电影 《银河系漫游指南》中的巴别鱼 科幻小说《银河系漫游指南》里面有种叫巴别鱼的生物，可以突破传统翻译工具的物理限制，通过解析脑电波实现跨物种语言的即时互译。这个看似遥不 可及的幻想，如今在深圳一家名为时空壶的公司手中，正逐步走向现实。 时空壶是全球首创AI同传翻译耳机的公司，他们正在用技术打破人类之间的语言壁垒，让跨语言交流变得如同说同一种母语一样自然。从2016年创立至 今，他们的产品已销往全球170多个国家，并且在北美市场占据了40%的份额，用户突破百万。今年初，中国海关总署甚至将时空湖的W4 Pro同传翻译耳 机作为中国从"制造"到"智造"转型的代表展示给全世界。 随着大模型技术的发展，AI翻译正从简单的"直译"进化为理解语境、把握情感的"意译"。年初在拉斯维加斯举办的消费电子展（CES）上，时空壶发布了 翻译行业的首个人工智能同声传译系统Timekettle Babel OS （The Road to Babel Fish 通往巴别鱼之路），首次将大语言模型作为AI翻译的底层能力，打造 逼近母语的自然交流体验，赋能时空壶各终端硬件和软件应用。 其中"Babel"在希伯来语中的原意是"混乱"。《圣经》 ...

压力是影响人类认知表现的重要因素，但它对大语言模型(LLMs)性能的影响尚未被充分研究。近期， 中国科学院自动化研究所曾毅研究员领导的人工智能安全与超级对齐北京市重点实验室和类脑认知智能 团队联合进行了相关开创性研究。结果显示，给人工智能适当压力能使其更好解决问题。 他表示，这些发现不仅在理论上有价值，也为如何优化AI系统在不同压力环境下的表现提供了实用指 导。例如，在需要情绪智能的应用中可能需要中等压力水平，而在需要减少偏见的场景中则应避免高压 力环境。 这项研究的实际应用贡献在于，为设计能在现实世界高压环境中保持性能的AI系统提供指导，特别是 在客户服务、医疗保健和紧急响应等压力普遍存在的场景。此外，在人机交互优化方面，提供了基于压 力水平优化人机交互的方法，可以据此研制更自然、更有效的AI助手。 人工智能安全与超级对齐北京市重点实验室成立 中关村论坛期间，北京市成立人工智能安全治理协同创新矩阵。人工智能安全与超级对齐北京市重点实 验室作为矩阵成员实验室首次正式对外公开，其由中国科学院自动化研究所牵头，北京大学、北京师范 大学参与共建。 作为北京市科技创新体系的重要组成部分，新组建的人工智能安全与超级对齐 ...

Core Insights - The article highlights the launch of the Lingyu CPU processor by Ruisi Semiconductor, marking it as China's first fully self-developed high-performance RISC-V architecture server chip, aimed at high-performance computing and applications like DeepSeek [2][4]. Company Overview - Ruisi Semiconductor, established in 2018, focuses on developing processors based on the open-source RISC-V architecture, providing chip solutions for various sectors from edge computing to data centers [4]. - The company has secured 37 invention patents, 19 software copyrights, and 6 integrated circuit layout designs related to the Lingyu processor [4]. Product Details - The Lingyu processor features a "one chip, dual-core" design architecture, consisting of 32 high-performance general computing cores (CPU) and 8 dedicated intelligent computing cores (LPU), optimized for tasks like inference for open-source large language models [2]. - The performance of the Lingyu processor is claimed to be on par with mainstream server chips from Intel and AMD [2]. Market Potential - The global intelligent computing market is projected to reach $39 billion in 2024 and grow to $89 billion by 2029, with a CAGR of 17.8%. The Chinese intelligent computing market is expected to exceed 150 billion RMB by 2028, with an annual growth rate of 21% [2]. - The global high-performance computing (HPC) market is anticipated to surpass $40 billion and potentially double by 2032 [2]. Ecosystem and Partnerships - The Lingyu processor ecosystem includes over 50 partners, covering key component manufacturers, OEMs, system software, and industry solutions, with successful software adaptations for various operating systems [4]. - Notable partners include Lenovo, SenseTime, Jiangbolong, and XSKY, supporting mainstream databases, machine learning frameworks, and complex deployment scenarios [4]. Future Plans - The company aims to expand its product matrix and accelerate the large-scale deployment of RISC-V server chips, contributing to a secure and efficient domestic computing ecosystem [5].

3月31日，教育部举行发布会，介绍深入贯彻落实《教育强国建设规划纲要（2024—2035年）》，推进 语言文字信息化发展情况。 教育部语言文字信息管理司司长刘培俊表示，为抢抓大语言模型迭代升级新机遇、助力"人工智能+"新 行动、回应经济社会发展新需求，日前教育部、国家语委、中央网信办印发了《关于加强数字中文建设 推进语言文字信息化发展的意见》（以下简称"《意见》"），推进语言文字和信息技术深度融合、系统 部署语言文字信息化发展。 一是创新应用自然语言处理、大语言模型、多模态信息处理、知识图谱、语料加工五项前沿技术，重点 服务大语言模型等人工智能技术创新应用"制高点"，夯实国家关键语料基础设施"新基建"；二是系统建 设语言文字规范标准、资源服务、人才培养、协同创新和安全治理五大保障体系，重点提升语言文字信 息化的基础能力；三是统筹实施数字中文服务教育发展、助力科技创新、赋能文化传承、推动产业升 级、促进社会进步五大赋能行动，重点推进语言技术与关键领域需求深度融合应用。 《意见》还着眼于创新长效化机制协同行动，构建数字中文建设赋能全局新格局。 刘培俊表示，加快推进语言文字信息化发展，将以重大应用作为战略牵引，有效 ...

