Core Insights - The article discusses the investment positions held by the analyst in various companies, indicating a bullish outlook on these stocks [1]. Group 1: Company Positions - The analyst has a beneficial long position in SPYI, JEPI, NVDA, GOOG, AMZN, and AVGO, either through stock ownership, options, or other derivatives [1].

英伟达表态强调，他们不会要求客户为未收到的产品付费。 如果您希望可以时常见面，欢迎标星收藏哦~ 据路透社报道，英伟达发言人1月13日表示，公司没要求中国客户预付H200芯片的费用。此前有 报道指，英伟达要求客户全额预付，因对中国政府是否批准出货存有疑虑，而这一支付结构实则 将财务风险转移给客户。 （来源 ：半导体芯闻综合 ） 点这里加关注，锁定更多原创内容 *免责声明：文章内容系作者个人观点，半导体芯闻转载仅为了传达一种不同的观点，不代表半导体芯闻对该 观点赞同或支持，如果有任何异议，欢迎联系我们。 推荐阅读 10万亿，投向半导体 芯片巨头，市值大跌 黄仁勋：HBM是个技术奇迹 Jim Keller：RISC-V一定会胜出 全球市值最高的10家芯片公司 喜欢我们的内容就点 "在看 " 分享给小伙伴哦~ 路透社8日曾引述消息人士透露，虽然英伟达的中国客户有时被要求支付预付款，但由于中国监 管部门对批准出货存在不确定性，该公司对H200芯片的付款要求更为严格。即要求中国客户全额 预付且无法取消、申请退款或调整配置，以对冲风险。 此外，美国对高端芯片出口态度反复。美国总统特朗普（Donald Trump，又译川普） ...

The chipmaker is one of the biggest success stories of the last decade.It's no secret that Nvidia (NVDA +0.04%) has been an incredible investment, especially during the artificial intelligence (AI) boom. The chipmaker's graphics processing units (GPUs) are in high demand from tech companies building out their data centers.Even with that in mind, the amount of money an early investor could've made in Nvidia is still hard to believe. How much a $1,000 Nvidia investment would've grownIf you'd invested $1,000 i ...

Investment Rating - The report maintains a "Buy" rating for several companies in the AI and computing sectors, including Weike Technology, Nengke Technology, Hehe Information, and Maixinlin [13]. Core Insights - The AI application sector is experiencing significant growth, highlighted by the successful IPO of MiniMax, which raised 5.54 billion HKD and achieved a market capitalization of 898 billion HKD on its first day of trading [6][45]. - Nvidia's new VeraRubin architecture has revolutionized computing power, achieving up to five times the performance in AI inference tasks compared to the previous Blackwell architecture, with a tenfold reduction in inference costs per token [5][34]. - MiroMind's MiroThinker1.5 model has demonstrated superior performance in international benchmarks, achieving significant cost efficiency and redefining the growth path for large models [4][24]. Summary by Sections Computing Power Dynamics - The report notes stable pricing in computing power leasing, with significant advancements from MiroMind's MiroThinker1.5 model, which features 30B and 235B parameter variants that excel in benchmark tests [4][18]. - The token consumption for the week of January 5 to January 11, 2026, reached 6.43 trillion, marking a 15.44% increase from the previous week [18][19]. AI Application Dynamics - NotionAI's weekly traffic increased by 25.06%, indicating strong user engagement in the AI application space [32]. - The report highlights the performance of Nvidia's VeraRubin architecture, which integrates CPU, GPU, and networking components for optimized AI computing, significantly enhancing training and inference capabilities [5][34]. AI Financing Trends - MiniMax's IPO is noted as the largest for an AI model company globally, with a remarkable oversubscription rate of 1837 times for public offerings, reflecting strong investor confidence [6][45]. - The company has successfully completed multiple funding rounds, raising a total of 1.5 billion USD from 30 institutional investors over four years [46][47]. Investment Recommendations - The report suggests focusing on companies like Maixinlin, Weike Technology, Hehe Information, and Nengke Technology, which are positioned to benefit from the expanding AI and computing markets [10][58]. - MiniMax's successful market entry is seen as a significant indicator of the AI application sector's commercial viability and growth potential [57].

