AMD是美国一家主要从事微处理器及相关IC设计的跨国企业，主要产品是中央处理器（包括嵌入式平台）、图形处理器、主板芯片组以及存储器。苏姿丰 表示，2025年AMD ROCm软件AI性能最高提升了五倍。并表示将推出Adrenalin Edition AI Bundle，旨在简化本地AI环境部署，助力PC端的AI开发应用。 苏姿丰还在演讲中强调，为了继续保持AI活跃增长，让全球普及AI应用，未来几年需要将全球的AI计算能力提升100倍。 1月6日消息，AMD CEO苏姿丰今日亮相CES 2026并发表主题演讲。苏姿丰在演讲中表示，自ChatGPT发布以来，使用AI的活跃用户从100万增至10亿，并大 胆预测2030年使用AI的活跃用户将达到50亿。她表示："这是互联网花了几十年才达到的里程碑"。 ...

从诸多方面来看，美光科技公司（MU）的股票在近期的人工智能芯片行情中算得上是一个异 类。 客观而言，美光股价在过去三个月内一路飙升，涨幅接近 75%；相比之下，人工智能领域的 标杆企业英伟达公司（NVDA）同期股价仅上涨了 0.5%。 在当前投资者对人工智能概念股秉持 "眼见为实" 审慎态度的阶段，美光却展现出了势不可挡 的强劲势头。 这背后的原因究竟是什么？ 【如需和我们交流可扫码添加进社群】 首先， 尽管美光与英伟达、超威半导体公司（AMD）等半导体巨头同属一个赛道，但其竞争 优势却源自人工智能产业链中一个完全不同的环节。 本质上，美光主攻的是产业链中的瓶颈环节 —— 存储器，而非那些抢占头条热度的产品，比 如图形处理器、加速器以及定制化芯片。 如果没有美光大规模生产的高带宽存储器（HBM），英伟达性能强劲的图形处理器也将一无是 处。 目前，全球范围内具备高带宽存储器供应能力的厂商仅有三家，另外两家分别是三星电子有限 公司（SSNLF）和海力士公司（HXSC.F）。 因此，对于美光而言，定价权远比产品销量重要得多。 高带宽存储器需要实现供不应求的市场格局 —— 而当下的市场恰恰已经处于这种状态，这也 正是 ...

为实现上述目标，政府计划统筹配置约5万块图形处理器资源，并据此优化算力分配机制，重点支持风 险投资机构与初创企业在技术研发及示范应用方面的需求。同时，将围绕人工智能、生物医药、文化创 意内容、国防军工、能源及先进制造等六大战略产业，系统完善政策支持体系，力争在2030年前完成相 关初创企业的培育任务。 韩国《韩联社》12月18日报道，韩国中小风险企业部于18日联合相关部门发布《迈向全球四大创投 强国综合对策》，明确提出以下战略目标：培育1万家专注于人工智能与硬科技领域的初创企业；打造 50家具有全球竞争力的独角兽及"十角兽"企业；推动相关企业与年规模约40万亿韩元（约合人民币1904 亿元）的全球风险投资市场实现有效对接。 （原标题：韩制定科创强国发展战略） ...

在此需说明，分析师并非认为人工智能本身缺乏发展持续性，相反，分析师预计它将继续保持高速增 长。 真正面临风险的，是那些投入到数据中心、图形处理器、冷却系统、供电及布线等领域高达数千亿美元 的人工智能资本开支 —— 未来的人工智能技术，根本无需如此庞大的硬件投入规模。 在数据中心支出缩减的潜在风险面前，没有哪家企业比英伟达受到的冲击会更大。 如今，该公司的绝大部分营收和利润都来源于为数据中心提供相关产品。 2.电力供应受限。美国电网的供电能力，难以支撑所有规划中新数据中心的运行需求。而新建发电厂投 入运营往往需要数年时间，部分项目甚至要超过十年。 3.能效持续提升。在人工智能技术自身等因素的推动下，各类设备和系统的能效将不断提高，这会减少 对基础设施的投资需求。 4.投资回报率不足。人工智能虽已改变诸多领域，但真正由此实现盈利增长的案例却屈指可数。 目前，大规模人工智能投资能获得市场平均回报率的案例寥寥无几，仅有微软和帕兰提尔科技等少数企 业或许取得了可观回报，其他多数企业的投资回报情况均不尽如人意。 5.投资者与首席财务官的耐心有限。对于这种回报难以量化的大规模投资，财务部门、公司董事及投资 者还能容忍多久？ ...

