Investment Rating - The report maintains a "Recommended" investment rating for the computer industry [2][22]. Core Insights - The upcoming NVIDIA GTC 2025 conference is expected to catalyze interest in areas such as agent-based AI, robotics, and accelerated computing, with a focus on domestic AI technology [4][16]. - The report highlights the increasing attention on domestic AI industries following the introduction of China AI Day at the NVIDIA conference, which aims to enhance the influence of domestic AI in various sectors [4][16]. - The report emphasizes the optimistic capital expenditure outlook for major domestic companies, predicting a significant increase in inference computing power, which is directly linked to AI applications [20][22]. Summary by Sections Recent Market Performance - From March 10 to March 14, 2025, the Shenwan Computer Index declined by 1.36%, with notable gainers including Zhisheng Information and Hongquan Internet, while losers included Yonyou Network and Deepin Technology [9]. Industry News - Baidu released its Wenxin large model 4.5 and X1, introducing new capabilities for advanced search and AI drawing, with pricing set for API usage [14]. - OpenAI launched new tools to simplify the development of intelligent agents, indicating a trend towards more accessible AI development [14]. Key Company Announcements - Daotong Technology expects a net profit of 180 to 200 million yuan for Q1 2025, marking a year-on-year growth of 44.29% to 60.32% [15]. Investment Recommendations - The report suggests focusing on domestic cloud computing companies such as Inspur Information and Yunsai Zhili, as well as AI application firms like Yonyou Network and Dingjie Zhizhi, and quantum technology companies like Guodun Quantum [22].

Core Viewpoint - Nvidia is expected to unveil significant advancements in AI hardware, including the Blackwell Ultra chip and details about the Rubin platform, at the upcoming GTC 2025 conference, which may help revive market sentiment towards AI stocks [1][2]. Group 1: Blackwell Ultra Chip - The Blackwell Ultra (GB300) chip is anticipated to be a highlight of the GTC conference, featuring improvements in HBM memory capacity and power consumption compared to its predecessor B200 [3]. - The changes in the Blackwell Ultra system are expected to benefit suppliers in power, battery, cooling, connectors, ODM, and HBM sectors [3]. Group 2: Rubin Platform - The Rubin platform is projected to be a new engine for AI computing by 2026, with Nvidia likely to share some details at the GTC conference [4]. - The Rubin GPU is expected to have a massive HBM capacity of 288GB, a thermal design power (TDP) of 1.4kW, and a 50% performance increase in FP4 computing compared to B200, with shipments starting in Q3 2025 [4][5]. - The Rubin platform may feature a dual logic chip structure, HBM4 memory with a total capacity of 384GB, and an expected TDP of around 1.8kW [5]. Group 3: CPO Technology - Nvidia's CPO (Co-Packaged Optics) technology is anticipated to be another major highlight at the GTC conference, aimed at enhancing bandwidth, reducing latency, and lowering power consumption [6][7]. - Initial applications of CPO are expected in switches, with widespread GPU-level adoption projected for the Rubin Ultra era in 2027 [8]. Group 4: Physical AI and Humanoid Robots - There is an increasing market focus on physical AI and humanoid robots, with Nvidia expected to showcase advancements in these areas at the GTC conference [9]. - Nvidia has already introduced platforms like Cosmos and GR00T, and further announcements regarding multimodal AI, robotics, and digital twins are anticipated [9][10].

Core Viewpoint - The article discusses the underlying logic behind the rise of robotics, emphasizing that the three key elements of AGI (Artificial General Intelligence) are computing power, algorithms, and data, with current robotics representing the data aspect [2][3]. Group 1: Development of Robotics - The development of large models faced challenges last year due to the exhaustion of available data on the internet, leading to a need for new data sources [3]. - Robotics can be viewed as a core component of AIDC (Artificial Intelligence Data Center), similar to GPUs and other capital expenditures in AI models [4]. - The anticipated deployment of 1 million robots globally by 2027-2028 could represent a capital expenditure of 500 billion to 1 trillion [4]. Group 2: Market Dynamics and Investment Opportunities - The current market perception of robotics is skewed, with many believing that robots are far from being able to serve humans, while they are actually crucial for data collection in AI development [4]. - The article suggests that the robotics sector is currently dominated by a small number of institutional investors, indicating a potential for significant growth if the sector gains broader acceptance [5]. - The ongoing "bull market" is attributed to a shift of global capital from US stocks to emerging markets, particularly Hong Kong and A-shares, which are closely following the trends in technology sectors [8]. Group 3: Challenges and Risks - There are several risks identified in the robotics sector, including the significant decline in major players' stock prices and the skepticism surrounding new entrants in the market [5]. - The article highlights the contradiction between strong expectations for AI implementation and the actual challenges faced in achieving these goals [7]. - Concerns are raised about the reliance on foreign capital and the potential volatility in the A-share market if foreign investors withdraw [8].

Core Viewpoint - Goldman Sachs identifies Physical AI as a significant emerging trend, emphasizing its applications in autonomous driving, AI equipment, and robotic automation [2][8]. Group 1: Definition of Physical AI - Physical AI, also known as generative physical AI, enables autonomous machines to perceive, understand, and execute complex operations in the real physical world [4]. - It extends traditional generative AI by allowing machines to comprehend spatial relationships and physical behaviors, resulting in more realistic outputs that adhere to physical laws [5]. Group 2: Autonomous Driving - Goldman Sachs highlights key players in the autonomous driving sector, including Uber, Pony.ai, BYD, Li Auto, Xiaomi, and Baidu [9]. - Uber is collaborating with Waymo to launch autonomous ride-hailing services in Austin and Atlanta by 2025, with expectations of a human-machine hybrid model in the future [9]. - Pony.ai is projected to achieve a 27% compound annual growth rate from 2024 to 2027, with profitability expected by 2030 [9][10]. Group 3: AI Equipment - In the AI equipment sector, Goldman Sachs favors companies such as Horizon Robotics, Mobileye Global, AAC Technologies, and Quanta Computer [12]. - Horizon Robotics is recognized as a leader in the ADAS/AV field in China and a key supplier for BYD [12]. - Mobileye is expected to gain a larger market share among Western OEMs due to its leadership in the ADAS sector [12]. Group 4: Robotics and Automation - Goldman Sachs focuses on companies like Harmonic Drive Systems, Yaskawa Electric, Sanhua Intelligent Controls, and Shenzhen Inovance Technology in the robotics and automation space [14]. - Harmonic Drive Systems leads the small precision gearbox market, widely used in humanoid robots [14]. - Yaskawa Electric is enhancing automation levels with its dual-arm robot, MOTOMAN NEXT [14]. Group 5: Infrastructure and Support - The development of AI relies on robust infrastructure, with Goldman Sachs favoring companies such as Belden, Flex, Jabil Circuit, TE Connectivity, Amphenol, Dassault Systemes, Prysmian, and Legrand [16]. - These companies play critical roles in data centers, power, cabling, and industrial automation, providing essential support for AI operations [16].