俄罗斯 Russia 技术主权驱动军工民用并进 ◎本报驻俄罗斯记者张浩 2025年俄罗斯人工智能（AI）发展呈现"政策驱动场景落地、军工与民用双线并进、自主技术生态初步 成型"的特征。 俄罗斯政府高度重视AI发展，普京总统11月在"人工智能之旅"会议上明确要求，在生成式AI领域要掌握 全套自主技术，强调其关乎"国家主权和技术主权"。为支撑算力需求，俄计划未来20年新建38座核电机 组。2025年AI市场规模预计达1万亿卢布，其中企业级解决方案占比首超消费级达52.3%。 在科研突破与军事应用方面，青年科学家团队研发的Headless-AD模型显著优化了长文本处理能力。军 事领域，集成AI能力的"蜂群"无人机系统于5月开始高强度测试，其已具备自主地形匹配与目标分类功 能。 在行业场景落地方面，AI技术深入航天、医疗、金融等各个领域。6月，俄航天局计划将国产大模型 GigaChat部署至国际空间站，旨在将卫星图像分辨率提升一倍。医疗领域，Yandex推出了首批儿科专用 核磁共振影像分析AI工具。截至2025年11月底，莫斯科数字医疗平台已覆盖全国近2000家机构，医生 可通过该系统使用AI技术分析放射学影像及其他 ...

Core Insights - In 2025, DeepSeek emerged, significantly lowering the application cost and threshold of AI technology, leading to a boom in vertical applications and a shift in industry competition from single model comparisons to full-stack ecosystem battles [1] - The AI landscape is transitioning from a dominance of OpenAI to a multi-polar competition, with applications expanding from software to intelligent hardware [1][2] - The "Hundred Mirrors War" in AI hardware is intensifying, with major tech companies investing heavily in AI glasses and smartphones, marking a significant shift in human-computer interaction [6] Group 1: AI Application Market Dynamics - The introduction of DeepSeek in February 2025 has drastically reduced AI inference costs, spurring growth in vertical applications such as AI in health, education, and office settings, leading to a reshuffling of the AI application market [2] - User data shows a concentration effect, with DeepSeek achieving an average monthly download of 34.72 million and ByteDance's Doubao at 31.44 million, dominating the general AI assistant market [2] - Vertical scenarios are becoming crucial for AI applications, evolving from language Q&A and content generation to multi-task intelligent agents across various industries [2][3] Group 2: Hardware Developments and Market Trends - McKinsey predicts a surge in vertical AI intelligent agents by 2025, with over 70% of AI value potential expected to come from these applications [3] - The global smart glasses market saw a shipment of 4.065 million units in the first half of 2025, a 64.2% year-on-year increase, with China accounting for 26.6% of the market share [6] - The global smart glasses market is projected to reach $42 billion by 2030 and $117 billion by 2040, despite facing challenges in technology maturity and privacy compliance [6] Group 3: Future Growth Areas - Key growth points in the AI field for 2026 include large models with continuous learning capabilities, real-time interactive 3D models, and seamless intelligent agents that integrate tools, data, and workflows [4] - The AI smartphone market is expected to see a shipment of 147 million units in China in 2026, a 31.6% year-on-year growth, capturing 53% of the overall market [8] - The "Doubao phone" model is gaining attention, with a focus on a multi-to-multi intelligent connection ecosystem, avoiding a zero-sum game in the internet ecosystem [9]