在此需说明，分析师并非认为人工智能本身缺乏发展持续性，相反， 分析师 预计它将继续保 持高速增长。 真正面临风险的，是那些投入到数据中心、图形处理器、冷却系统、供电及布线等领域高达数 千亿美元的人工智能资本开支 —— 未来的人工智能技术，根本无需如此庞大的硬件投入规 模。 在数据中心支出缩减的潜在风险面前，没有哪家企业比英伟达受到的冲击会更大。 如今，该公司的绝大部分营收和利润都来源于为数据中心提供相关产品。 人 工 智 能 资 本 开 支 增 长 难 以 为 继 的 原 因 以下 13 点，正是 分析师 认为当前人工智能资本开支增长无法持续的核心依据： 1. 未来人工智能的能耗将显著降低。 deepseek公司以及即将落地的脉冲神经网络就是有力例 证，这类神经网络在闲置时可自动停机以实现节能。深度求索公司，即便未采用英伟达的图形 处理器，也研发出了具备竞争力的大型语言模型。 7. 新技术落地周期远超预期。 自动驾驶领域的案例表明，这类技术要熟练应对复杂任务，所 需时间往往比预想中更长。 关键在于技术要能真正成熟可用。马斯克等人十年前就承诺推出自动驾驶汽车，而谷歌旗下的 自动驾驶公司Waymo出行，直至如今才 ...

来源：环球市场播报 调整后每股收益：1.95美元（预期1.86美元） 今年6月，博通透露其定制化人工智能芯片已有3家客户和4家潜在客户；9月宣布迎来第四家匿名大客 户，对方下达了100亿美元的定制芯片订单；10月又与OpenAI达成合作，共同研发定制化芯片。投资者 正密切关注博通是否能确认这些企业持续合作，并按计划采购、部署定制芯片。 博通本季度总营收同比增长28%，公司将这一增长主要归功于人工智能芯片销售额74%的大幅攀升，这 意味着第四季度人工智能相关收入已达82亿美元。 博通（Broadcom）发布的第四财季报告显示，公司调整后每股收益与营收均超出市场预期，同时受 人工智能需求推动，发布了强劲的本季度业绩指引。 营收：180.2亿美元（预期174.9亿美元） 博通表示，第一季度营收预计约为191亿美元，同比增长28%，高于分析师平均预期183亿美元。 首席执行官Hock Tan在声明中称，博通预计本季度人工智能芯片销售额将同比翻倍至82亿美元，收入来 源既包括定制化人工智能芯片，也涵盖人工智能网络相关半导体产品。 本季度公司净利润同比激增97%，从去年同期的43.2亿美元（合每股0.90美元）增至85. ...

