Market Performance - The Shanghai Composite Index rose by 0.33% to 4136.16 points, while the Shenzhen Component increased by 0.79% and the ChiNext Index gained 0.63%[1] - The Hang Seng Index closed up 0.45% at 26749.51 points, with the Hang Seng Tech Index rising 0.62% and the Hang Seng China Enterprises Index increasing by 0.51%[1] - The total market turnover in Hong Kong was 240.9 billion HKD[1] Currency and Trade Tensions - The Japanese yen rebounded strongly, nearing the 160 mark against the USD, marking its largest single-day gain since August of the previous year[8] - U.S. President Trump threatened to impose a 100% tariff on all Canadian exports to the U.S. if Canada reaches a trade agreement with China[8] ETF and Market Sentiment - Continuous outflows from broad-based ETFs in China have raised concerns about potential reductions in state-owned fund holdings, leading to increased interest in small-cap stocks[12] - From January 15 to 22, approximately 67.5 billion USD was sold off from 14 ETF products by the central government, indicating a significant market impact[12] Corporate Developments - Dongpeng Beverage plans to raise up to 10.141 billion HKD through an IPO, with a share price set at 248 HKD, representing a 12.5% discount compared to its A-share price[10] - BYD aims for overseas sales of 1.3 million vehicles in 2026, a nearly 24% increase from last year's 1.05 million deliveries[14]

2026年开年，全球汽车智能化竞赛在政策破局与商业落地两端同时按下加速键。1月，智能网联汽车领域都发生了哪些大事？小编为您一一梳理点 评。 国内新闻 ◆ 交通运输部：推动数据应用支撑智能驾驶、新能源汽车产业发展 1月4日，交通运输部发布《关于加快交通运输公共数据资源开发利用的实施意见》。其中提出，围绕服务公众出行、保通保畅、物流降本增效、 多式联运、绿色低碳、金融服务等行业领域，打造一批典型示范场景。通过数据开放、授权运营等方式，推动交通运输公共数据与企业数据融合应 用，支撑人工智能、智能驾驶、低空经济、新一代信息技术、新能源汽车等新兴产业与未来产业发展。 点评：数据是驱动智能驾驶发展的核心动力。交通运输公共数据资源的开发利用，必将为智能驾驶发展提供更多体量大、质量好的数据资源。 ◆ 工信部就7项智能网联汽车强制性国标公开征求意见 1月7日，工业和信息化部发布关于公开征求《智能网联汽车 自动泊车系统安全要求》等7项强制性国家标准制修订计划项目意见的公示。据悉， 《智能网联汽车 自动泊车系统安全要求》具体内容包括动态驾驶任务执行、人机交互、功能要求、用户告知、保障要求、安全档案、试验方法等。 点评：自动泊车普及 ...

Core Viewpoint - Samsung Electronics is nearing certification from Nvidia for its AI memory chip HBM4, aiming to close the competitive gap with SK Hynix [1][2]. Group 1: Samsung's Progress - Samsung has entered the final qualification phase with Nvidia after supplying initial samples in September [2]. - The company is preparing for mass production of HBM4 in February, with shipments expected to commence soon [3]. - Samsung's shares increased by up to 3.2% in Seoul, while SK Hynix's stock experienced a similar decline [3]. Group 2: Market Context - Samsung, SK Hynix, and Micron Technology are leading in AI memory, with all three companies seeing significant stock surges due to a memory shortage in the electronics industry [4]. - The combined market value of these three memory chip manufacturers has increased by approximately $900 billion since early September [4]. Group 3: Future Prospects - Investor optimism is growing that Samsung may supply components for Nvidia's upcoming flagship Rubin processors, which have primarily relied on SK Hynix for advanced memory chips [5]. - Samsung is expected to begin HBM4 shipments to Nvidia and Advanced Micro Devices in the coming month [6].