2025.12. 18 这场由巨头博弈引发的震荡，将一个核心议题推至台前：在以大模型为核心的AI时代，硬件的技术范 式是否正在从通用GPU转向专用芯片如TPU？这是否意味着一场结构性的变革已然来临？ 本文字数：1632，阅读时长大约3分钟 作者 | 第一财经 刘佳 这一悬念不仅关乎国际巨头的战略布局，也紧密牵动着中国AI算力产业链的神经。作为对标英伟达、 不久前刚刚上市的中国GPU厂商代表，摩尔线程创始成员、摩尔学院院长李丰与沐曦高级副总裁孙 国梁在今日腾讯contech大会上"同框"，并回应了对于两种路线的看法。 在李丰看来，争议背后其实是"通才与专才"的分工，而非简单的替代关系。 他分析，谷歌能做TPU，本质上是因为它是全栈整合公司。谷歌有强大的 Infra、基础模型与云服务 形成闭环，把模型跑在自家芯片上量身优化，实现成本性价比的最大化。"但绝大部分企业不具备这 样的垂直整合能力。" 他总结，GPU持续保持优势的原因有三个：灵活度是"甜点"、多模态时代的全功能性、生态的护城 河。 谷歌新一代AI模型Gemini 3系列的发布，在硬件领域投下一颗"重磅炸弹"——其自研TPU（张量处 理器）所展现的性能与成 ...

谷歌新一代AI模型Gemini 3系列的发布，在硬件领域投下一颗"重磅炸弹"——其自研TPU（张量处理 器）所展现的性能与成本优势，被外界解读为对英伟达GPU（图形处理器）霸主地位的强劲挑战。资本 市场反应迅速，英伟达市值一度蒸发超千亿美元。 生态更是关键壁垒，英伟达之所以在计算领域成为"王者"，得益于它所建立起的CUDA生态，能够联合 所有开发者建设生态。李丰称，摩尔线程也在搭建自己MUSA的生态。 沐曦创始人孙国梁的观点更加直接：任何芯片架构都没有高低优劣之分，关键还是看场景。 他认为，GPU和ASIC（专用芯片）的架构几十年前就存在，已经是超级稳态。而现在的大模型太卷 了，迭代速度非常快，达到了按周计、按月计的程度，任何基础模型远未到达收敛的时间点，通用 GPU 的泛化能力和适配性仍是核心竞争力，现在业界还很难把一个专用性的产品放在通用的场景里。 但与此同时，客户是多元化的，应用场景分散、层出不穷，因此GPU和类似TPU这样的ASIC会长期共 存。 这场由巨头博弈引发的震荡，将一个核心议题推至台前：在以大模型为核心的AI时代，硬件的技术范 式是否正在从通用GPU转向专用芯片如TPU？这是否意味着一场结构 ...

按一下此處編輯母版標題樣式 文件名 产品及投资方案部 ｜2025年12月8日 每周投资策略 中信証券財富管理 (香港) CITIC Securities Wealth Management (HK) 投资策略 每周投资策略 上周环球 大类资产表现 (1) 美国市场焦点 预计美联储 本周再次降息 股票 "AI 泡沫"的中短期走向； Alphabet；亚马逊 ETF Invesco纳斯达克100 指数ETF (2) 澳大利亚市场焦点 通胀持续高企 令降息预期落空 股票 推荐原材料和红利板块； Northern Star； Woodside (3) 印度尼西亚 市场焦点 通胀缓解提供降息依据 股票 2026年谨慎乐观； 中亚银行 ；Telkom ETF VanEck印度尼西亚 指数ETF 资料来源：中信证券财富管理 (香港) 1 本周主要地区 经济数据公布日程 上周环球 股市表现 美国降息预期稳固，全球股市普遍向好 资料来源：彭博、中信证券财富管理 (香港) 注：截至2025年12月5日 3 上周环球 债市表现 美债收益率曲线熊市走陡 日本央行发表鹰派言论，日本国债遭抛售 | | | | | 上周环球债市表现 | ...