1、穿戴/IoT：AI眼镜、摄像头耳机依旧为穿戴设备关注焦点，各类新型IoT品类融入AI。 4、PC/手机：联想推出跨多端超级智能体，芯片企业迭代端侧芯片。 1）智能眼镜：今年热度不减，超50家企业参展且中国大陆企业是主力，外观美化、轻量化、全天佩 戴、多模态交互、多芯方案等是升级方向，同时也有新品聚焦运动、视听障解决等细分领域。2）耳 机：本届CES可看到耳机产品的创新重点由单一音频性能升级，转向音质+AI+多模态的综合能力演 进，AI能力深度嵌入耳机形态，部分产品展示集成摄像头、环境感知与多麦克风阵列的创新新品，伴 随上半年苹果AI摄像头耳机推出，其他品牌也有望跟进。3）新型IoT：智能影像设备、3D打印机、 NAS等品类关注度提升，越来越多的创业公司开始进入相关赛道，此外AI家居、AI录音卡、AI显示器 等亦看到创意新品推出。 2、汽车：AI驱动汽车全链路智能化升级，高阶自动驾驶有望迎来规模化落地。 芯片厂商中，英伟达发布Alpamayo系列开源AI模型，打造开放模型、仿真框架与数据集一体的生态系 统，有望加速技术渗透及自动驾驶行业商业化落地。高通与谷歌持续深入合作，并与零跑打造双骁龙 8797域控平台 ...

Group 1 - The core viewpoint of the report is that NVIDIA's new AI chip architecture, NVIDIA Vera Rubin, represents a comprehensive rethinking of system architecture, addressing the exponential growth in AI computing demands and redefining storage stack requirements [1][2][3] - NVIDIA's Vera Rubin platform includes six new chips designed to enhance system communication bandwidth, achieving a bandwidth that is twice that of the global internet total bandwidth, thus overcoming traditional data transfer bottlenecks [1][3] - The introduction of BlueField-4DPU allows for the management of a shared, persistent, high-speed context memory pool of up to 150TB, directly connected to GPUs, enabling dynamic allocation of up to 16TB of dedicated context space per GPU [2][3] Group 2 - The demand for NAND storage is projected to increase significantly, with an estimated 161EB needed by 2025, which would account for approximately 16% of the global NAND demand and 54% of enterprise SSD demand [4] - The Vera Rubin architecture allows for training a next-generation model with 100 trillion parameters using only a quarter of the cluster size required by the previous Blackwell system, greatly accelerating the research-to-product iteration cycle [3][4] - The AI computing throughput of a Vera Rubin data center is expected to be about 100 times that of a data center based on the Hopper architecture, significantly reducing the token generation cost for large-scale AI services to about one-tenth of the current level [3]

Core Insights - The narrative around the AI industry is undergoing significant scrutiny as massive capital expenditures collide with stagnant revenue growth, raising concerns about a potential "bubble" [1] - There is a growing gap between substantial investments in AI and the actual commercial returns, leading to a shift in focus from technological optimism to financial pragmatism [2] Group 1: Investment and Market Performance - In the U.S. market, NVIDIA's stock has reached new highs, reflecting investor enthusiasm for its AI chip business, while companies like Microsoft, Google, and Meta show structural differences in stock performance [1] - In China, Alibaba's stock has hit multi-year highs, with Tencent and Baidu also showing active performance in AI-related stocks, indicating ongoing market interest in domestic AI applications and infrastructure [1] - Despite high valuations in the global capital markets for the AI industry, concerns about the sustainability of these valuations are becoming a focal point of discussion [1] Group 2: Profitability Challenges in ToB AI - The global enterprise AI market is experiencing an asymmetric cycle of investment and profitability, with major players like Amazon and Google facing challenges as they expand [3] - Amazon's AWS is projected to have a capital expenditure of $125 billion in 2025, primarily for AI data center expansion, but its profit margins are under pressure due to rising operational costs [4][6] - AWS's revenue and operating income showed signs of recovery in Q3 2025, but profitability remains sensitive to capital expenditure and customer purchasing cycles [7] Group 3: Google Cloud's Growth and Challenges - Google Cloud has positioned AI at the core of its growth strategy, achieving significant revenue growth, but concerns about the mismatch between capital expenditure and returns persist [8][10] - Despite high ROI cases reported, the majority of AI projects struggle to achieve measurable returns, with only 25% of enterprise AI projects meeting initial ROI goals [14][15] Group 4: ToC AI Market Dynamics - The consumer AI segment faces challenges in converting user growth into revenue, with only 5% of AI projects yielding measurable benefits [16] - OpenAI's ChatGPT is projected to have annual revenue exceeding $20 billion in 2025, but its operational costs are rising exponentially, leading to significant losses [17] - The user base for ChatGPT has grown rapidly, but the conversion rate to paid subscriptions remains low, highlighting a disconnect between user acquisition and monetization [20][23] Group 5: Commercialization and Long-term Perspectives - The current investment-return imbalance in AI is seen as a phase rather than a failure of technology, with the potential for long-term value creation through efficiency improvements across industries [25][26] - The AI industry's commercial path is expected to follow a "J-curve," indicating that current losses are part of a necessary accumulation phase before significant returns can be realized [26][27] - The ongoing challenges in both ToB and ToC segments are contributing to the narrative of an "AI bubble," but the long-term potential of AI technology remains intact [27][28]