Core Viewpoint - The choice of TSMC as a foundry partner by Nvidia and AMD has proven to be a significant investment, especially in the context of the current AI industry where chip supply is a major bottleneck [1][2][3]. Group 1: Importance of TSMC - TSMC is recognized as the largest foundry in the AI supply chain, playing a crucial role alongside manufacturers like Nvidia and AMD [4]. - The strong relationships TSMC maintains with its partners are a key reason why companies prefer TSMC over alternatives, even when faced with attractive options from competitors like Intel [4]. Group 2: Nvidia's Commitment - Nvidia's CEO Jensen Huang expressed confidence in becoming TSMC's largest customer, a promise he made despite initial setbacks in technology [2]. - Nvidia's success, with a market valuation of $5 trillion, is attributed to its close relationship with TSMC, which has granted Nvidia exclusive access to certain technologies and a steady supply of chips [2]. Group 3: AMD's Strategic Decision - AMD's CEO Lisa Su highlighted the decision to trust TSMC as a major strategic move, which has led to significant gains in market share in both client and server segments [3]. - AMD's shift from GlobalFoundries to TSMC as its primary manufacturing partner has been pivotal in its success, contrasting with Intel's struggles in its internal foundry operations [3].

Core Viewpoint - The PCB sector is experiencing significant performance growth driven by AI demand, with several key investment themes identified for 2023 [1][2]. Investment Themes - **PCB Upgrade Trend**: The commercialization of CoWoP technology is accelerating, leading to a new round of upgrades in AI PCB products. mSAP capacity, equipment, and technical capabilities will become higher competitive thresholds for PCB manufacturers, presenting investment opportunities across the mSAP supply chain [1][2]. - **CCL Upgrade from M8 to M9**: The transition from M8 to M9 CCL is a definitive trend, with an increasing number of GPUs, ASIC servers, and 1.6T switches adopting M9 CCL. The usage of Q fabric, HVLP 3-4, and hydrocarbon resins will continue to rise rapidly [1][2]. - **Upstream Material Price Increases**: The price of upstream materials is still in an upward cycle, which is expected to further improve profitability [1][3]. - **Rising Demand for Substrates**: Demand for BT substrates is increasing, with continuous price hikes, while ABF substrate demand is beginning to overflow to domestic manufacturers [1][4]. Market Performance - The PCB sector's performance has exceeded market expectations, particularly in the upstream materials and equipment segments, driven by global AI PCB capacity expansion. Companies like Jin'an Guoji and Huazheng New Materials in the CCL segment, and Dazhu CNC and Chipbase in the equipment segment, have shown significant excess returns [2]. Price Trends - The CCL industry average price has increased by 20%-30% in 2025, with expectations for further price hikes in 2026 potentially exceeding those of 2025 due to supply-demand dynamics and raw material price trends [3]. Demand Dynamics - The global AI data center's storage demand is robust, with TSMC's capital expenditure for 2026 projected at $52-56 billion, significantly above market expectations. This indicates a strong upward trend in storage chip demand, leading to continuous price increases for BT substrates and the overflow of ABF substrate demand to domestic suppliers [4].

Core Insights - The rapid development of models like VLA has led to the emergence of various testing benchmarks, but the growth in model capabilities has outpaced existing benchmarks, highlighting a significant issue in the embodied intelligence field: the lack of a standardized measurement system for assessing true model capabilities [2] - The reliance on experience and intuition for R&D decisions has become a systemic risk in the transition from research to engineering in embodied intelligence [2] Group 1: Challenges in the Embodied Intelligence Field - The field is transitioning from storytelling to productivity, showcasing advancements like medical robots and mobile operation robots, but there are underlying industry consensus issues regarding the limitations of models and their ability to generalize across different tasks and environments [3][4] - The need for comprehensive generalization capabilities is emphasized, as robots must perform well in varied scenarios without being overly specialized, which is currently a challenge for many companies in the industry [5][6] Group 2: Testing and Evaluation Issues - The current testing landscape lacks standardized, scalable evaluation methods, leading to a reliance on limited testing scenarios that do not adequately measure model capabilities [10][12] - The industry consensus is that real-world testing cannot be scaled effectively, making simulation the only viable path for evaluation [13][21] Group 3: The Need for Industrial-Grade Evaluation Systems - There is a pressing need for a unified, scalable, and deterministic evaluation infrastructure that can support industrial-level decision-making in embodied intelligence [21][22] - NVIDIA and Lightwheel Intelligence's collaboration to create the Isaac Lab-Arena represents a significant step towards establishing a scalable evaluation framework in the field [23][24] Group 4: Features of the Isaac Lab-Arena - The Arena allows for flexible task creation and evaluation, moving away from rigid scripts to a modular approach that can adapt to various tasks and environments [26][28] - It supports a diverse range of tasks and environments, enabling systematic measurement of model capabilities rather than isolated demonstrations [66][70] Group 5: RoboFinals as an Industrial Benchmark - Lightwheel Intelligence has developed RoboFinals, an industrial-grade evaluation platform with over 250 tasks that systematically expose model failure modes and capability boundaries [63][71] - RoboFinals has been integrated into the workflows of leading model teams, providing continuous evaluation signals rather than just a ranking system [71][73] Group 6: The Importance of Collaboration - The partnership between NVIDIA and Lightwheel Intelligence is notable for its depth, as it combines strengths in simulation technology and real-world application experience to create a comprehensive evaluation system [42][56] - The collaboration aims to ensure that the evaluation infrastructure is not only technically sound but also aligned with the practical needs of model teams and robotic companies [54][56]