新京报讯(记者冯琪)"新型国家语料库"如何建设？3月31日，新京报从教育部召开的新闻发布会上获 悉，教育部、国家语委已经支持布局了五个领域的自主安全可控大语言模型建设项目；教育部已经启动 布局了新型国家语料库的建设，包括"中华文脉新型语料库""中华大阅读体系语料库"等。 "当前以深度求索(DeepSeek)等为代表的人工智能技术创新不断取得突破性的进展，在这个大背景下， 国家提出建设新型国家语料库的战略部署，凸显了其重要性、必要性和紧要性。"在3月31日的新闻发布 会上，教育部语言文字应用管理司副司长王晖说道。 他指出，现在在一些应用领域，主要是在语言的教育教学和研究领域，有多个语料库，但是很多语料库 还处于单一文本模式和领域应用阶段，在建设的理念、技术和方法、规模，以及数据多样性、时效性尤 其是与人工智能相结合的大规模应用方面还存在不足，难以满足多元化、动态化尤其是智能化的语言数 据需求。 "我们总的考虑是：立足人工智能时代大背景，突破传统语料库单一文本模式和领域应用壁垒，以大模 型训练及性能评测、智能计算为核心，以新质态、多模态、多语言、大规模、全域性为突出特性，为通 用领域和细分领域多场景应用及创新发展 ...

当中国最大互联网公司遇到一局上限足够高的新游戏，它可能试试就放过吗？ 文 丨 王与桐 程曼祺 编辑 丨 程曼祺 黄俊杰 面对 AI，字节依然是那个字节：一旦看到有潜力的方向，就加倍、饱和、全面出击。 一个最新例子是：智能体应用 Manus 出圈前后，字节已有至少 5 个团队在开发不同智能体产品，其中 有些是对内工具。Manus 是 3 月 6 日刚由创业公司 Monica 开始内测的智能体应用。 去年 11 月我们在一篇文章中说："中国掌握极强产品能力和流量资源的不止字节。微信还没出手呢。" 现在手握微信的腾讯终于出手，以出其不意的方式：全面接入 DeepSeek。 这对字节产生了更实质的影响。3 月 19 日腾讯总裁刘炽平在业绩会上说，从 2 月到 3 月，元宝日活 增长了 20 倍，排名中国 AI 应用第三。他没有说的前两名分别是 DeepSeek 和字节豆包。 仅用字节十分之一的时间和小得多的投放预算，腾讯的用户规模来到了豆包的约 1/5。 在中国所有大科技公司中， 字节本是大语言模型起步最晚的一家。在 2022 年底 OpenAI ChatGPT 上 线前，百度、华为、阿里、腾讯（按发布时间顺序）都已 ...

Market Outlook - The international market is expected to continue rapid growth, with developing countries leading the way, accounting for two-thirds of international revenue [2][3] - The average market share of the company's three major product lines in developing countries is still in the high single digits, significantly lower than in the domestic market [2][3] - The company anticipates that developing countries will remain a key driver of growth for a considerable time [2][3] Domestic Market Recovery - Factors that hindered growth in the domestic market last year, such as industry regulation and insufficient local government funding, are expected to see a turnaround this year [3] - The company won 160 out of 200 ultrasound units in a centralized procurement project initiated by the Hainan Provincial Health Commission, indicating improved bidding success [3] - The issuance of local government special bonds for hospital renovations and equipment procurement is accelerating, which is expected to support domestic business recovery [3] AI Applications in Medical Imaging - The company has made significant advancements in AI applications across various medical imaging fields, including cardiovascular and obstetrics [4][5] - The newly launched Nuewa A20 aims to provide a comprehensive ultrasound solution covering all workflow stages, enhancing clinical application effectiveness [4][5] - AI features such as early pregnancy volume recognition and obstetric section identification significantly improve examination efficiency and reduce clinical workload [5][6] Impact of Centralized Procurement - Increased procurement centralization in certain regions may affect profitability, but the company maintains that the impact on profit margins is manageable [7][8] - The focus on compliance and transparency in procurement is expected to reduce unreasonable price increases while ensuring reasonable profits for manufacturers [7][8] - Continuous high R&D investment and innovative capabilities are expected to strengthen the company's market position despite competitive pressures [7][8]

