Group 1 - The Chinese Academy of Sciences and the Chinese Academy of Engineering announced the election results for the 2025 academicians, with 73 academicians elected to the Chinese Academy of Sciences and 71 to the Chinese Academy of Engineering [1][2] - In the robotics field, five experts were elected, including four from the Chinese Academy of Sciences and one from the Chinese Academy of Engineering [1] - The average age of the newly elected academicians from the Chinese Academy of Sciences is 57.2 years, with 67.1% being 60 years old or younger, and five female scientists elected [1] Group 2 - Yin Zhouping, a prominent expert in electronic manufacturing equipment, was elected as an academician of the Chinese Academy of Sciences, recognized for his contributions to digital manufacturing and electronic manufacturing technology [3] - Li Shutao, an expert in remote sensing image processing and information fusion, was also elected as an academician of the Chinese Academy of Sciences, with significant achievements in artificial intelligence and information processing [4] - Zhou Zhihua, a vice president of Nanjing University and an expert in artificial intelligence and machine learning, was elected as an academician of the Chinese Academy of Sciences, noted for his impactful research and publications [6] - Hu Dewen, a strategic scientist in control science and cognitive science, was elected as an academician of the Chinese Academy of Sciences, recognized for his work in brain signal analysis and brain-machine interfaces [7] - Chen Xin, a leading expert in high-speed and high-precision electronic manufacturing equipment, was elected as an academician of the Chinese Academy of Engineering, known for his breakthroughs in core technologies for electronic manufacturing [8][11]

刚刚，清华大学刘云浩和南京大学周志华，正式当选中国科学院院士。 计算机领域，清华大学的刘云浩教授，正式当选中国科学院院士。 人工智能领域，南京大学周志华教授，正式当选中国科学院院士。 2025年中国科学院院士增选当选院士公布！ 中国科学院选举产生了73名中国科学院院士和27名中国科学院外籍院士。 刘云浩 刘云浩，1971年11月出生，现年53岁。 他于1995年在清华大学自动化系，获得工学学士学位；1997年在北京外国语大学高级翻译学院，获得文学硕士学位。 随后，他分别于2003年和2004年，在美国密歇根州立大学计算机系，获得工学硕士和工学博士学位。 他曾出任： 信息产业部邮政电子办副主任兼党支部书记； 香港科技大学计算机科学与工程系副教授、系研究生部主任； 清华大学信息科学与技术国家实验室特别研究员； 教育部信息系统安全重点实验室主任； 清华大学可信网络与系统研究所所长； 清华大学软件学院院长。 2011年，入选国家首批青千、国家杰青、长江学者。2014年11月，入选IEEE Fellow；2015年12月，入选ACM Fellow。 刘云浩在一年之内，拿遍国家青千、国家杰青、长江学者。 有人称赞他，仅用 ...

Core Insights - The rapid development of artificial intelligence technology has made quantitative trading an essential investment tool in major overseas capital markets, with over 70% of U.S. stock trading driven by algorithms, a figure that continues to rise [2] - Major global quantitative trading firms, such as Millennium, WorldQuant, Two Sigma, Citadel, D.E. Shaw, and Bridgewater, are expanding at an unprecedented pace, with their latest holdings in U.S. stocks for Q3 now disclosed [3][4] Group 1: Millennium - Millennium Management, founded in 1989, has achieved an impressive record of positive returns in 33 out of 34 years, with only one loss during the 2008 financial crisis [3][4] - The firm employs strict drawdown management, reducing allocated funds by half after a 5% drawdown and liquidating strategies after a cumulative 10% drawdown [3] - Millennium is recognized as a "Huangpu Military Academy" for Chinese quantitative private equity, with many prominent fund managers in China having previously worked there [4] Group 2: WorldQuant - WorldQuant, a major player in global quantitative hedge funds, was established in 2007 as a spin-off from Millennium, focusing on global quantitative analysis [7] - The firm has developed a central knowledge base containing 4 million "alphas" to industrialize the generation of excess returns [7][8] - Several notable Chinese fund managers, including the founders of Jiukun Investment, have previously worked at WorldQuant [8] Group 3: Two Sigma - Two Sigma, founded in 2001, is known for its application of data science and advanced technology in investment, managing assets between $50 billion and $100 billion [11] - The firm has established a wholly-owned subsidiary in Shanghai and has been instrumental in training numerous quantitative talents in China [11][12] - Two Sigma's Q3 holdings reached $67.17 billion, a growth of 18.95% from the previous quarter, with major positions in S&P 500 ETF, Financial ETF, and Consumer Discretionary ETF [13][14] Group 4: Citadel - Citadel, founded in 1990, has become the most profitable hedge fund globally, with cumulative net returns exceeding $65.9 billion [15] - The firm processes approximately $410 billion in trades daily, covering over 11,000 U.S. listed securities [15] - Citadel's Q3 holdings amounted to $657.15 billion, reflecting a 14.09% increase from the previous quarter, with significant positions in S&P 500 ETF and Nasdaq 100 ETF [17][21] Group 5: AQR Capital Management - AQR, established in 1998, integrates academic research with quantitative investment strategies, managing $159.2 billion [23][24] - The firm focuses on a diverse range of investment strategies, emphasizing systematic methods and diversification [23] - AQR's Q3 holdings reached $155.99 billion, a 29.05% increase from the previous quarter, with major investments in Nvidia, Microsoft, and Apple [24][28] Group 6: Renaissance Technologies - Renaissance, founded in 1982 by mathematician James Simons, is renowned for its quantitative trading success, managing over $65 billion [30][31] - The firm has consistently achieved high returns, including significant profits during market downturns [30] - Renaissance's Q3 holdings totaled $75.75 billion, with major positions in Palantir, Nvidia, and Roblox, and a notable increase in Google shares [31][35]

