格隆汇1月2日 | 入选逻辑：英伟达不仅是AI时代的"卖铲人",更是定义AI计算标准的"总设计师";拥 有"CUDA软件+GPU硬件+Networking网络"的软硬一体化护城河，难以被逾越；受益于全球云巨头资本 开支(CapEx)指数级增长及Blackwell/Rubin新平台的选代。 H 哈隆汇 - DEALER TO NVDA) 核心入选逻辑 历史地位:如同PC时代的英特尔、移动时代的苹果,Al时代属于英伟达 缩放定律(Scaling Laws):预训练、后训练和推理的算力需求持续验证"良性循环" (算力普及->模型更强->应用落地->更多算力) 基建规模:CEO黄仁勋预测,到2030年全球AI基础设施年建设规模将达3-4万亿美元 "军备竞赛" 五大云厂商 总设计师地位:英伟达不仅是Al时代的"卖铲人",更是定义Al计算标准的"总设计师" 生态壁垒:拥有"CUDA软件+GPU硬件+Networking网络"的软硬一体化护城河,难以被逾越 业绩确定性:受益于全球云巨头资本开支(CapEx)指数级增长及Blackwell/Rubin新平台的迭代 2025年五大云厂商 (微软、谷歌、Meta、亚马逊、甲骨文) ...

Core Insights - Nvidia is aggressively expanding its influence in the AI sector through strategic acquisitions and investments, including a $20 billion licensing agreement with Groq, which allows Nvidia to integrate Groq's core team and technology while Groq maintains operational independence [1][3][5] - The acquisition of Groq is seen as a strategic defense and capability enhancement, as Groq's LPU architecture poses a significant threat to Nvidia's dominance in AI inference markets [5][6] - Nvidia's investments in companies like Intel and Nokia, along with its commitment to OpenAI, illustrate a comprehensive strategy to control key nodes in the AI computing value chain [10][13][17] Group 1: Strategic Acquisitions - The $20 billion deal with Groq not only secures key technology but also eliminates a major competitor in the AI inference space [3][5] - Nvidia's investment in Synopsys for $2 billion aims to embed its accelerated computing capabilities into future chip design tools, shortening design cycles across various applications [10][12] - The $5 billion investment in Intel is intended to create a strategic alliance, allowing Nvidia to integrate its GPU technology into Intel's next-generation chips [13][15] Group 2: Financial Strength and Investment Strategy - Nvidia's cash reserves have surged to $606 billion, a 4.5-fold increase from early 2023, enabling significant strategic investments [24] - The company is expected to generate $968.5 billion in free cash flow in 2025, with total cash flow over the next three years potentially exceeding $5.76 trillion [24] - Nvidia prioritizes strategic investments over stock buybacks, viewing them as essential for building competitive barriers and securing key partnerships [24] Group 3: Long-term Vision and Ecosystem Development - Nvidia's investment strategy is designed to create a comprehensive network across the AI industry, ensuring that its hardware and software are integral to future AI applications [18][19] - The company is focusing on high-potential areas such as autonomous driving, robotics, and fusion energy, aiming to embed its standards and software ecosystem in these sectors [21][22] - Nvidia's approach reflects a shift from open ecosystems to internal capabilities that can be controlled and accumulated over time [8][18]

