之间数据集成基础薄弱，短期内难以形成规模效应；新兴产业在部分场景中已 实现探索性应用，但普遍仍处于"点状突破、多点未及"的阶段；而未来产业由于具备更高的成本容忍度 与对颠覆式创新的开放态度，被认为是生成式人工智能最具战略潜力的应用场景，但产业落地的不确定 因素更多。根据行业特点发挥科技金融等政策工具的分类施策 ...

Investment Rating - The report indicates a positive outlook for equities, suggesting a potential for continued market upside due to light investor positioning and macroeconomic factors [30][32][46]. Core Insights - The macro team has upgraded growth forecasts, delayed rate cuts, raised global index targets, and reduced recession risk from 45% to 35% [1]. - The geopolitical landscape appears relatively stable, and resilient hard data combined with the potential recovery in soft data may support risk appetite in the near term [1][2]. - The report highlights the significant deflationary impact of generative AI, which is expected to outweigh inflationary pressures from tariffs [3]. - The S&P 500 index may witness one of the fastest recoveries from a 20% drawdown to new all-time highs [4]. - The VIX and MOVE indices have experienced one of the sharpest resets since 1990, indicating a decline in market volatility [6]. - Cyclical stocks have outperformed defensive stocks by 18% since April 4, reflecting an optimistic economic growth outlook [8]. - Despite resilient hard data, soft data has deteriorated year-to-date, marking one of the largest gaps since the 1970s [10]. - Financial conditions have not tightened significantly despite tariffs being eight times larger than in the previous trade war [12]. - US equity valuations are near historical highs, and global equity markets are not inexpensive relative to history [13]. Summary by Sections Market Dynamics - The report emphasizes the need for prudence and selectivity in adding risk, focusing on market dislocations and fundamentals [2]. - The performance of the Magnificent 7 has been notable, with a rally of 28% from its April low, although it remains down 5% year-to-date [49][50]. Economic Indicators - The report notes that the US equity sentiment indicator registered -1 standard deviations, typically indicating above-average returns for the S&P 500 in the following weeks [30]. - Hedge fund net leverage is at a particularly low level, suggesting potential for increased market activity [32]. Future Outlook - The report suggests that the current environment may favor strong pricing power, robust balance sheets, and sectors with secular growth [46]. - The anticipated earnings growth for the Magnificent 7 may exceed consensus estimates, indicating potential upside [53].

Core Viewpoint - Apple is unlikely to spend significant time discussing Siri at this year's WWDC, including future upgrades and previously announced features that were postponed [2] Group 1: Leadership Attitudes Towards AI - Apple's software chief, Craig Federighi, is skeptical about investing heavily in artificial intelligence, viewing it as not a core competency and believing it will not yield practical returns [2] - Other executives share a cautious stance similar to Federighi, emphasizing that in the AI realm, the product's nature is uncertain until investment is made, which contrasts with Apple's typical product development approach [2] - Despite some executives being convinced of AI's revolutionary potential, they have been unable to persuade Federighi, leading to many suggestions being ignored [2] Group 2: Challenges in AI Investment - Apple's AI chief, John Giannandrea, has struggled to gain immediate traction in his role, advocating for significantly increased investment in AI, but his efforts have often faced obstacles [2] Group 3: Upcoming Focus - Apple's strategy to recover from its perceived failure in AI will not be a focus at the upcoming WWDC, where the company plans to unveil iOS 19 and other new features [2]

