资料图。本文来源 ： 澎湃新闻 记者 吴雨欣 活动上，蔡崇信与白宫人工智能和加密货币事务负责人David Sacks展开观点交锋。David认 为，美国赢得人工智能竞赛非常重要。 蔡崇信则表示，他本人对于"赢"的定义，不是谁推出了最强大的人工智能模型，而是谁能更快 地采用它。美国大量的资源应该投入到技术应用和推广上，而不仅仅是对技术投入资金，超大 规模公司每年的投资大约800亿美元，但在中国，有几件事正在发生，一是中国已经拥护开源， 二是包括阿里巴巴在内的许多公司，已经推出了更小的模型，而不是万亿参数的模型。 蔡崇信认为，如果希望人工智能普及，可以看看现在的中国，"我并不是说中国在模型战争中技 术上获胜，但就实际应用以及受益人群而言，人工智能已经取得了长足的进步。有调查显示， 去年，只有8%的公司在其业务中使用人工智能，现在的比例正接近50%。" 在访谈中，主持人问及，随着越来越多的工作量（由人工智能完成），劳动力是否会自然地减 少？ 对此，蔡崇信回答道："我们还没有宣布任何因人工智能导致的裁员，我一直在问我们的工程主 管，现在有多少代码是由人工智能编写的。我得到的答案各不相同，这取决于你问哪个部门， 但我认 ...

10月9日，知名播客All-in发布其举办的All-in Summit峰会的视频和音频，在这场活动上，阿里巴巴集团董事局 主席蔡崇信表示，人工智能竞赛不是赢者通吃，而是一场"漫长的马拉松"，每周都有一个模型处于领先地位， 但到了下周，另一个模型就会超越它们。 活动上，蔡崇信与白宫人工智能和加密货币事务负责人David Sacks展开观点交锋。David认为，美国赢得人工 智能竞赛非常重要。 蔡崇信则表示，他本人对于"赢"的定义，不是谁推出了最强大的人工智能模型，而是谁能更快地采用它。美国 大量的资源应该投入到技术应用和推广上，而不仅仅是对技术投入资金，超大规模公司每年的投资大约800亿 美元，但在中国，有几件事正在发生，一是中国已经拥护开源，二是包括阿里巴巴在内的许多公司，已经推出 了更小的模型，而不是万亿参数的模型。 责编：汪云鹏 校 对： 吕久彪 百万用户都在看 折算率"归零"！多家券商出手，影响多大？ 蔡崇信认为，如果希望人工智能普及，可以看看现在的中国，"我并不是说中国在模型战争中技术上获胜，但 就实际应用以及受益人群而言，人工智能已经取得了长足的进步。有调查显示，去年，只有8%的公司在其业 务中使用 ...

4 、马斯克的人工智能初创公司 xAI ，正以一种与芯片采购直接 " 挂钩 " 的创新结构，推进一轮高达 200 亿美元的融资。 此次融资最引人注目的特点是， 英伟达将作为重要的股权投资方参与其中，出资额或达 20 亿美元，且整轮融资的结构都与 xAI 采购英伟达 GPU 的计划深度绑定。 英伟达首席执行官黄 仁勋确认，英伟达已投资 xAI 。黄仁勋表示，他本人在 OpenAI 与 AMD 的交易公开宣布前并不知情。他直言后悔未更早投资 OpenAI ，同时指出 OpenAI 的营收正呈指数级增长。 1 、据中国证券报， A 股市场于 10 月 9 日迎来四季度首个交易日。这个假期，全球金融市场并不平静：海外股市普遍小幅走强，为 A 股提供了积极的外 部环境； 与此同时，国际金价历史性突破 4000 美元 / 盎司关口，彰显出全球资金的避险需求。国内层面，刚刚过去的黄金周展现消费韧性，出行人次与 部分核心消费场景的亮眼数据，为经济基本面注入暖意。 在此背景下，私募人士普遍表示，海外市场走强与国内积极因素叠加，有望共同支撑 A 股后市 表现。 2 、 今日凌晨，美联储公布 9 月会议纪要显示，美联储官员在上个月 ...

机器人流程自动化公司UiPath(PATH.US)盘初一度涨超20%，最高触及15.15美元，创近4个月新高。消息 面上，UiPath正与英伟达合作，将人工智能模型集成到敏感的企业工作流程中，并与OpenAI在企业代理 自动化方面展开合作。(格隆汇) ...

特朗普政府同意使用马斯克旗下xAI的人工智能模型。（华尔街日报） 风险提示及免责条款 市场有风险，投资需谨慎。本文不构成个人投资建议，也未考虑到个别用户特殊的投资目标、财务状况或需要。用户应考虑本文中的任何 意见、观点或结论是否符合其特定状况。据此投资，责任自负。 ...