Group 1: DeepSeek's New Model - DeepSeek has open-sourced a new model, DeepSeek-Math-V2, which is the first open-source model to reach IMO gold medal level in mathematics [1] - The performance of Math-V2 surpasses that of Google's Gemini DeepThink in certain aspects, as demonstrated in the IMO-ProofBench benchmark and recent math competitions [1] Group 2: AI Scaling Era Conclusion - Ilya Sutskever, CEO of Safe Superintelligence, claims that the era of AI scaling has ended, indicating a shift back to research paradigms rather than mere expansion [2] - He emphasizes that the current computational power cannot continuously yield better scaling, blurring the line between scaling and waste [2] Group 3: Baidu's AI Department Restructuring - Baidu has established two new AI departments: the Basic Model R&D Department and the Application Model R&D Department, both reporting directly to CEO Li Yanhong [3] - The restructuring reflects Baidu's commitment to enhancing its R&D capabilities in large models, with leadership from internally cultivated talents [3] Group 4: Nvidia's Response to Short Selling - Nvidia responded to Michael Burry's claims about the minimal real demand for AI products, clarifying that its strategic investments represent a small portion of its revenue [4] - Following a significant drop in Nvidia's stock price, the company aims to prove the sustained strength of AI demand [4] Group 5: Google's AI Glasses Project - Google is accelerating its new AI glasses project, with hardware manufacturing by Foxconn and chip supply from Qualcomm, expected to enter small-scale production [6] - The project is independent of the previously announced AR glasses and is led by a key figure from Google Labs [6] Group 6: HSBC's Warning on OpenAI's Profitability - HSBC forecasts that OpenAI will face severe financial pressure over the next decade, predicting it will struggle to achieve profitability even with a projected revenue of $213 billion by 2030 [7] - The analysis highlights the significant cash flow deficit OpenAI may encounter, amounting to $207 billion [7] Group 7: Industrial Fulian's Performance Clarification - Industrial Fulian clarified rumors regarding a downward adjustment of its Q4 performance targets, stating that operations are proceeding as planned [8] - The company's stock experienced fluctuations, reflecting market concerns about its relationship with Nvidia [8] Group 8: Denial of Google Order by Tianfu Communication - Tianfu Communication denied rumors of securing a $3 billion order from Google, amidst speculation about its role as a supplier [9] - The stock prices of related companies fluctuated based on market interest in optical module stocks [9] Group 9: Meta's Interest in Google's TPU - Meta is reportedly considering a multi-billion dollar purchase of Google's TPU for its data center development, which could mark the first external sale of Google's TPU [10] - This potential shift could impact Nvidia, as Meta is currently its largest GPU customer [10] Group 10: AI's Water Consumption - A Morgan Stanley report highlights that AI not only consumes significant electricity but also requires substantial water resources for data center operations [11] - The report points out the challenges of water resource allocation for AI data centers, particularly in regions facing water supply issues [12]

Core Insights - DeepSeek has released its latest technology achievement, DeepSeek-Math-V2, which focuses on enhancing mathematical reasoning and theorem proving capabilities in large language models, boasting 685 billion parameters [1][5] Performance Highlights - DeepSeek-Math-V2 achieved gold medal levels in the 2025 International Mathematical Olympiad (IMO) and the 2024 Chinese Mathematical Olympiad (CMO), and scored 118 out of 120 in the Putnam 2024 competition, surpassing the historical human record of approximately 90 points [1][3] - In the IMO-ProofBench benchmark, Math-V2 scored nearly 99% on the basic set, significantly outperforming Google's Gemini DeepThink, which scored 89%. On the advanced set, Math-V2 scored 61.9%, slightly below Gemini DeepThink's 65.7% [4] Technological Innovations - DeepSeek-Math-V2 addresses the "illusion of reasoning" problem highlighted by former OpenAI chief scientist Ilya Sutskever, moving beyond mere answer correctness to ensure rigorous logical reasoning [5][6] - The model employs a strict "process-focused" strategy, requiring clear and logical step-by-step derivations, and does not reward correct final answers if intermediate steps are flawed [6] - A unique multi-level "Meta-Verification" mechanism enhances the reliability of scoring, increasing the confidence level from 0.85 to 0.96 [9] Industry Impact - The release of DeepSeek-Math-V2 has generated significant buzz in the overseas developer community, marking a strong comeback for DeepSeek and breaking the long-standing dominance of closed-source models in top reasoning capabilities [11] - The model's success in mathematical reasoning is expected to influence the coding model space, potentially disrupting existing code assistance tools [11] - The global AI landscape is transitioning from "text generation" to "logical reasoning," with DeepSeek's approach providing a clear path for technological evolution through rigorous validation mechanisms rather than sheer computational power [11]