Group 1 - Nvidia has acquired AI software company SchedMD, highlighting its increased investment in open-source technology and the AI ecosystem to address growing competition [1] - SchedMD's core technology, Slurm, is open-source software that assists in scheduling large-scale computing tasks, which significantly occupy data center server capacity [1] - Nvidia's proprietary CUDA software has become an industry standard, driving chip sales and emphasizing the importance of software in maintaining its dominance in the AI field [2] Group 2 - Nvidia has launched the third generation of its "Nemotron" large language model, which boasts faster computation speeds, lower costs, and higher intelligence compared to previous versions, covering various fields such as physical simulation and autonomous driving [2] - The trend in the tech industry is shifting towards open-source AI models, with Nvidia becoming a significant supplier by releasing new models and providing training data and tools for enterprise users [4] - The rapid development of generative AI has led companies to explore key variables for the next decade, including self-developed chips and full-stack software control to accelerate their competitive edge [4] Group 3 - Companies like Weimi Hologram are advancing open-source full-stack AI technology by integrating hardware, software, and ecosystems, aiming to create a comprehensive capability from underlying architecture to industry applications [5] - Weimi Hologram is exploring low-power chips and edge computing solutions to lower the computational barriers for intelligent scenarios, supporting third-party model training through open computing resources [5] - The AI market is rapidly evolving, with a shift towards open-source AI model development, indicating a long-term market potential for various industry applications [6]

当潮水退去，才知道谁在裸泳。 出品 | 新行情 作者 | 松涛 来源：市场资讯 （来源：新行情） 今年10月，英伟达市值首次突破5万亿美元，规模超过了英、法、德等主要经济体的股市总值，也将市 场对AI算力的乐观情绪推至高潮。 然而高峰过后，形势急转直下。 短短一个多月内，英伟达市值连续经历数次大幅下跌，万亿市值蒸发，再次成为舆论焦点。 英伟达市值的剧烈波动，不仅仅是单只股票的涨跌，更反映了市场情绪的集体转变：资本从狂热追逐逐 渐转为冷静审视。 其中也透露出市场的担忧：天价芯片订单是否依赖脆弱的融资循环？激烈的竞争与国际环境波动，是否 在侵蚀其护城河？就连黄仁勋本人关于"未向OpenAI付款"的澄清，也被市场解读出了别样的信号。 一场关于"AI泡沫"的疑虑，正随着英伟达市值的剧烈波动而扩散。风暴尚未停息，它迫使整个行业在狂 飙突进之后，必须直面那些悬而未决的根本问题。 英伟达市值暴跌 12月18日，英伟达股价报收于170.94美元，当日下跌3.81%，市值在一夜之间蒸发1648亿美元（约合 1.16万亿人民币）。 | 170.940 " | 176.130 昨收 177.720 量比 1.29 | | | -- ...

智通财经APP获悉，英伟达(NVDA.US)周一宣布收购AI软件公司SchedMD。这家芯片巨头正通过加大 开源技术投入、强化AI生态布局，以应对日益激烈的行业竞争。 虽然英伟达凭借高性能芯片享誉业界，但其同样提供涵盖物理模拟、自动驾驶等多个领域的自有AI模 型，并将这些模型作为开源软件向研究机构和企业开放。其专有的CUDA软件已成为多数开发者的行业 标准，这正是英伟达芯片的核心卖点，软件实力也成为其维持AI行业领导地位的关键。 英伟达在官方博客中表示："支持最新英伟达硬件的Slurm系统已成为生成式AI关键基础设施的重要组成 部分，被基础模型开发者与AI构建者广泛用于管理模型训练和推理需求。" 值得一提的是，同日早些时候，英伟达发布了全新开源AI模型系列。面对中国AI实验室开源模型的竞 争浪潮，该公司称新系列模型较先前版本速度更快、成本更低且性能更智能。 据SchedMD官网信息显示，该公司由Slurm软件开发者Morris "Moe" Jette与Danny Auble于2010年在加利 福尼亚州利弗莫尔创立，目前拥有40名员工。其客户包括云基础设施公司CoreWeave(CRWV.US)与巴塞 罗那超级 ...

