华见早安之声 市场概述 请各位听众升级为见闻最新版APP，以便成功收听以下音频。 科技股力挺三大美股指低开高走、四连阳，标普收创最高纪录；芯片关税消息后，英伟达大涨3%；特斯拉回落超0.6%，科技七巨头中独跌；矿业股Freeport McMoRan涨2.5%；"口服版减肥神药"在美率先获批后，诺和诺德欧股涨超9%，带动泛欧股指四日内三度收创历史新高。 法国通过短期预算案，十年期法债领涨同期欧债。 美GDP强劲打击降息预期，GDP后，美债价格止涨回跌、收益率抹平降幅、一度刷新近两周高位；美元指数收窄跌幅、靠近日高。日本高官暗示准备干预 后，日元两日反弹；离岸人民币连创14个月新高、一年多来首次盘中涨破7.02；比特币盘中较日高跌超2%、跌破8.7万美元。 金银铜继续创历史新高，现货金银盘中分别涨超1%和近4%，但在美GDP后曾"闪跌"；伦铜史上首次涨破1.2万美元；美国继续发力切断委内瑞拉石油贸 易，原油五连阳、收创至少近两周新高，五日涨近6%。 亚洲时段，A股三大指数冲高回落、小幅收涨，海南板块延续强势，商业航天概念下挫。 要闻 中共中央总书记对央企工作作出重要指示强调，充分认识职责使命，更好服务党和国家工作 ...

【环球时报报道 记者 倪浩 张依依】据路透社报道，多位知情人士透露，英伟达已告知中国客户，计划 于明年2月中旬，即中国农历春节前向中国客户交付其性能排名第二的人工智能（AI）芯片H200。其中 两位消息人士称，英伟达计划动用库存履行首批订单，预计发货总量为5000至10000套芯片模组，相当 于约4万至8万颗 H200芯片。 业内有观点认为，在国产芯片崛起、政策也有意推动国产替代的大背景下，英伟达是否能在短期内重回 中国市场仍难有定论。尤其是今年7月底，国家网信办就H20算力芯片漏洞后门安全风险约谈了英伟 达。统筹发展与安全，中国或更倾向于依靠科技自立自强对核心关键技术进行攻关。 中关村信息消费联盟理事长项立刚23日告诉《环球时报》记者，白宫希望放开禁令，维持英伟达业绩预 期，提振美国股市；而一些国会议员站在反华立场上，希望继续在高科技上封锁中国。电信与互联网行 业专家马继华表示，美国政府和英伟达急于重返中国市场，怕因中国芯片技术崛起而丧失市场竞争力和 空间，也担心英伟达业绩下滑而刺破华尔街担心的AI泡沫。项立刚说，中国乐见美国在高科技出口上 采取更加开放与合作的立场，但要保证向中国出口的芯片安全、环保、符合 ...

但咱们关起门来说点大实话，这事儿要是真这么简单，坐在那栋大楼里管外汇的几百个顶尖聪明人，难道还不如咱们这帮在手机屏幕前敲键盘的懂行？这里 面不仅不是阴谋，反而是一个让人特别难受的阳谋，是那种你明知道坑在哪，还得硬着头皮往里踩的死局。 我问你个问题，你有没有发现，最近网上特别流行一种说法，觉得只要全世界都不买美债，美国立马就得完蛋，或者说我们手里的那些美元如果不买美债， 拿去买芯片、买矿产，咱们的高科技早就起飞了？ 我昨天刷到这几句话的时候，盯着屏幕愣了好一会儿，感觉这逻辑听着特别解气，像是咱们手里攥着美国人的命门，只要轻轻一捏，对方就得跪地求饶。 我查了一下美国财政部发布的最新国际资本流动报告，也就是那个TIC数据，现在外国投资者持有的美债大概是8万亿美元左右，而美国现在的国债总额已 经飙到了35万亿美元以上。 这说明什么？说明这所谓"全世界买美债"的大盘子里，外国人早就不是绝对的大头了，真正的大头是美国国内的机构和美联储自己。你说如果不买美债，美 国能不能印钱过日子？理论上能，美联储可以直接下场买，这叫债务货币化。 但为什么他们不敢敞开了印？因为印钱是有代价的。我也琢磨过，要是美联储真把这就剩下的大几万亿债 ...