Jay 发自 凹非寺 量子位 | 公众号 QbitAI 与此同时，中国科学院新增外籍院士27人，中国工程院新增外籍院士24人。 人工智能领域，南京大学周志华教授，正式当选。 从今往后，是周志华教授，更是周志华院士。 周志华，院士！ 周志华，江苏盐城人，1973年出生，现年51周岁。 1992年起，他入学南京大学计算机科学与技术系，后分别拿下本 （1996年） 、硕 （1998年） 、博 （2000年） 学位。 周志华主要从事人工智能、机器学习、数据挖掘等领域的研究工作。 2001年，周志华留校任教；次年就被破格聘任为副教授。 2025年中国科学院、工程院院士增选结果，正式出炉！ 今年共有144人当选—— 中国科学院院士73人、中国工程院院士71人 。 2018年3月，周志华任南京大学人工智能学院院长 （兼） ；2022年6月，任南京大学智能科学与技术学院院长 （兼） 。 2023年5月，南京大学任命周志华为南京大学计算机科学与技术系主任，兼人工智能学院院长。 2024年7月31日，南京大学官网"现任领导"栏目更新信息显示，周志华已任该校副校长。 而如今，他又成功当选中国科学院院士。 在国际上与人工智能相关重要 ...

Core Points - The Chinese Academy of Sciences and the Chinese Academy of Engineering announced the results of the 2025 academician elections, electing 73 academicians from the former and 71 from the latter, further optimizing the structure of the academician team in China [2][3] - The average age of newly elected academicians from the Chinese Academy of Sciences is 57.2 years, with 67.1% being 60 years old or younger, and 5 female scientists among the elected [2][3] - Notably, several scholars related to the field of artificial intelligence were elected, highlighting China's ongoing breakthroughs and emphasis on cutting-edge technology [4][7] Summary by Sections Chinese Academy of Sciences - A total of 908 academicians are currently in the Chinese Academy of Sciences after this election [3] - The newly elected academicians include prominent figures in computer science and artificial intelligence, indicating a focus on advanced technology [7] - Notable elected members include Liu Yunhao, a professor at Tsinghua University, recognized for his research in computer system architecture and IoT [10][11] and Zhou Zhihua, a professor at Nanjing University, known for his work in machine learning theory and methods [12][15] Chinese Academy of Engineering - The Chinese Academy of Engineering elected 71 academicians and 24 foreign academicians in 2025 [25] - The election reflects a diverse range of expertise across various engineering disciplines, including mechanical, electronic, and environmental engineering [26][27][29][30] - The elected academicians are affiliated with prestigious institutions, contributing to advancements in their respective fields [26][27][29][30]