Core Insights - The demand for Nvidia's chips is surging, with a backlog exceeding $500 billion, indicating strong market interest and growth potential for the company [1][2] - Nvidia is making significant advancements in AI technology, particularly in areas like physical AI, which enhances understanding of the world and has applications in self-driving cars and robotics [3][4] - The company is focused on improving energy efficiency and reducing costs, with new chips being ten times more energy efficient and lower in cost compared to previous generations [4][5] Industry Trends - The AI sector is expanding into various fields, including healthcare and drug discovery, which is driving demand for advanced semiconductor solutions [2] - The competition in the AI chip market is intensifying, with numerous companies, including Chinese firms, entering the space and raising substantial capital [5][6] - The overall infrastructure investment in AI is projected to reach $85 trillion over the next 15 years, marking it as potentially the largest infrastructure buildout in history [8][9] Market Dynamics - Nvidia's GPUs are in high demand, with all available units currently rented out across major cloud platforms, indicating robust market conditions [11][12] - The rising spot prices for GPUs suggest a strong demand trajectory, further supporting the notion that the market is not in a bubble despite concerns about excessive borrowing for AI investments [10][11] - The company aims to maintain a competitive edge in the AI race by excelling across all layers of the AI stack, from energy to applications [6][7]

来源：环球市场播报 一位熟悉内情的人士周一表示，三星电子计划从下月开始生产下一代高带宽内存（HBM） 芯片，即 HBM4，并向英伟达供货。 该人士拒绝透露详细情况，比如三星计划向英伟达供应多少芯片。 三星发言人拒绝发表评论。 韩国报纸《韩国经济日报》周一援引芯片行业消息人士的话报道称，三星通过了英伟达和AMD的 HBM4资格测试，将于下月开始向这两家公司发货。 美股频道更多独家策划、专家专栏，免费查阅>> 责任编辑：栎树 ...

特斯拉、苹果、微软 、Meta、阿斯麦、IBM等科技股将于本周陆续发布财报。其中，市场对特斯拉财 报的关注点已从财务数据转移至全自动驾驶（FSD）系统、人形机器人与Robotaxi技术进展。微软与 Meta则将回答市场关于"企业是否开始从AI投资中获益"的问题。 【机构观点】 【市场回顾】 北京时间1月26日，日经225指数开盘报53023.28点，跌幅1.53%；韩国综合指数开盘报4997.54点，上涨 0.1%。 北京时间1月26日，现货黄金首次突破5000美元/盎司，日内涨约1%；现货白银盘初同样再创新高，涨 幅超2%，最高触及106.541美元/盎司。 当地时间1月23日，美国三大股指收盘涨跌不一，道指跌0.58%报49098.71点；标普500指数涨0.03%报 6915.61点；纳指涨0.28%报23501.24点。全周来看，道指累计下跌0.52%，标普500指数累计下跌 0.35%，纳斯达克指数累计下跌0.06%。 当地时间1月23日，欧洲主要股指收盘涨跌不一，德国DAX指数涨0.18%报24900.71点；法国CAC40指 数跌0.07%报8143.05点；英国富时100指数跌0.07%报10 ...

When Jeff Bezos said that one breakthrough technology would shape Amazon’s destiny, even Wall Street’s biggest analysts were caught off guard. Fast forward a year and Amazon’s new CEO Andy Jassy described generative AI as a “once-in-a-lifetime” technology that is already being used across Amazon to reinvent customer experiences. At the 8th Future Investment Initiative conference, Elon Musk predicted that by 2040 there would be at least 10 billion humanoid robots, with each priced between $20,000 and $25,000 ...