谷歌（股票代码：GOOG、GOOGL）在 2025 年初的处境步履维艰。尽管公司股价在 2024 年上涨 36%，但在华尔街眼中，谷歌在人工智能赛道的竞争中，依旧长期屈居开放人工智能（OpenAI）之 后，位列第二甚至第三名。 转眼至年末，局势彻底反转：谷歌已然一枝独秀、大放异彩；而开放人工智能的首席执行官山姆・奥特 曼却已宣布启动'红色警报'紧急预案，全力研发产品以对标谷歌最新发布的双子座 3 代（Gemini 3）人 工智能模型。颇具戏剧性的是，2022 年聊天生成预训练转换器（ChatGPT）面市时，彼时陷入被动的 谷歌也曾为自己拉响过红色警报。 谷歌在核心指标月活跃用户量上，也正不断缩小与开放人工智能的差距。 芯片业务方面，谷歌同样捷报频传。今年 10 月，克劳德（Claude）人工智能的研发商安索普人工智能 （Anthropic）宣布，将扩大谷歌人工智能芯片的使用规模，计划部署多达 100 万个谷歌人工智能处理 器，为其自研的人工智能软件提供算力支撑。 另有行业媒体《信息》报道，谷歌正洽谈向脸书、照片墙的母公司元宇宙（Meta）供应自研芯片，助 力其运行各类人工智能产品。 这一系列利好加持之下，这家 ...

Group 1 - The article highlights significant announcements in the stock market, including "suspensions and resumption of trading, share buybacks, investment wins, acquisitions, earnings reports, unlocks, and high transfers" to help investors identify potential investment hotspots and mitigate risks [1] - A company is involved in the fields of chip technology, 6G, commercial aerospace, and has products applicable to low-orbit satellite communication substrates and aircraft engines [1] - Another company has signed an agreement with a Chinese rocket company to implement an expansion plan for the Hainan commercial aerospace launch site [1] - A company plans to establish a production capacity of 1.2 million units for humanoid robots and solid-state batteries by 2026 [1]

Core Viewpoint - The United States plans to impose new tariffs on China's semiconductor industry, effective June 23, 2027, targeting chips that currently have 0% duties [1] Group 1 - The U.S. Trade Representative announced the upcoming tariffs on Chinese semiconductor products [1]

Core Viewpoint - Nanjing's Mu Xi Co., Ltd. has successfully listed on the Sci-Tech Innovation Board, becoming the second domestic GPU company to go public in A-shares, with its stock price soaring nearly 7 times on the first day, closing at 829.9 yuan per share and a total market value exceeding 330 billion yuan, highlighting the fertile ground for tech innovation in Nanjing [1] Group 1: Company Overview - Mu Xi Co., Ltd. is a leading domestic high-performance general-purpose GPU manufacturer, focusing on the independent research and development of full-stack high-performance GPU chips and computing platforms [1] - The company has achieved large-scale application in over 10 intelligent computing clusters in China and is one of the few GPU suppliers to commercialize "thousand-card clusters" [1] - The first domestically produced general-purpose GPU, Xi Yun C600, was recently launched in Nanjing, filling a gap in the high-end GPU application field in China [1] Group 2: Government Support and Investment - Nanjing's government investment fund has invested a total of 700 million yuan in Mu Xi Co., Ltd. since November 2020, operating in a market-oriented manner without government intervention in investment decisions [2] - The city has established 153 sub-funds aimed at early, small, long-term, and hard-tech investments, promoting deep integration of technological and industrial innovation, leading to the listing of 11 local companies including Mu Xi Co., Ltd. [2] - The government has created a supportive environment for tech innovation, providing comprehensive support in finance, policy, talent, and services, which has significantly contributed to the success of local enterprises [1][2] Group 3: Other Local Companies and Innovations - Haojing Cloud Computing Technology Co., Ltd. focuses on AI and has developed an enterprise AI operating system that integrates large model capabilities into business processes, serving over 18 billion terminal users globally [2] - Ying Shi Innovation Technology Co., Ltd., a global leader in panoramic cameras, has established an innovation center in Nanjing, leveraging local talent and resources to focus on AI imaging algorithms and VR/AR technologies [3] - The company Out the Door Innovation Technology Co., Ltd. has expanded its operations nationwide from Nanjing, benefiting from comprehensive support in talent introduction and project application [4]

Group 1 - Haikou's 15th Five-Year Plan emphasizes the implementation of "double 15% tax incentives" to attract foreign capital and promote cross-border e-commerce [2] - Guangzhou's 15th Five-Year Plan aims to deepen cooperation with Hong Kong in the horse racing industry and establish a horse racing economic circle [3] - Hong Kong's stock market is projected to lead global IPO financing in 2025, with a total of HKD 274.6 billion raised from 106 companies [4] Group 2 - The "Qwen-Image-Layered" model launched by Alibaba allows for independent manipulation of image layers, enhancing digital content creation [7] - The "Qing Tian Rent" platform for robot leasing has been launched, covering over 50 cities and aiming to expand to 200 cities by 2026 [8] - BYD confirmed salary increases for technical research staff, with adjustments based on performance and contributions [9] Group 3 - The first prototype of the new car brand "Yijing" by Dongfeng and Huawei has been completed, with plans for mass production in 2026 [10] - Porsche will gradually shut down its self-built charging stations by March 2026, totaling around 200 stations [11] - Huawei's HarmonyOS has surpassed 32 million devices, marking it as the fastest-growing operating system in smart terminals [12] Group 4 - OpenAI's computing profit margin has reportedly increased to 70%, significantly higher than previous years [13] - Kakao is in talks to sell its portal site Daum to an AI startup, potentially through a share swap [13] - Baidu's autonomous driving service "Luo Bo Kua" plans to launch testing and services in London in 2026 [13] Group 5 - A major PC manufacturer is negotiating supply agreements with leading memory chip makers to address rising prices in the memory chip market [14] - Samsung is developing a foldable phone to compete with Apple's upcoming iPhone Fold [15] - Samsung Biologics is set to acquire GSK's human genome sciences company for approximately USD 280 million [15]