Core Viewpoint - AMD is not in an AI bubble but is in the "third year of a ten-year super cycle of computing demand" [1][10]. Group 1: AMD's Strategic Positioning - AMD has transitioned from being a "CPU follower" to a data center powerhouse [3]. - The company has reallocated R&D resources towards high-performance computing and AI, resulting in a data center business growth rate exceeding 50%, projected to rise above 60% [5][6]. - AMD aims to capture a double-digit market share in a projected $1 trillion data center market by 2030, leveraging its comprehensive product portfolio [6][8]. Group 2: Competitive Advantages - AMD's chiplet-first architecture and rack-scale systems provide a significant competitive edge [2]. - The company possesses unique capabilities across CPUs, GPUs, FPGAs, and ASICs, allowing for integrated solutions that adapt to changing workloads [6][8]. - AMD believes that GPUs will dominate the market for the next five years due to their programmability and flexibility, while custom ASICs will complement rather than replace them [7][12]. Group 3: Transition to System Solutions - AMD is evolving from a "chip company" to a "system company," focusing on full-stack solutions to enhance deployment efficiency [9][10]. - The acquisition of ZT Systems and partnerships for rack-level designs like Helios demonstrate AMD's commitment to this strategy [9][10]. Group 4: AI Market Dynamics - AMD's CEO asserts that the current AI landscape is not speculative but integral to productivity and innovation across various sectors [10][12]. - The demand for CPUs is rising due to the increasing need for general-purpose processing in AI applications, countering the notion that GPUs will solely dominate [11][12]. Group 5: Future Outlook - AMD's strategic focus on high-performance computing and AI positions it well for significant growth, with analysts projecting a potential stock price of $775, and in optimistic scenarios, close to $1000 [2].

Core Insights - Intrinsic, a subsidiary of Alphabet, is partnering with Foxconn to establish a joint venture focused on deploying robots in Foxconn's U.S. factories, leveraging Foxconn's extensive manufacturing expertise [2][4] - The collaboration aims to enhance manufacturing processes through AI-driven robotics, addressing the challenges of flexible manufacturing and labor shortages in the industry [3][6] Group 1: Partnership Details - The partnership between Intrinsic and Foxconn has been in discussion for one to two years, indicating a strategic alignment in software and AI technology [3] - Foxconn's Chairman Liu Yangwei emphasized that this collaboration will strengthen their global manufacturing leadership and contribute to the development of future factories [4] - The joint venture is not a pilot project, although specific investment amounts have not been disclosed [5] Group 2: Industry Trends - The focus on "embodied AI" reflects a growing trend towards applying AI in real-world manufacturing settings, driven by supply chain disruptions during the COVID-19 pandemic and the need for reshoring manufacturing [6] - The loss of skilled labor in developed economies has created a demand for robotic solutions to enhance production capacity [6] - Asia, particularly China, dominates the industrial robotics market, producing over half of the world's industrial robots, with companies like Unitree advancing humanoid robot development [7]

Core Viewpoint - The article discusses the increasing volatility of AI concept stocks in the US market, highlighting concerns about an "AI bubble" as major firms like Nvidia see soaring valuations while others, including SoftBank and Citadel, reduce their stakes in these stocks [2][3][4]. Group 1: Valuation Concerns - AI concept stocks are perceived to have inflated valuations that may not be sustainable, with Nvidia's stock price increasing approximately 11 times since the launch of ChatGPT in November 2022, while the S&P 500 index rose about 70% during the same period [2][3]. - Nvidia's market capitalization recently surpassed $5 trillion, exceeding Germany's annual GDP, raising questions about the sustainability of such valuations [2]. - Oracle's stock surged 41% after announcing a $300 billion order from OpenAI, yet its latest financial report revealed an AI cloud service gross margin of only 14%, indicating potential profitability issues [2]. Group 2: Infrastructure Investment - Major tech companies, including OpenAI, Microsoft, Google, Meta, and Amazon, are engaged in a significant "AI arms race," with projected capital expenditures on AI infrastructure reaching $1.4 trillion from 2025 to 2027 [3]. - In 2023 alone, investments in the AI sector amounted to $500 billion, but returns have yet to materialize, suggesting a risk of sunk costs if technology becomes outdated [3]. Group 3: Financing Risks - The current financing model among AI giants involves mutual investments and high-value contracts, which may inflate revenue figures artificially, creating a risk of collapse if any part of the chain falters [3][4]. - The shift from light-asset to heavy-asset models among tech companies is leading to increased debt reliance, with $157 billion raised in the US bond market by tech firms as of September 2023, a 70% year-on-year increase [5]. Group 4: Profitability Challenges - There is a significant mismatch between the costs associated with AI and the value generated, with nearly 80% of companies deploying AI failing to achieve net profit increases [4]. - OpenAI reported $4.3 billion in revenue in the first half of 2023 but incurred a net loss of $13.5 billion, highlighting the profitability challenges in the sector [5]. Group 5: Market Sentiment and Future Outlook - Some industry leaders, including Bill Gates and IMF President Kristalina Georgieva, warn that the current AI investment frenzy resembles the late 1990s internet bubble, suggesting potential for significant losses [5][6]. - Supporters of AI argue for its vast demand and potential, with Nvidia's CEO asserting that current AI technology is actively utilized, and capital expenditures among major cloud providers are expected to rise to $632 billion by 2027 [6]. - The article emphasizes the need to differentiate between short-term market fluctuations and the long-term innovative potential of AI, suggesting that while market corrections may occur, the fundamental advancements in productivity driven by AI remain promising [7][8].

