2025 年 11 月 3 日，美国总统 唐纳德·特朗普 表示，英伟达的最先进芯片将仅供美国公 司使用，中国及其他国家无法获得。 特朗普在播出的 CBS《60分钟》节目预录采访中以及在空军一号专机上对记者的答复中 表示，只有美国客户才能获得英伟达提供的顶级 Blackwell 芯片。 他告诉 CBS："除了美国外，我们不会让任何国家获得最先进的 AI 芯片。我们不会把 （Blackwell）芯片卖给其他国家。" 上述言论表明，特朗普可能对美国尖端 AI 芯片实施比美国政府官员此前暗示的更严格的 限制，中国乃至全球其他地区可能被禁止获得最先进的半导体。 今年 7 月，特朗普政府发布了一项新的 AI 蓝图，力求放宽环保规定，并大幅扩大对盟友 的 AI 技术出口力度，以维持美国在这一关键技术领域相对中国的优势。 就在上周五，英伟达表示将向韩国及其部分大型企业（包括三星电子）供应超过 26 万块 Blackwell AI 芯片。 自 8 月以来，人们一直在猜测特朗普是否会允许向中国出口降级版 Blackwell 芯片 —— 他当时曾暗示可能会允许此类销售。 特朗普告诉 CBS，他不会允许将最先进的 Blackwell ...

智通财经APP获悉，AMD(AMD.US)将于周二美股盘后公布第三季度财务业绩。据 TradingView 数据， 分析师预计 AMD 每股收益(EPS)为 1.17 美元，营收为 87.5 亿美元。上年同期，AMD 营收 68.2 亿美 元，每股收益 0.92 美元。上一季度，AMD 营收 76.8 亿美元，每股收益 0.48 美元。 今年迄今，AMD实现了强劲的表现，其股价上涨了约 115%。人工智能的繁荣为股价提供了强劲的助 力，预计来自人工智能支出的预期支持将继续支撑公司的财务指标。尽管在面向数据中心的芯片计算能 力方面，AMD 落后于英伟达(NVDA.US)，但 AMD 以折扣价提供其产品，这使其在该领域拥有自己的 细分市场。AMD并未远远落后于英伟达，投资者认为它能够在价格方面保持竞争优势。 AMD 在其产品路线图上有几款产品，有望进一步缩小与英伟达之间的差距。下一代人工智能机 架"Helios"基于 AMD 下一代 Instinct MI400 系列 GPU 构建，预计其性能将是前一代产品的约 10 倍。 除了新的部署外，服务器升级活动应有助于推动 AMD 的营收预期，这对股价对财报的反应至关重 ...

Market Analysis by covering: NVIDIA Corporation. Read 's Market Analysis on Investing.com ...

Market Analysis by covering: NVIDIA Corporation, Digital Realty Trust Inc, Vertiv Holdings Co, Constellation Energy Corp. Read 's Market Analysis on Investing.com ...

1. 11月，第十五届全国运动会将隆重举行。作为本届全运会的重磅科技亮点之一，中国移动通信集团公 司、乐聚智能（深圳）股份有限公司及北京通用人工智能研究院联合，首次实现了"机器人与人联合火 炬接力"活动，全球首款5G-A人形机器人"夸父"同时亮相。 【市场复盘】 上周五 （10月31日），科创人工智能ETF华夏（589010） 下跌1.71%，盘面呈现震荡下行格局。分时图 显示，该ETF开盘即回落至分时均线下方，午后围绕1.44元一线窄幅整理，走势偏弱。持仓股方面，18 只成分股上涨、12只下跌，结构分化明显。福昕软件、合合信息分别上涨20%与14.14%，AI应用与安全 方向个股走强；而石头科技、澜起科技跌幅居前，分别下跌12.04%与10.33%，高位回调明显。流动性 方面，成交量约7508万手、成交额超1.08亿元，交投保持活跃。近五日持续净流入，市场情绪高涨。 从技术面看，ETF全天运行于分时均线下方，短线处于调整阶段，若后续能稳住1.42元支撑或有望迎来 技术性反弹。整体来看，板块延续调整，但量能未显著萎缩，市场多空仍在分歧博弈中。机器人ETF （562500） 机器人ETF（562500.SH）报 ...

高盛发表研究报告指，预计英伟达10月底止第三财季业绩将胜预期，而股价反应将取决于公司上调指引 的幅度。该行预计业绩会议将聚焦四大重点，包括预期数据中心收入5,000亿美元的补充细节、OpenAI 2026年的部署、Rubin 2026年的量产进程，以及恢复中国业务的潜在可能性。 该行重申"买入"评级，将2026至28财年的收入与non-GAAP每股盈测平均上调12%，并将目标价上调至 240美元。 ...