Core Viewpoint - The article discusses the challenges and strategic decisions faced by Chinese smartphone manufacturers, particularly Xiaomi and OPPO, in their attempts to develop self-researched smartphone chips, highlighting the importance of timing, financial strength, and organizational structure in such endeavors [2][3][8]. Group 1: Historical Context - Huawei began self-researching smartphone chips in 2012, launching the Kirin series in 2014, but faced significant challenges due to U.S. export controls that disrupted its supply chain [2]. - Xiaomi launched its first self-researched chip, the Surge S1, in 2017, but faced difficulties with the subsequent Surge S2, leading to a halt in its chip project [2][3]. - OPPO initiated its chip development plan in 2019 but abruptly shut down its chip business in 2022 due to financial pressures and market uncertainties, marking a significant setback for the domestic chip development initiative [3][7]. Group 2: Financial Considerations - The financial health of a company is crucial for chip development, as the costs involved are substantial, with initial R&D investments potentially exceeding billions [6][7]. - OPPO reportedly spent hundreds of billions on its chip project, which became unsustainable amid declining sales and cash flow issues [7][8]. - In contrast, Xiaomi has maintained a stronger financial position, allowing it to restart its chip development with a more robust cash reserve and diversified business lines [8]. Group 3: Organizational Structure - The integration of chip development within the smartphone business is essential for success, as seen in Apple's model, where chip design is closely aligned with product needs [9][10]. - OPPO's independent chip division faced challenges due to a lack of synergy with the smartphone division, leading to inefficiencies and misalignment [9][10]. - Xiaomi's new chip initiative, "玄戒," is structured to ensure close collaboration with its smartphone division, enhancing decision-making efficiency and product alignment [10]. Group 4: Lessons Learned - Xiaomi's previous experiences with its chip projects have provided valuable lessons, leading to a more cautious and strategic approach in its current endeavors [11][12]. - The failure of OPPO's chip project serves as a reminder of the importance of understanding market dynamics and the need for a sustainable business model in chip development [11][12]. - Xiaomi's strategy includes leveraging partnerships, such as collaborating with MediaTek for 5G technology, to mitigate risks associated with self-researching complex technologies [12][16]. Group 5: Market Environment - The geopolitical landscape, particularly U.S.-China relations, has influenced the chip development strategies of Chinese companies, with recent shifts in focus away from high-end SoC chips [14][15]. - The rise of AI technology in smartphones has created a pressing need for customized chips, prompting manufacturers to invest in self-researched solutions to enhance AI capabilities [16][17]. - Xiaomi's expansion into electric vehicles and AIoT ecosystems provides additional opportunities for its chip development efforts, potentially allowing for cross-application of technology [17][18]. Group 6: Future Outlook - If Xiaomi successfully launches its "玄戒" chip, it could position itself as a major player in the high-end smartphone chip market, joining the ranks of Apple, Samsung, and Huawei [18][19]. - The article concludes that the success of Xiaomi's chip initiative will depend on its ability to navigate the complexities of the market and leverage its past experiences effectively [18][19].

Group 1: Technology Usage - In 2024, UK adults primarily focus on consolidating existing media technology rather than purchasing new devices due to economic pressures, with some opting to downgrade or cancel subscriptions in favor of streaming services [1] - The use of AI tools has significantly increased, with office workers commonly utilizing ChatGPT and Microsoft Copilot for repetitive tasks, and some applying these tools in personal life for tasks like writing applications and planning trips [1] - Smart home devices, particularly smart doorbells, are gaining traction due to security features, although users show resistance to subscription services [1] Group 2: Content Consumption - The trend of online on-demand viewing continues, with the proliferation of smart TVs boosting the usage of public service platforms like BBC iPlayer and ITVX, despite a decline in public trust towards BBC [2] - YouTube has become a major viewing platform, especially among males, surpassing traditional TV and streaming services, while social media usage is becoming more cautious [2] - Public service broadcasts like "Mr. Bates vs. The Post Office" have received acclaim for addressing social issues, highlighting the role of public service media [2] Group 3: Privacy and Security - Most participants view the provision of personal data as a "necessary evil" for using online services, showing a passive acceptance of this reality [2] - Users express confidence in identifying threats like scam calls and emails, primarily through methods such as checking sender addresses and consulting family [2] - Concerns are rising regarding AI-generated content, particularly deepfake videos on social media, leading users to rely on comments for content authenticity [2] Group 4: News Consumption - News consumption is increasingly polarized, with mainstream media facing trust issues, particularly among low-income and minority groups who feel underrepresented [2] - BBC remains the most widely used news service, but its credibility is challenged, leading some to turn to social media and YouTube for alternative news sources [2] - The coverage of the 2024 elections has drawn criticism for its confrontational debate style, with many participants believing media coverage does not significantly influence their voting decisions [2] Group 5: Reflection on Two Decades of Media Life - Over the past 20 years, smartphones have been recognized as the most influential technology, reshaping communication, content consumption, and social interaction [3] - Participants acknowledge the conveniences brought by technology but express concerns over privacy breaches and fragmented family life [3] - AI is viewed as a key variable for the future, with discussions around its potential impact on education and employment, alongside a desire for a return to simpler living [3] Group 6: Industry Guidelines for AI in Translation - The China Translation Association has developed the "Guidelines for the Application of Generative AI in the Translation Industry (2025)" to help the industry navigate technological advancements [5] - The guidelines focus on four dimensions: scenario application, capability enhancement, technology ethics, and quality control, addressing core contradictions in human-machine collaboration [5] - The guidelines will be regularly updated based on industry feedback to ensure ongoing relevance [5]