Core Viewpoint - The article discusses the increasing volatility of AI concept stocks in the US market, highlighting the growing concerns about a potential "AI bubble" as major firms like Nvidia reach unprecedented market valuations while others, including SoftBank and Bridgewater, significantly reduce their holdings in these stocks [1][4]. Group 1: Valuation Concerns - The high valuations of AI concept stocks are seen as overextending performance expectations, with Nvidia's stock price increasing approximately 11 times since the launch of ChatGPT in November 2022, while the S&P 500 index rose about 70% during the same period [1]. - Nvidia's market capitalization recently surpassed $5 trillion, exceeding Germany's annual GDP, raising questions about the sustainability of such valuations [1]. - Oracle's stock surged 41% after announcing a $300 billion order from OpenAI, yet its latest financial report revealed an AI cloud service gross margin of only 14% and a quarterly loss of $100 million from leasing Nvidia chips [1]. Group 2: Infrastructure Investment - Major tech companies, including OpenAI, Microsoft, Google, Meta, and Amazon, are engaged in a fierce "AI arms race," with capital expenditures on AI infrastructure projected to reach $1.4 trillion from 2025 to 2027 [2]. - The World Economic Forum noted that AI investments reached $500 billion this year, but returns have yet to materialize, indicating a risk of significant sunk costs if technology becomes outdated [2]. Group 3: Financing Risks - AI giants are using a cycle of mutual investments and high-value contracts to inflate their revenue and valuation, raising concerns about the sustainability of this model [2]. - Nvidia's $100 billion investment in OpenAI and OpenAI's $300 billion order from Oracle exemplify this interconnected financing, which could collapse if any part of the chain falters [2]. Group 4: Profitability Challenges - The costs associated with AI investments do not align with the value created, posing a significant challenge to current business models [3]. - Data indicates that 80% of companies deploying AI have not seen net profit increases, and 95% of generative AI pilot projects have not yielded direct financial returns [3]. - OpenAI reported $4.3 billion in revenue but a net loss of $13.5 billion in the first half of the year, with a quarterly loss exceeding $11.5 billion [3]. Group 5: Economic Implications - The massive investments in AI infrastructure are pushing tech companies towards a heavy asset model, increasing reliance on debt financing, with US tech companies raising $157 billion in the bond market by September, a 70% year-on-year increase [4]. - The deep integration of AI investments into the US economy has raised concerns that a downturn in AI investment could adversely affect overall economic growth [6]. Group 6: Market Comparisons - Industry experts draw parallels between the current AI stock frenzy and the internet bubble of the late 1990s, warning of potential financial fallout [4]. - Supporters of AI argue for its vast demand and potential, with Nvidia's CEO asserting that current AI technology is actively utilized, contrasting with the past internet bubble [4]. Group 7: Future Outlook - The article suggests a long-term perspective on the current debates surrounding AI investments, emphasizing the transformative potential of AI in enhancing productivity across various sectors [5][6]. - The contrasting strategies of US tech giants and Chinese AI companies highlight different approaches to market dominance, with the latter adopting more open-source strategies [7].