Core Insights - The core viewpoint of the articles is that China Merchants Bank (CMB) is leveraging artificial intelligence (AI) to enhance its operations and create a new growth trajectory, marking a significant shift in its technology strategy from "Digital CMB" to "Smart CMB" [1][2][3]. Group 1: AI Strategy and Implementation - CMB's AI strategy has been elevated, focusing on the integration of AI technologies, particularly large language models, into its operations [2][4]. - The bank has reported over 120 applications of large models across various sectors, achieving a total of 26 million hours of labor savings through intelligent applications [4]. - CMB's AI assistant, "AI Xiao Zhao," is the first in the banking industry to utilize large models, significantly improving efficiency in financial processes [4]. Group 2: Technological Advancements and Investments - CMB's technology investments reached 13.35 billion yuan in 2024, accounting for 4.37% of its operating income, with a workforce of 10,900 dedicated to research and development [3]. - The bank's historical technological innovations have positioned it among the top tier of global banks, particularly in cloud computing and mobile internet technologies [3][5]. - CMB has achieved a "cloud revolution" in computing power over three years, enhancing the efficiency and cost-effectiveness of its large model development [6][7]. Group 3: Competitive Landscape - The global banking sector is witnessing a race in AI adoption, with major international banks like JPMorgan Chase and DBS Bank also integrating AI into their operations [5]. - CMB's competitive edge lies in its integrated capabilities in computing power, algorithms, and data, supported by a vast customer base of over 200 million retail clients and 3 million corporate clients [6][7]. - The bank's strategy emphasizes a hybrid model of human and AI collaboration, ensuring a balance between speed and personalized service [8].

Core Insights - The company reported a revenue of HKD 4.114 billion for the fiscal year 2024, with the sports knowledge subscription platform generating HKD 2.59 billion, a year-on-year increase of 13.68%, accounting for 62.9% of total revenue [1] - The company's loss narrowed to HKD 14.7 million, a 32.2% reduction compared to the HKD 21.7 million loss in 2023, primarily due to increased other income and reduced selling expenses [1] Revenue and Growth - The sports knowledge subscription platform's revenue increased by 13.7% compared to the previous year [2] - The total user base of the platform rose by 21.4% to 106 million, with average monthly active users growing by 17.4% year-on-year [1] Strategic Initiatives - The company aims to diversify its digital sports entertainment business while addressing the competitive landscape and evolving consumer demands [1] - Significant resources have been allocated to R&D, leading to the launch of targeted products in the sports knowledge subscription sector, enhancing competitiveness and user retention [2] Market Expansion - The company is focusing on optimizing its business model in the sports and leisure gaming sector, reducing investment in lower-yield games, and leveraging existing IP for sports game distribution [2] - International expansion efforts have progressed, with successful localized testing in Southeast Asia receiving positive feedback from users [2] Brand and Community Engagement - The company has successfully hosted major events, including the WBC Professional Boxing Championship in Foshan, which garnered over 300 million views, significantly enhancing brand influence [3] - The company is committed to social responsibility by promoting fitness through various sports events, contributing to the development of a strong sports culture in China [1]

Core Viewpoint - Apple's decision to purchase approximately $1 billion worth of NVIDIA's GB300 NVL72 GPU cluster servers marks a significant shift in its AI strategy, acknowledging the advantages of the GPU ecosystem and generative AI paradigm over its self-developed chips [1][3][21]. Group 1: Apple's Shift to NVIDIA - Apple has historically relied on its self-developed chips, achieving great success with its Apple Silicon series in mobile and edge computing [3]. - The recent order for NVIDIA's GPUs indicates Apple's recognition of the GPU ecosystem's superiority in the generative AI space, driven by urgent market demands for high-performance computing [3][4]. - Analysts suggest that Apple plans to order around 250 NVL72 servers, with each server costing between $3.7 million and $4 million, totaling nearly $1 billion [3]. Group 2: Implications of Siri's Performance - Siri's declining competitiveness against rivals like Google Assistant and Alexa has prompted Apple to reassess its AI hardware strategy [4][5]. - The anticipated updates to Siri have been delayed, reflecting the challenges Apple faces in enhancing its AI capabilities [4][5]. Group 3: Generative AI and Market Dynamics - The rise of generative AI has redefined user expectations for intelligent assistants, shifting from simple command execution to intelligent collaboration [5]. - Apple's investment in NVIDIA GPUs is speculated to support the development of an Apple LLM, enhance Siri, and integrate AI into various applications [5][6]. Group 4: GPU vs. ASIC - The choice of NVIDIA's GPUs over self-developed ASICs highlights the critical importance of time and performance in the AI race, with NVIDIA's established ecosystem providing immediate solutions [8][16]. - NVIDIA's GPUs have become the de facto standard for training large language models (LLMs), showcasing their performance and ecosystem maturity [8][11]. - The high cost of NVIDIA GPUs, which have surged to $90,000 each, reflects their dominant market position, with NVIDIA reporting a revenue of $39.3 billion and a gross margin exceeding 70% [8][9]. Group 5: Future Outlook - Despite the current preference for NVIDIA GPUs, Apple may still pursue a hybrid strategy, utilizing NVIDIA for model training while relying on its own chips for inference [6][19]. - The ongoing competition between ASICs and GPUs suggests that while ASICs may face challenges now, they are not entirely out of the picture for future applications [19][21].