这种恶劣的会计舞弊——事实上也是刑事欺诈，曾经引发了美股市场的重大变革，其中最著名的就是 《萨班斯—奥克斯利法案》(Sarbanes-Oxley Act)。它使得美国上市公司中的赤裸造假在很大程度上成为 过去式。 通常来说，当一个会计性质的问题在华尔街成为一段时间内的热门话题时，对于股票市场而言绝对不是 一个好兆头。这就是为什么，近期围绕美国科技巨头们AI算力基础设施"折旧年限"安排与计划的相关热 门讨论，应当让那些深度沉醉于AI投资热潮的投资者们在迈向2026年之际保持警惕。 一般来说，金融市场上的由那些编制公司财务报表的人所争论的事项过于晦涩——而且坦率地说，也过 于乏味，因此在本世纪初期以前几乎没有引起股票投资者们的积极探索兴趣。 然而，自本世纪初期以来，会计造假问题在安然(Enron)、世通(WorldCom)以及阿德尔菲亚通信公司 (Adelphia Communications)等曾经在资本市场上红极一时的热门公司被揭露使用欺骗性会计做法之 后，"会计造假"这一长时间以来在资本市场沉积的词条时不时就能够登上新闻头条，且往往引起热议后 不久，股票市场可能迎来一波极速下坠。 这些公司迅速从看似辉煌的" ...

Core Viewpoint - NVIDIA currently holds a near-monopoly in the AI training and inference chip market, driven by advanced technology and an unmatched ecosystem, making it the highest-valued public company globally with a market capitalization of approximately $4.5 trillion as of November 2025, and a year-over-year revenue growth of about 62% in Q3 2025 [2]. Competitive Landscape - NVIDIA faces competition from traditional chip giants like AMD and Intel, as well as tech companies like Google and Amazon with their custom chips, and emerging players like Cerebras and Groq. However, none have significantly challenged NVIDIA's leadership position so far [2]. - The AI compute chip market has two main applications: training and inference, with training being the core bottleneck in the early and mid-stages of large model development [4][5]. Training Dominance - NVIDIA's dominance in training compute stems from advanced technology and a monopolistic ecosystem. The training of large models requires massive computational power, necessitating large-scale chip clusters and a comprehensive software system to connect engineers, chips, and models [6]. - Key requirements for training chips include single-chip performance, interconnect capabilities, and software ecosystem [6]. - NVIDIA excels in single-chip performance, but competitors like AMD are closing the gap. However, this alone does not threaten NVIDIA's lead in AI training [7]. - Interconnect capabilities are crucial for large model training, with NVIDIA's proprietary NVLink and NVSwitch enabling efficient interconnectivity at a scale of tens of thousands of chips, while competitors struggle to achieve similar scales [7]. Ecosystem Advantage - NVIDIA's ecosystem advantage is primarily software-based, with CUDA being a well-established programming platform that fosters a strong developer community and extensive resources, enhancing user stickiness [8][9]. - The ecosystem's network effects mean that as more developers engage with CUDA, its value increases, creating a significant barrier to entry for competitors [10]. Inference Market Dynamics - Inference requires significantly fewer chips than training, leading to reduced interconnect demands. Consequently, NVIDIA's ecosystem advantage is less pronounced in inference compared to training [12]. - Despite this, NVIDIA still holds over 70% of the inference market share due to its competitive performance, price, and development costs [13]. Challenges to NVIDIA - Competitors must overcome both technical and ecosystem challenges to compete with NVIDIA. If they cannot avoid ecosystem disadvantages, they must achieve significant technological advancements [15]. - In the U.S., challengers are focusing on custom AI chips (ASICs), with Google's TPU showing promising results. However, the ecological disadvantage remains a significant hurdle [16]. - In China, U.S. export restrictions on advanced chips have created a protected market, limiting NVIDIA's ecosystem influence and presenting opportunities for local chip manufacturers [17][18]. Strategic Considerations - The geopolitical landscape has led to a potential rise of strong domestic competitors in China, as developers begin to adapt to local ecosystems like CANN, despite initial challenges [19]. - The U.S. government's recent policy shift allowing NVIDIA to sell advanced chips to China under specific conditions reflects a recognition of the need to maintain NVIDIA's competitive edge while managing technological disparities [19]. - A balanced approach is necessary for China to foster its AI chip industry while allowing for essential imports to support core AI projects [19].