SchedMD提供的软件可帮助调度大型计算任务，这类任务往往会占用数据中心服务器容量的很大一部 分。该公司的Slurm开源技术允许开发者和企业免费使用，通过提供工程与维护支持服务盈利。 英伟达 凤凰网科技讯北京时间12月16日，据路透社报道，英伟达周一表示，已收购AI软件公司SchedMD。随 着竞争的加剧，英伟达正加倍押注开源技术，并加大对AI生态系统的投资以应对挑战。 虽然英伟达以开发高速芯片著称，但它也提供一系列自有AI模型，从物理模拟到自动驾驶汽车，并将 其作为开源软件供研究人员和公司使用。英伟达专有CUDA软件是大多数开发者采用的行业标准，也是 英伟达芯片的一大卖点，使得软件成为其维持在AI行业主导地位的关键。 这笔交易的财务条款未予披露。英伟达表示，将继续以开源方式分发SchedMD的软件。 在宣布这个收购消息并发布新开源（300109）AI模型后，英伟达股价上涨1.35%。(作者/箫雨) ...

Core Viewpoint - Nvidia is expected to maintain strong profitability and growth, with optimistic projections for future earnings and revenue growth, despite facing challenges in the Chinese market [4][8]. Financial Performance - Nvidia's adjusted EPS for the last quarter was $1.05, with total revenue of $46.74 billion, exceeding market expectations. For the upcoming quarter, adjusted EPS is projected to reach $1.25, a 19% quarter-over-quarter increase, while revenue is expected to be $54.8 billion, a 17% increase [1]. - Analysts predict a compound annual growth rate (CAGR) of 22.0% for EPS and 20.2% for revenue over the next five years, indicating more than double growth in both metrics [4]. - The projected profit margin is expected to expand, with the adjusted net profit margin increasing from 55.3% to 56.2% in the next quarter [1]. Growth and Profitability Projections - By January 2026, EPS is projected to be $4.54, with revenue at $207.33 billion and a profit margin of 53.98%. By January 2028, EPS is expected to reach $8.47, with revenue of $356.75 billion and a peak profit margin of 58.52% [5]. - The average net profit margin over the next five years is anticipated to be 57.0% [4]. Market Dynamics - Nvidia's market share in the Chinese AI chip market is projected to decline from 66% in 2024 to 54% in 2025, primarily due to the rise of domestic competitors and complexities in chip supply recovery [8]. - Domestic AI chip manufacturers, such as Huawei, are rapidly iterating their products, which may further pressure Nvidia's market position [9]. Competitive Landscape - The growth of domestic AI chips may impact Nvidia's pricing power, which has been strong due to its near-monopoly in high-performance AI chips. The increasing competition could lead to price pressures and a potential loss of market share [13]. - Analysts note that the Chinese market's scale provides local companies with opportunities to grow and develop their ecosystems, potentially leading to competition beyond China [13].

Core Insights - The article emphasizes Nvidia's pivotal role in the AI revolution, highlighting its rapid growth and strategic investments in various AI sectors since the emergence of ChatGPT [4][5]. - Nvidia's investment strategy is characterized by a broad approach, targeting multiple AI technologies and companies to secure its position as a foundational player in the AI ecosystem [10][24]. Investment Strategy - Nvidia has participated in 50 venture capital deals in 2025 alone, surpassing its total of 48 deals in 2024, indicating an aggressive investment pace [5]. - The company has made significant investments in OpenAI, totaling $100 billion, to develop large-scale AI infrastructure, showcasing its commitment to being a key player in AI development [6][7]. - Nvidia's strategy includes investing in competing AI firms, such as xAI, to diversify its technological bets rather than aligning with a single winner [7][10]. AI Ecosystem Development - Nvidia is building a comprehensive AI ecosystem by investing in companies across various sectors, including data centers, energy solutions, and foundational technologies [16][24]. - The company has invested in firms like Ns c a l e and Cr us oe, which focus on AI data centers, ensuring that Nvidia's GPUs remain integral to AI operations [12][13]. - Nvidia's investments in energy technologies, such as nuclear fusion, aim to address the significant energy demands of AI, positioning the company as a leader in sustainable AI infrastructure [14][15]. Application Areas - Nvidia's investments span multiple AI application areas, including autonomous driving, robotics, healthcare, and content creation, ensuring its technology is embedded across industries [18][22]. - The company has backed various startups in the autonomous driving sector, such as Wa yve and Nu r o, reflecting its long-term vision for AI applications in transportation [18][19]. - In the robotics field, Nvidia has invested in companies like Fi g u r e AI and Bri g ht Ma c h i n e s, indicating its focus on making AI chips the "brains" of robots [20][22]. Strategic Goals - Nvidia's overarching goal is to become the foundational infrastructure for the AI era, akin to how Microsoft and Google established their operating systems [24][25]. - The company aims to create a dependency on its GPUs across all AI companies, ensuring that its technology is essential for AI development and deployment [24]. - By investing in a wide array of AI applications, Nvidia seeks to secure its position as a dominant player in the evolving AI landscape, with a focus on long-term growth and influence [25].