Core Insights - DeepSeek has released a new model, DeepSeek-Math-V2, which is the first open-source model to achieve International Mathematical Olympiad (IMO) gold medal level performance [3][5] - The model outperforms Google's Gemini DeepThink in certain benchmarks, showcasing its capabilities in mathematical reasoning [5][9] Performance Metrics - DeepSeek-Math-V2 achieved 83.3% in IMO 2025 and 73.8% in CMO 2024, while scoring 98.3% in the Putnam 2024 competition [4] - In the Basic benchmark, Math-V2 scored nearly 99%, significantly higher than Gemini DeepThink's 89%, but in the Advanced subset, Math-V2 scored 61.9%, slightly lower than Gemini's 65.7% [5] Research Implications - The paper titled "DeepSeek Math-V2: Towards Self-Validating Mathematical Reasoning" emphasizes the importance of rigorous mathematical proof processes rather than just correct answers [8] - DeepSeek advocates for self-validation in mathematical reasoning to enhance the development of more powerful AI systems [8] Industry Reactions - The release of Math-V2 has generated excitement in the industry, with comments highlighting its unexpected success over Google's model [9] - The competitive landscape is evolving, with other major players like OpenAI and Google releasing new models, raising anticipation for DeepSeek's next moves [10]

Core Viewpoint - DeepSeek has released an open-source model, DeepSeek-Math-V2, which is the first model to achieve IMO gold medal level in mathematics and outperforms Google's Gemini DeepThink in certain benchmarks [3][5]. Group 1: Model Performance - DeepSeek-Math-V2 achieved nearly 99% on the Basic benchmark, significantly outperforming Gemini DeepThink, which scored 89% [5]. - In the more challenging Advanced subset, Math-V2 scored 61.9%, slightly below Gemini DeepThink's 65.7% [5]. - The model has demonstrated gold medal-level performance in IMO 2025 and CMO 2024, and nearly perfect scores in the Putnam 2024 exam (118/120) [8]. Group 2: Research and Development Insights - DeepSeek emphasizes the importance of verifying mathematical reasoning comprehensively and rigorously, moving from a result-oriented approach to a process-oriented one [8]. - The model is designed to teach AI to review proof processes like a mathematician, enhancing its ability to solve complex mathematical proofs without human intervention [8]. Group 3: Industry Reactions and Expectations - The release of Math-V2 has generated excitement in the industry, with reactions noting that DeepSeek has surpassed expectations by defeating Google's IMO Gold model by a 10% margin [9]. - There is anticipation regarding DeepSeek's next moves, especially concerning updates to its flagship models, as the industry awaits further developments [9].

Core Insights - DeepSeek has released a new model, DeepSeek-Math-V2, which is the first open-source model to achieve International Mathematical Olympiad (IMO) gold medal level performance [1] - The model outperforms Google's Gemini DeepThink in certain benchmarks, showcasing its capabilities in mathematical reasoning [1][5] Performance Metrics - DeepSeek-Math-V2 achieved 83.3% on IMO 2025 problems and 73.8% on CMO 2024 problems [4] - In the Putnam 2024 competition, it scored 98.3%, demonstrating exceptional performance [4] - On the Basic benchmark, Math-V2 scored nearly 99%, while Gemini DeepThink scored 89% [5] - In the Advanced subset, Math-V2 scored 61.9%, slightly below Gemini DeepThink's 65.7% [5] Research and Development Focus - The model emphasizes self-verification in mathematical reasoning, moving from a result-oriented approach to a process-oriented one [8] - DeepSeek aims to enhance the rigor and completeness of mathematical proofs, which is crucial for solving open problems [8] - The research indicates that self-verifying mathematical reasoning is a viable direction for developing more powerful AI systems [8] Industry Reaction - The release has generated significant interest, with comments highlighting DeepSeek's competitive edge over Google's model [9] - The industry is keenly awaiting further developments from DeepSeek, especially regarding their flagship model updates [10]