Group 1: Core Insights - The global AI industry is experiencing a dual iteration of computing power models, leading to the commercialization of AI applications such as ChatGPT Health, with significant advancements in AI-assisted healthcare and humanoid robots [2][6] - AI chip companies are launching next-generation platforms to enhance computing power support, with NVIDIA introducing the Vera Rubin platform and several collaborative design chips, thereby reducing the cost threshold for enterprises to operate large models [3][5] - Overseas companies are accelerating the commercialization of large AI models through substantial financing, while domestic firms are exploring market opportunities via open-source tools and engineering innovations [4][6] Group 2: Key Events - On January 6, AMD unveiled a comprehensive AI chip covering data centers, AI PCs, and embedded edge applications, with plans for a 2nm process MI500 series to be launched in 2027 [5] - On January 7, xAI announced it had exceeded $20 billion in Series E funding, significantly surpassing market expectations, with funds allocated for GPU cluster expansion and Grok 5 model training [5] - OpenAI launched "ChatGPT Health" on January 7, which integrates user health information with electronic medical records, tapping into a projected global AI healthcare market expected to reach approximately $505.59 billion by 2033 [5][6] Group 3: Industry Trends - The AI healthcare sector is entering a commercialization acceleration phase, with companies like OpenAI and Ant Group's AI medical app making significant strides in personalized consultation services [6] - In the humanoid robotics sector, collaborations such as DeepMind with Boston Dynamics are integrating advanced models into new generation humanoid robots, showcasing capabilities for various applications [6] - The report highlights a noticeable market trend towards higher elasticity in technology growth styles, with funds being preemptively allocated to capitalize on potential spring market movements [7] Group 4: Recommended Companies - The report recommends companies such as Ding Tai Gao Ke, which is experiencing high growth driven by AI PCB demand [8] - It also highlights Zhi Pu as a new AI player in the Hong Kong market, focusing on model iteration and ecosystem development [8] - MINIMAX-WP is noted as a benchmark for AI expansion overseas, with a multi-modal layout for future growth [8]

2026 年 01 月 12 日 其 他 研 究 开源晨会 0112 晨会纪要 ——晨会纪要 数据来源：聚源 -20% 0% 20% 40% 60% 80% 2025-01 2025-05 2025-09 沪深300 创业板指 昨日涨跌幅前五行业 | 行业名称 | 涨跌幅(%) | | --- | --- | | 传媒 | 5.315 | | 综合 | 3.600 | | 国防军工 | 3.290 | | 计算机 | 2.901 | | 有色金属 | 2.777 | | 数据来源：聚源 | | 昨日涨跌幅后五行业 | 行业名称 | 涨跌幅(%) | | --- | --- | | 银行 | -0.436 | | 非银金融 | -0.199 | | 建筑材料 | 0.011 | | 交通运输 | 0.034 | | 农林牧渔 | 0.342 | | 数据来源：聚源 | | 吴梦迪（分析师） wumengdi@kysec.cn 证书编号：S0790521070001 观点精粹 总量视角 【宏观经济】美联储或继续观望降息效果——美国 12 月非农就业数据点评 -20260110 【宏观经济】PPI 环比创 2024 ...