Group 1: Market Overview - On September 25, the main funds in the Shanghai and Shenzhen markets experienced a net outflow of 23.6 billion yuan, with the ChiNext board seeing a net outflow of 8.9 billion yuan and the CSI 300 index experiencing a net outflow of 0.63 billion yuan [1] - Among the 31 first-level industries, 7 sectors saw an increase, with the media industry leading at a growth rate of 2.23%, while 24 sectors declined, with textiles and apparel, comprehensive, agriculture, and household appliances all dropping over 1% [1] Group 2: Fund Inflows and Outflows - Eight industries received net inflows from main funds, with the computer and electric equipment sectors leading with inflows exceeding 1 billion yuan each; media, communication, and non-ferrous metals also saw inflows above 590 million yuan [1] - The electronics industry had the highest net outflow, totaling 14.843 billion yuan, followed by machinery, basic chemicals, household appliances, and defense industries, each with outflows exceeding 1 billion yuan [1] Group 3: Individual Stock Performance - Among individual stocks, 86 saw net inflows exceeding 100 million yuan, with 17 stocks receiving over 400 million yuan; the top performer was Inspur Information, with a net inflow of 1.777 billion yuan and a closing price increase of 9.99% [2][4] - Other notable stocks included New Yisheng and Huagong Technology, with net inflows of 1.283 billion yuan and 1.173 billion yuan respectively, both experiencing price increases [2][4] Group 4: Notable Trends - CATL's stock rose by 3.4%, with a net inflow of 1.115 billion yuan, following an upgrade from JPMorgan, which raised its rating from neutral to overweight due to increased demand for energy storage batteries [3] - The upcoming 2025 Artificial Intelligence Computing Conference in Beijing is expected to drive interest in computing power stocks, with Alibaba announcing a partnership with NVIDIA to develop AI models [2]

路透社9月22日消息，阿布扎比技术创新研究所（TII）与英伟达（Nvidia）宣布，双方已在阿联酋联合 设立一家研究实验室，专注于研发下一代人工智能模型和机器人。TII称，该实验室是英伟达在中东地 区首个人工智能技术中心，旨在将其多学科研究与英伟达的人工智能模型及算力资源相结合，共同推动 全球人工智能发展。 ...

具体措施包括预付本公司所需的能源及电力基础设施费用，以免抬高周边社区电价，保护消费者免受数 据中心带来的额外成本影响;同时承诺"对于我们消耗的每一千瓦时化石来源电力，微软都将向电网等量 回馈无碳能源，包括正在波蒂奇县建设的250兆瓦太阳能项目。" 微软与WE Energies的合作将确保在透明电价下持续探索能源输送、发电与使用方式，保障电网可靠 性。 在就业方面，史密斯透露，首个数据中心全面运营后预计将雇佣约500名全职员工，第二个数据中心建 成后总员工数将增至约800人。 此外，微软本周早些时候还宣布，未来四年将向英国投资300亿美元。 智通财经APP获悉，微软(MSFT.US)周四宣布已签署协议，将在三年内投入40亿美元，在威斯康星州建 设第二座数据中心。此前该公司已在该州投入33亿美元，两项投资合计使威斯康星州数据中心总投资额 达到73亿美元。首个数据中心位于芒特普莱森特，预计2026年初启用。 微软副董事长兼总裁布拉德·史密斯在博客文章中指出，该数据中心旨在助力人工智能研究人员和工程 师构建全球最先进模型、加速创意测试并提升工作效率，其核心不仅是运行人工智能，更是"创造人工 智能"——下一代人工智能模 ...

Core Insights - Microsoft plans to expand its physical infrastructure to train its own AI models, aiming to compete with companies like OpenAI and Anthropic [1] - The company emphasizes the importance of self-sufficiency in AI for a corporation of its scale, while also deepening partnerships with OpenAI and other model manufacturers [1] - Microsoft has launched its first large language model, trained on 15,000 Nvidia H100 chips, indicating a focus on efficiency in model creation compared to competitors [2] Group 1 - Microsoft is making a "massive investment" in its computing clusters to train AI models [1] - Mustafa Suleyman, head of consumer AI at Microsoft, highlighted the need for self-sufficiency in AI for large companies [1] - The relationship between Microsoft and OpenAI is showing signs of tension as both companies launch competing products [1] Group 2 - Microsoft’s large language model is reportedly 6 to 10 times smaller in computing cluster scale compared to models developed by Meta, Alphabet, and xAI, suggesting higher efficiency [2] - Microsoft plans to adopt a multi-model strategy across all its products, allowing for the selection of AI models based on customer preferences [2] - A non-binding agreement has been signed between Microsoft and OpenAI to allow OpenAI to advance its restructuring plan into a for-profit entity [2]

Investment Rating - The report does not provide a specific investment rating for the industry Core Insights - The increasing adoption of artificial intelligence (AI) in financial institutions is transforming operations, risk management, and customer interactions, but the limited explainability of complex AI models poses significant challenges for both financial institutions and regulators [7][9] - Explainability is crucial for transparency, accountability, regulatory compliance, and consumer trust, yet complex AI models like deep learning and large language models (LLMs) are often difficult to interpret [7][9] - There is a need for robust model risk management (MRM) practices in the context of AI, balancing explainability and model performance while ensuring risks are adequately assessed and managed [9][19] Summary by Sections Introduction - AI models are increasingly applied across all business activities in financial institutions, with a cautious approach in customer-facing applications [11] - The report highlights the importance of explainability in AI models, particularly for critical business activities [12] MRM and Explainability - Existing MRM guidelines are often high-level and may not adequately address the specific challenges posed by advanced AI models [19][22] - The report discusses the need for clearer articulation of explainability concepts within existing MRM requirements to better accommodate AI models [19][22] Challenges in Implementing Explainability Requirements - Financial institutions face challenges in meeting existing regulatory requirements for AI model explainability, particularly with complex models like deep neural networks [40][56] - The report emphasizes the need for tailored explainability requirements based on the audience, such as senior management, consumers, or regulators [58] Potential Adjustments to MRM Guidelines - The report suggests potential adjustments to MRM guidelines to better address the unique challenges posed by AI models, including the need for clearer definitions and expectations regarding model changes [59][60] Conclusion - The report concludes that overcoming explainability challenges is crucial for financial institutions to leverage AI effectively while maintaining regulatory compliance and managing risks [17][18]