Summary of Novartis Management Investor Event Company Overview - **Company**: Novartis - **Event**: 2025 Meet Novartis Management Investor event - **Focus**: Interaction between investors, analysts, and management teams, discussing company performance and future strategies [1][3] Core Industry Insights - **Industry**: Pharmaceuticals - **Strategy**: Transitioned to a pure-play medicines company, divesting from Alcon and Sandoz, leading to a focused strategy on four key therapeutic areas and key geographies [4][6] Financial Performance - **Sales Growth**: Achieved 7% sales growth and 15% core operating income growth [4] - **Free Cash Flow**: Generated $15.9 billion in the first nine months of the year, comparable to the full year 2024 number [5] - **Return on Invested Capital**: Improved to 17%, above peer median [5] - **Shareholder Returns**: Ranked in the top five for total shareholder returns over five years and second over three years [5] Strategic Focus Areas - **Therapeutic Areas**: Focus on four key therapeutic areas and technology platforms, including data science and artificial intelligence [6] - **Capital Allocation**: Emphasis on investing in business growth, with ongoing share buybacks and a commitment to a growing dividend [7] Product Portfolio and Pipeline - **Blockbusters**: 14 in-market blockbusters and eight brands with peak sales potential over $3 billion [8] - **Pipeline Assets**: 30 high-value pipeline assets with 15 submission-enabling readouts expected in the next two years [11][22] - **Market Potential**: Estimated market sizes for new platforms: $36 billion in RNA therapeutics, $28 billion in radioligand therapies, and up to $49 billion in cell and gene therapies [9] Growth Outlook - **Sales Guidance**: Upgraded guidance for 2024-2029 to 6% sales growth, with 5-6% expected from 2025 to 2030 [11][12] - **Core Margin**: Anticipated decline of 1-2 percentage points in core margin in 2026 due to the Avidity acquisition, with recovery expected to over 40% by 2029 [12] Launch Performance - **Recent Launches**: Strong performance in recent product launches, with significant market shares achieved within months [15][16] - **International Markets**: Notable growth in China, Germany, and Japan, with aspirations to improve market positions [16] Key Product Updates - **Kisqali**: Upgraded to over $10 billion peak sales potential based on strong early performance [17] - **Cosentyx**: Maintained outlook at $8 billion, supported by recent positive data [17] - **Kesimpta**: Projected at over $6 billion, with ongoing evaluations of competitive dynamics [17] - **Scemblix**: Upgraded guidance based on strong brand share growth despite competition [18] Regulatory and Market Challenges - **European Market**: Facing challenges due to MFN agreements affecting pricing and market access, leading to potential delays in product launches [55][56] - **Asia Growth**: Significant opportunities identified in Asian markets, particularly China and Japan [56] ESG Commitment - **Sustainability**: Recognized as a leader in ESG matters, with a AAA MSCI rating and a commitment to global health initiatives [48] Conclusion - **Overall Strategy**: Novartis is positioned for continued growth with a strong pipeline, focused strategy, and commitment to shareholder returns, despite facing regulatory challenges in Europe and a competitive market landscape [49]

Core Insights - The evolution of AI is transitioning from "capability breakthroughs" to "system construction" by 2025, focusing on reliability, interpretability, and sustainability [2] - NeurIPS, a leading academic conference in AI and machine learning, received 21,575 submissions this year, with an acceptance rate of 24.52%, indicating a growing interest in AI research [2] - The conference will take place from December 2 to 7, 2025, in San Diego, USA, with a new official venue in Mexico City, reflecting the diversification of the global AI academic ecosystem [2] Event Overview - The "NeurIPS 2025 Paper Sharing Conference" is designed for domestic AI talent, featuring keynote speeches, paper presentations, roundtable discussions, poster exchanges, and corporate interactions [3] - The event is scheduled for November 22, 2025, from 09:00 to 17:30 at the Crowne Plaza Hotel in Zhongguancun, Beijing [5][6] Keynote Speakers and Topics - Morning keynote by Qiu Xipeng from Fudan University on "Contextual Intelligence: Completing the Key Puzzle of AGI" [8][14] - Afternoon keynote by Fan Qi from Nanjing University on "From Frames to Worlds: Long Video Generation for World Models" [10][17] Paper Presentations - Various presentations will cover topics such as data mixing in knowledge acquisition, multimodal adaptation for large language models, and scalable data generation frameworks [9][30] - Notable presenters include doctoral students from Tsinghua University and Renmin University, showcasing cutting-edge research in AI [9][30] Roundtable Discussion - A roundtable discussion will explore whether world models will become the next frontier in AI, featuring industry experts and academics [10][20]