Investment Rating - The report maintains a "Buy" rating for key companies in the liquid cooling industry, including Zhongji Xuchuang, Xinyi Sheng, and Yingweike, among others [10]. Core Insights - The liquid cooling industry is transitioning from a phase driven by expectations to one focused on performance realization, marked by the mass production of NVIDIA's GB300 and the upcoming Vera Rubin platform [1][19]. - The market is expected to see a significant shift as high-power cabinets (100kW+) become the norm, with major companies like AWS and Meta adopting liquid cooling solutions for their self-developed ASICs starting in 2026 [2][20]. - The competitive landscape is evolving from component-level competition to a focus on comprehensive system capabilities, emphasizing the importance of integrated thermal management systems [3][21]. Summary by Sections Investment Strategy - The report suggests focusing on the computing power sector, particularly in optical communication and liquid cooling, highlighting companies like Zhongji Xuchuang and Yingweike as key players [24][13]. Industry Trends - The liquid cooling industry is entering a second development phase characterized by confirmed orders and capacity realization, with a strong emphasis on system integration and operational capabilities [6][22]. - The competitive focus has shifted to complete thermal management systems, increasing customer reliance on solution providers [3][21]. Key Companies and Recommendations - Recommended companies include Zhongji Xuchuang, Xinyi Sheng, and Yingweike, which are positioned to benefit from the industry's growth and the shift towards liquid cooling solutions [10][24]. - The report also highlights the importance of upstream and downstream partnerships within the liquid cooling supply chain, indicating a trend towards comprehensive solutions rather than standalone components [23][24].

Investment Rating - The investment rating for NVIDIA is "Outperform" [5] Core Insights - Demand remains strong, with NVIDIA's revenue for FY26Q3 reaching $57.006 billion, a year-over-year increase of 62% and a quarter-over-quarter increase of 22% [1][9] - The company expects revenue guidance for FY26Q4 to be $65 billion, reflecting a significant increase from the previous quarter [1][24] - The introduction of the GB300 product has driven a 56% year-over-year growth in computing business, with GB300 now accounting for over two-thirds of Blackwell's total revenue [2][12] - The Rubin platform is set to begin mass production in H2 2026, promising significant performance improvements [2][12] - NVIDIA has established new partnerships, including one with Anthropic, which will utilize NVIDIA's technology for a substantial computing capacity [2][12] Financial Performance - For FY26Q3, NVIDIA reported a GAAP gross margin of 73.4%, with a net profit of $31.9 billion, reflecting a 65% year-over-year increase [1][9] - Revenue from the data center segment was $51.2 billion, up 66% year-over-year, while gaming revenue was $4.3 billion, up 30% year-over-year [1][12][13] - The network business saw revenue of $8.2 billion, a remarkable 162% increase year-over-year, driven by the successful application of NVLink technology [2][11] Financial Projections - Revenue projections for FY2026-2028 have been raised to $213 billion, $334 billion, and $428 billion, respectively, with net profit estimates adjusted to $114 billion, $188 billion, and $235 billion [3] - The expected EPS for FY2026 is $7.72, with a projected P/E ratio of 23 [4][27] - The company anticipates maintaining a gross margin of around 75% through ongoing cost optimization and product structure adjustments [24][27]

Group 1: Nvidia's Strategic Moves - Nvidia's investment of $100 billion in OpenAI is designed to secure long-term orders from its largest customer, while OpenAI gains essential funding and technical support for next-generation AI infrastructure [3][5] - The partnership allows for joint optimization of hardware and software roadmaps, creating a significant technological barrier against competitors [5] - Nvidia's upcoming Vera Rubin platform is expected to provide 8 exaFLOPS of AI computing power, significantly enhancing OpenAI's model evolution when deployed in late 2026 [5][6] Group 2: Oracle's Emergence in AI Infrastructure - Oracle's $300 billion cloud services contract with OpenAI positions it as a key player in AI infrastructure, with remaining performance obligations (RPO) surging to $455 billion [7][9] - The shift in OpenAI's exclusive partnership with Microsoft opened opportunities for Oracle, which offers a full-stack service from data center construction to cloud platform operation [7] - Oracle's involvement in the "Stargate" project, despite challenges, aims to establish critical data centers that will enhance OpenAI's computational network [9] Group 3: OpenAI's Strategic Positioning - OpenAI's strategy focuses on balancing AI research, product development, and infrastructure challenges, ensuring sufficient support while maintaining technological autonomy [10][12] - The multi-vendor strategy allows OpenAI to secure chip supply from Nvidia, cloud infrastructure from Oracle, and maintain flexibility with Microsoft, enhancing its negotiating power [12] - OpenAI's commitment to AGI control and its unique governance structure aim to ensure that decisions benefit humanity while attracting significant investments [12][13] Group 4: Industry Challenges and Opportunities - The global AI infrastructure spending is projected to reach $3-4 trillion by the end of the decade, presenting both opportunities and challenges related to energy supply and geopolitical factors [14][16] - Energy consumption is a critical bottleneck, with data centers expected to consume 945 terawatt-hours by 2030, prompting a shift towards renewable energy sources [16] - Geopolitical dynamics are influencing infrastructure strategies, with the U.S. aiming to maintain its dominance in AI chips and data centers, leading to increased competition for technological sovereignty [17] Group 5: Future Implications of AI Infrastructure - The ongoing competition among Nvidia, Oracle, and OpenAI is reshaping the foundational aspects of future civilization, with control over AI infrastructure becoming a key determinant of economic power [18][19] - The need for sustainable development models is emphasized as energy demands rise, and the concentration of computational resources among a few tech giants raises concerns about equity and accessibility [18][19]