智东西1月13日报道，今日凌晨，谷歌与苹果发布联合声明，双方就AI服务达成多年深度合作——苹果要依靠谷歌Gemini和云技术来构建苹果的基础模 型。原本在操作系统大战的两大巨头，在AI时代意外地走向融合。 ▲谷歌与苹果发布联合声明（图源：社交平台X） 据外媒CNBC从苹果获取的一份声明称："经过仔细评估，我们认为谷歌的技术能为苹果基础模型提供最强大的基础，我们很高兴它将为我们的用户带来 创新的新体验。" 消息一经发布，马斯克跳出来在社交平台X直言："考虑到谷歌旗下还拥有安卓和Chrome浏览器，这种权力集中似乎有些不合理。" 从今天开始，iPhone的"大脑"，即将由谷歌来部分定义。 ▲马斯克对此事件的评论（图源：社交平台X） 对于这场世纪牵手，广大网友也各执一词。有网友认为"（合作）这是正确的举措"，但依然发出犀利的提问："如果他们是对Gemini模型的微调，还能叫 苹果基础模型吗？"有人直指："这真是对那些吹捧iOS比安卓更好的失败者们的漂亮反击。" 鉴于此前苹果已与OpenAI展开了合作，于是有网友猜测其与谷歌合作的主要原因可能是"意识到OpenAI即将推出的消费级AI设备将与iPhone展开竞争。" ...

1月13日，科技和算力硬件板块午后继续下探，相关热门ETF回调吸引资金积极布局。截止14点15 分，创业板人工智能ETF华夏（159381）下跌2.81%，换手率24.77%，盘中成交4.27亿元；通信ETF华 夏（515050）调整下跌2.69%，当日成交达3.91亿元；云计算ETF华夏（516630）跌幅扩大至1.80%。 消息面上，近期英伟达展示了Vera Rubin AI超级计算机平台，并宣布该产品即将量产。该平台涵 盖Vera CPU、Rubin GPU等6款新型芯片。凭借跨芯片极致协同设计，其不仅可将单Token推理成本降低 1/10，还能把混合专家（MoE）模型训练所需的GPU数量缩减至1/4。 【免责声明】本文仅代表作者本人观点，与和讯网无关。和讯网站对文中陈述、观点判断保持中立，不对所包含内容 的准确性、可靠性或完整性提供任何明示或暗示的保证。请读者仅作参考，并请自行承担全部责任。邮箱： news_center@staff.hexun.com 通信ETF华夏（515050）跟踪中证5G通信主题指数。深度聚焦英伟达、苹果、华为产业链。前五大 持仓股：中际旭创、新易盛、立讯精密、工业富联、兆易创 ...

Core Insights - Nvidia plans to collaborate with Eli Lilly to invest $1 billion in a joint AI lab aimed at transforming the healthcare sector through advanced AI technologies [3][25] - The focus of the collaboration is to address the global shortage of healthcare professionals by deploying AI agents in the medical field, with a significant emphasis on the rapid adoption of AI in healthcare compared to other industries [5][12] - Nvidia's CEO highlighted the importance of physical AI and its impact on the pharmaceutical industry, with advancements in AI models and robotics enhancing laboratory automation and drug development processes [6][10] Group 1: Collaboration and Investment - Nvidia and Eli Lilly will establish a joint AI lab with a $1 billion investment to integrate top scientists and AI researchers [3][25] - The partnership aims to accelerate drug discovery and laboratory automation, shifting the current model from 90% wet lab work to a more balanced approach with increased computational methods [25][29] Group 2: AI in Healthcare - The healthcare sector is experiencing unprecedented speed in the deployment of technology, with AI expected to play a crucial role in addressing the projected shortage of millions of healthcare workers by 2030 [12][11] - Nvidia's AI models and tools are being utilized to enhance clinical workflows, allowing healthcare professionals to save significant time and improve patient care [13][31] Group 3: Technological Advancements - Nvidia's advancements in AI, such as the Cosmos model and Isaac robotics platform, are designed to improve laboratory efficiency and quality control in drug manufacturing [6][19] - The company is also focusing on open-source models and tools to democratize access to AI technologies, enabling a wider range of companies to innovate in the healthcare space [9][22] Group 4: Future Outlook - The emergence of AI scientists and agents is expected to revolutionize the pharmaceutical industry, with a projected $300 billion market for drug development being reshaped by these technologies [18][25] - Nvidia's collaboration with Eli Lilly is seen as a pivotal moment in the integration of AI into scientific research, potentially leading to breakthroughs in drug discovery and development [25][28]