Investment Rating - The report does not explicitly state an investment rating for the industry Core Insights - The future of corporate banking cash management is being reshaped by four major trends, emphasizing the need for customized solutions and data-driven services to enhance client relationships and operational efficiency [5][11] - There is a significant increase in demand for strong liquidity and cash management strategies due to complex geopolitical factors and fluctuating economic conditions [5][9] - The transition from transactional products to strategic, data-driven services is accelerating, requiring advanced knowledge and integrated data flows [5][10] Summary by Sections Cash Management Trends - The report identifies four key trends reshaping cash management, focusing on automation, data-driven services, customized solutions, and blockchain technology [7][11] - Companies are increasingly recognizing the potential of automated digital solutions and richer data sets to enhance their cash management capabilities [5][10] Strategic Cash Management - CFOs and treasury executives are under pressure to transform operations and establish new collaborative models, maximizing internal liquidity and reducing reliance on external financing [9][11] - There is a growing expectation for banks to provide actionable insights and industry-specific knowledge to meet client needs [9][11] Data-Driven Services - The report highlights the importance of integrating multi-source data to provide timely, actionable recommendations tailored to client operations and industry standards [31][32] - Clients are interested in AI-driven solutions that offer predictive insights and access to external data sets [33][36] Industry-Specific Solutions - There is a strong demand for customized cash management services that cater to the unique characteristics of different industries, with a significant portion of CFOs expressing the importance of industry-specific knowledge [43][45] - Banks are encouraged to develop vertical solutions that simplify core functions and adapt to industry-specific cash flow cycles and payment patterns [49][54] Digital Assets and Blockchain - The rise of digital assets, including stablecoins and tokenized funds, presents new opportunities and challenges for cash management solutions [56][61] - Banks are expected to leverage blockchain technology to enhance transaction efficiency and expand their service offerings to digital-native clients [62][63]

以常州瑞声科技为例，在高精密的生产过程中，瑞声科技运用人工智能和机器学习技术提升产品检测效率，通过自动化实现模具循环使用和铜材回收等工 艺，减少材料浪费，践行可持续发展承诺。 崔玉善说："苹果公司也致力于让世界更美好，过去十年间，已将全球碳足迹降低了超过60%，并大幅提升了再生材料的使用比例。苹果公司承诺到2030 年，在供应链和整个产品生命周期中实现百分百碳中和。" 据悉，目前，苹果公司产品在中国已有超过90%的生产制造采用可再生能源，立讯精密等供应商已完全实现使用清洁能源生产苹果公司产品，并在关键 iPhone部件中100%使用再生稀土元素、再生铜和再生钨。 【环球网科技报道 记者 张阳】11月18日，以"汇聚新质生产力开放合作赢未来"为主题的2025年产业链供应链国际合作交流会暨企业家太湖论坛在无锡成功 举办。作为商务部"投资中国"系列活动重要组成部分，论坛搭建起跨国界、跨行业的交流合作平台，吸引了苹果、辉瑞、LG新能源等全球知名企业代表齐 聚，共探产业链供应链高质量发展新路径。 论坛现场披露的数据显示，江苏已成为外资企业投资兴业的优选地。2024年江苏实际使用外资190.5亿美元，占全国比重16.4% ...

[文/观察者网 阮佳琪] 中国人工智能技术正以爆发式速度迭代，与美国的差距快速拉近。据彭博社19日报道，一项最新统计显 示，清华大学在人工智能领域发表的学术论文中，入选"全球引用量最高100篇论文"的数量位居全球高 校之首，且该校获批的相关专利数量更超过麻省理工学院、斯坦福大学、普林斯顿大学与哈佛大学这四 所美国顶尖高校的总和。 报道引述励讯集团（RELX）旗下专利数据分析服务商律商联讯（LexisNexis）的数据称，2005年至 2024年末，清华累计获得4986项人工智能与机器学习相关专利，仅去年一年就新增900余项。而在全球 该领域的有效专利族（同一项核心技术在多国/地区申请的全部专利）中，中国占比已过半。 不过目前，美国在人工智能领域仍保有最具影响力的专利与性能最优的模型。例如，在专利影响力排名 中，哈佛大学与麻省理工学院始终领先于清华大学。斯坦福大学发布的《人工智能指数报告》也显示， 2024年美国科研机构研发的知名人工智能模型达40个，而中国为15个。但在部分性能测评指标上，中国 机构正逐步缩小与美国的差距。 这也让美国想要保住人工智能科研领域的领先地位，正面临不小挑战。华盛顿智库美国信息技术与 ...