Core Viewpoint - Nvidia and OpenAI have announced a strategic partnership and a significant investment of up to $100 billion to support OpenAI's AI data center plans [2]. Group 1: Investment Details - The investment will be paid to OpenAI gradually as the deployment of GPUs increases [4]. - This investment represents approximately 2.2% of Nvidia's current market capitalization of about $4.46 trillion [5]. Group 2: Infrastructure and Energy Consumption - OpenAI plans to utilize millions of Nvidia GPU systems to deploy AI data centers, with an energy consumption target of at least 10 gigawatts [7]. - The first phase of the data center will have an energy consumption of 1 gigawatt and is expected to be deployed in the second half of 2026 [9]. Group 3: Strategic Partnership - OpenAI will be the first "beta user" of Nvidia's DGX supercomputer system, highlighting a decade-long collaboration between the two companies [10]. - OpenAI will receive priority in GPU delivery, while Nvidia will benefit from OpenAI's highest priority in external collaborations [11]. - OpenAI will become the preferred "computing" and "network" strategic partner in Nvidia's AI factory growth plan, ensuring optimal performance for OpenAI's models and infrastructure software [12]. - Both companies plan to finalize the specific details of their strategic partnership in the coming weeks [13].

Core Insights - OpenAI plans to build and deploy a 10 GW Nvidia system, equivalent to approximately 4 to 5 million GPUs, matching Nvidia's total shipments for the year and doubling last year's output [3][5][12] - Nvidia and OpenAI announced a strategic partnership with an investment of up to $100 billion to support OpenAI's AI data center plans [5][12] Investment and Financials - The partnership will be implemented in phases, starting with a 1 GW data center to be deployed in the second half of 2026, with an initial investment of $10 billion from Nvidia upon completion of the first system [7][14] - Building a 1 GW data center is estimated to cost between $50 billion and $60 billion, with about $35 billion allocated for Nvidia's chips and systems, indicating a significant share for Nvidia in OpenAI's infrastructure [14][17] - OpenAI's revenue is projected to reach $13 billion this year, a more than threefold increase from $4 billion last year, with a revised forecast for 2030 revenue exceeding $200 billion [17][18] Market Position and Competition - The collaboration secures Nvidia a strategic customer in OpenAI, enhancing its position in the AI chip market amid competition from AMD and cloud service providers [14][18] - OpenAI's R&D costs are expected to account for nearly 50% of its total revenue by 2030, significantly higher than the 10% to 20% range typical for other tech giants [17][18] Future Outlook - The partnership aims to accelerate the development of OpenAI's next-generation AI infrastructure, with expectations for significant outcomes in the coming months [12][18] - The AI infrastructure arms race has entered a new phase with investments reaching the billion-dollar mark, indicating a growing demand for computational resources [18]