Core Viewpoint - Nvidia has become the first publicly traded company in the world to surpass a market capitalization of $5 trillion, reflecting its dominant position in the AI sector and raising questions about whether this valuation represents a new benchmark or an "AI bubble" [1][6]. Group 1: Market Performance - Nvidia's stock price increased by 3% to $207.04, with a year-to-date gain exceeding 50% [1]. - The company's market capitalization reached $5.03 trillion, marking a significant milestone in its valuation history [1][6]. - Since the launch of ChatGPT in November 2022, Nvidia's stock has surged approximately 11 times, indicating strong investor confidence in its growth potential [6]. Group 2: Demand and Supply Dynamics - The surge in Nvidia's market value is attributed to the explosive global demand for AI, positioning Nvidia as a key supplier in the AI "arms race" [2]. - Nvidia's AI chips, particularly the H100, are in high demand, with companies needing to place orders months in advance due to supply constraints [2][3]. - Major cloud computing companies are projected to increase capital expenditures significantly, indicating sustained demand for Nvidia's products [3]. Group 3: Competitive Landscape - Nvidia's competitive advantage is bolstered by its CUDA software ecosystem, which creates a high barrier to entry for competitors like AMD and Intel [2]. - Despite losing its market share in China, Nvidia is still expected to find growth opportunities in other global markets [3][5]. - The company faces increasing competition from emerging players in the AI chip market, particularly from Chinese firms [7]. Group 4: Valuation Concerns - Analysts have mixed views on whether Nvidia's valuation is justified, with some suggesting that the AI bubble has not yet burst [6][7]. - Nvidia's current price-to-earnings ratio is approximately 33 times its expected earnings, compared to the S&P 500 average of about 24 times, raising concerns about its high valuation [7]. - The potential for challenges in AI commercialization and regulatory issues could impact Nvidia's future growth trajectory [7].

Core Insights - OpenAI and AMD announced a significant computing power infrastructure agreement, involving a total of 6 gigawatts of computing power, which could allow OpenAI to acquire approximately 10% of AMD's shares [1] - Analysts view this deal as a validation of AMD's AI roadmap, positioning the company favorably in the rapidly growing AI market [1] - Following the announcement, Jefferies raised AMD's target price from $170 to $300, while UBS increased it from $210 to $265, reflecting increased market confidence in AMD's future [1][2] Market Dynamics - The agreement between OpenAI and AMD is perceived as a threat to NVIDIA, with retail investor sentiment shifting from neutral to bearish regarding NVIDIA's stock [3] - Some investors predict NVIDIA's stock could drop to $150, a nearly 20% decline from its previous close, due to increased competition and challenges in the Asian market [3] - Despite concerns about NVIDIA's high valuation, analyst Ming-Chi Kuo suggests that as long as the overall AI computing power market grows, the impact of the OpenAI-AMD partnership on NVIDIA should be limited [3] Competitive Landscape - OpenAI's CEO, Sam Altman, reassured that the partnership with AMD is intended to complement existing collaborations with NVIDIA, which includes a separate 10-gigawatt computing power agreement [4] - The deal grants OpenAI warrants that could influence AMD's strategic decisions, contrasting with NVIDIA's relationship where OpenAI is merely a customer [4]