以下文章来源于科创板日报 ，作者潇湘 科创板日报 . 专注科创板和科技创新，上海报业集团主管主办，界面财联社出品。 英伟达公司上周进一步创造了历史，成为全球首家市值突破5万亿美元的企业。而这一里程碑式的壮举，或许也预示着这家全球顶尖的芯片公司，对 世界经济和金融市场的影响力上升到了一个空前的维度。 这家处于人工智能革命核心的芯片制造商不仅是当今世界上规模最大的公司，也可能正成为华尔街历史长河里最具影响力的股票。 自2023年初以来，英伟达一直是美股上涨的主要推动力，为股东们带来巨额回报，并为公司首席执行官黄仁勋创造了上千亿美元的财富增 长。目前，其市值已超过了标普500指数11个行业板块中的6个，也超过了世界上大多数国家的股票市场规模。 Manulife John Hancock Investments联席首席投资策略师Matt Miskin表示，"从历史角度看，这显然是一个巨大的异常值，是真正值得 载入史册的奇观。" 就在上周，英伟达宣布与诺基亚、三星电子和现代汽车集团达成了新的合作。虽然该公司要到11月中旬才发布财报，但其却依然是本轮美股 财报季迄今最大的赢家之一：近期其他科技巨头的业绩普遍都凸显了英伟达 ...

Ah, the financial markets. A bastion of logic, predictability, and sober analysis. Or so one might hope. But when Donald J. Trump is in the political arena, particularly when he’s making pronouncements on trade, tariffs, and technological supremacy, the markets often resemble a particularly agitated toddler in a bouncy castle: full of sudden, unpredictable movements, punctuated by moments of dizzying ascent and equally abrupt descents. The past few weeks have been a masterclass in this very phenomenon, as i ...

Core Viewpoint - The value in the AI infrastructure market is expected to shift from chip manufacturers like NVIDIA to cloud service providers, but this perspective is challenged by the current economic realities of data centers and intense competition from Chinese firms [1][2]. Group 1: Cloud Profitability Reality - Cloud service profitability is significantly lower than anticipated, as evidenced by Oracle's data center gross margin disclosures, which reveal limited profitability even after accounting for GPU depreciation [3][4]. - The economic model resembles a monopoly upstream (NVIDIA) extracting major profits, while the downstream (cloud services) faces fierce competition and high costs, leading to limited profits [4][5]. Group 2: Downstream Application and Competition - Downstream profits are not as optimistic as market expectations, with many enterprises finding token demand lower than anticipated and economic benefits from tokens not materializing immediately [6][7][8]. - The competition from Chinese firms, particularly Alibaba's Qwen series, is reshaping cost structures with significantly lower token prices, creating downward pressure on pricing [10][11][20]. Group 3: Capital Cycle Perspective - The AI infrastructure investment is projected to exceed $4 trillion over the next 5-7 years, with signs of overcapacity and declining unit profits reminiscent of the historical railway boom [23]. - Key indicators of a potential cycle turning point include declining utilization rates, intensified price wars, and tightening financing conditions [23]. Group 4: Future Value Distribution - The ultimate value in AI is expected to flow towards application developers rather than cloud service providers, as chip manufacturers currently extract high profits, but as model costs decrease, the real profits will shift to AI enterprise software and vertical industry solutions [24][25]. - Alibaba's low-price strategy for tokens indicates a future where tokens become cheap and replaceable resources rather than high-margin products [26].

Core Insights - The current challenge in the AI industry is not an oversupply of computing resources but a lack of sufficient electricity to power GPUs, as stated by Microsoft CEO Satya Nadella [2] - The demand for electricity in AI data centers is projected to increase significantly, with a forecasted growth of 160% by 2030, leading to a need for an additional $50 billion in capital expenditure in the U.S. [2] - The competition for electricity resources among AI data centers is causing a rise in residential electricity costs, impacting ordinary citizens [5] Group 1: Electricity Supply and Demand - Nadella emphasized that the main issue is the inability to provide adequate power for the existing GPU inventory, rather than a shortage of chips [2] - Goldman Sachs reported that the share of electricity demand from U.S. data centers is expected to rise from 3% in 2022 to 8% by 2030 [2] - The U.S. Energy Information Administration (EIA) predicts an addition of 63 GW of power supply this year, with major AI companies accounting for approximately 41.3% of this new capacity [3] Group 2: Impact on AI Development - If electricity supply does not keep pace with the growing demand from AI data centers, it could become a bottleneck for AI development [4] - Dell Technologies noted that some clients have delayed delivery times for AI servers due to power supply issues, highlighting the critical need for sufficient energy alongside computing power [4] - OpenAI has called for the U.S. government to add 100 GW of generating capacity annually to maintain competitiveness with China in AI [5] Group 3: Future Considerations - There is speculation about the potential for advanced edge AI hardware to replace the need for large data centers, which could change the landscape of AI infrastructure [5] - Sam Altman mentioned the possibility of developing consumer hardware capable of running advanced AI models at low power, which could pose a risk to large centralized computing clusters [5]