Nvidia (NVDA 0.53%) is one of the hottest stocks on the market today. Over the past five years, Nvidia shares have soared in value by nearly 1,500%, including another 20% in the last 12 months.Think the run is over? Think again. Nvidia stock remains far cheaper than most investors realize due to one critical factor.Nvidia's profits will rise for decades to comeThe artificial intelligence (AI) revolution is in full swing. But we're still in the early innings. In 2023, the United Nations estimated the global ...

高盛维持对AMD(AMD.US)的"中性"评级，目标价为140美元。尽管这家半导体巨头的回报和营收令人 印象深刻，但投资者认为，AMD的增长潜力受到人工智能和GPU领域激烈竞争的抑制。 InvestingPro的数据显示，AMD的市盈率为101.36，这意味着其估值处于历史高位。尽管如此，该股在 过去六个月中仍实现了19.28%的回报率，这表明投资者对人工智能的热情高涨，且其投入不断增加。 AMD在过去12个月的收入增长了21.71%，年总收入达到277.5亿美元，其运营状况持续良好。作为一家 生产基于X86架构的服务器和PC CPU、定制SoC以及商用GPU的无晶圆厂制造商，AMD的战略重点使 其在服务器CPU和PC CPU市场取得了显著进展。 挑战依然存在 仍有分析师看好前景 高盛预计，由于基于ARM的处理器的采用率不断上升，AMD在服务器CPU市场的份额增长将放缓。 ARM处理器因其高效和可扩展性而日益受到欢迎。另一方面，AMD的商用GPU产品面临来自英伟达的 激烈竞争，英伟达的领导地位也得益于其强大的AI软件堆栈。英伟达在AI领域的领先地位及其成熟的 生态系统，使得AMD难以快速抢占市场份额。 高盛还 ...

Nvidia (NVDA 0.75%) shares climbed 0.7% on Thursday, July 10, to close at $164.10,  outperforming the broader market and pushing the chipmaker over the $4 trillion market capitalization threshold at the close of trading. The stock traded between $161.63 and $164.49 throughout the session, and the close above $4 trillion added to its position as the largest public company globally.The S&P 500 and Dow Jones Industrial Average also finished in positive territory, gaining 0.27% and 0.43% respectively. Nvidia's ...

我们讲过很多关于GPU vs ASIC的内容，前几天还发过这样一张图，国外大厂的研发进度规划。 下面的数据是HSBC统计的，我只列出了统计的部分数据，星球中我们把各大投行日常研报中的关键 数据都做了记录，有兴趣的朋友可以到星球中查看。 | Chip supplier | Chip type | Chip name | Design partner | Release date | Tech | Memory type | Capacity (GB) | | --- | --- | --- | --- | --- | --- | --- | --- | | NVIDIA (Global) | Al GPU | A100 | In - House | 2020 | node 7nm | HBM2e 8 High | 80 | | NVIDIA (Global) | AI GPU | H100 | In - House | 2022 | 4nm | HBM3 8 High | 80 | | NVIDIA (Global) | AI GPU | B100 | In - House | 2024 | 4nm | HBM ...

Group 1: Nvidia Overview - Nvidia is now the largest publicly traded company in the world with a market capitalization of nearly $4 trillion, driven by significant investment in artificial intelligence (AI) [1] - Analysts highlight Nvidia's monopoly in critical technology and its strong pricing and margin power, indicating robust demand for its products [2] Group 2: IBM's Position in AI - IBM, referred to as "Big Blue," has historically faced challenges but continues to invest in AI, with its generative AI business generating $6 billion in annual revenue [3][4] - The demand for AI solutions is projected to grow by over 30% in the next decade, positioning IBM's AI segment as a potential major profit driver [4] Group 3: Quantum Computing Potential - IBM is also focusing on quantum computing, with plans to launch a large-scale, fault-tolerant quantum computer by 2030, which could represent a significant technological breakthrough [5] - Analysts note that IBM's dual focus on AI and quantum computing may provide a long-term competitive advantage over companies that specialize in only one area [8] Group 4: Comparative Analysis of IBM and Nvidia - Despite IBM's exciting prospects, it is a diversified company with only a small portion of its business currently benefiting from AI, leading to a projected revenue growth of just 5.5% for IBM compared to 53% for Nvidia this year [10] - Nvidia's AI GPUs are recognized as the best in the industry, maintaining over 90% market share in data center GPUs, while IBM faces stiff competition in its markets [11][12] Group 5: Investment Considerations - Investors are advised not to abandon Nvidia for IBM at this stage, as Nvidia remains a critical infrastructure provider for the AI industry, while IBM's services are one of many options available [12][13] - A diversified portfolio that includes both companies allows investors to capitalize on the entire AI supply chain, from hardware to software [13]

智通财经APP获悉，摩根大通最新CIO调查报告显示，未来三年AI将成为重点投入领域：约68%受访者计划 将超5%预算投入该领域，当前约为25%。 本次调查覆盖了168位管理着约1230亿美元年度企业IT支出的首席信息官，与半导体支出直接相关的两大核 心问题包括：1）当前组织IT预算中用于AI/加速计算本地硬件及云服务的占比；2）当前公共云支出占IT预 算比重及其预期值。调查结果印证了由AI/加速计算数据驱动支出带动的持续强劲云资本支出增长预期。 调查结果提供了几个关键点，小摩认为这些点支持了由AI加速计算数据中心建设推动的持续强劲的云资本 支出增长。首先，反馈显示未来三年对AI的强烈关注——68%的受访者打算在未来三年内将超过5%的IT预 算用于AI计算硬件。其次，作为CIO IT预算百分比的AI相关计算支出意图在未来三年内看起来将增加到 15.9%，而目前约为5.9%，这意味着年复合增长率为41%，这一增长率优于小摩的XPU（GPU、TPU、 DPU）半导体收入增长预期的30-35%。 小摩认为，来自大型企业客户的低双位数云支出年复合增长率表明，云服务提供商（AI和通用计算工作负 载）的持续健康业务背景有助 ...

Core Viewpoint - The article discusses the increasing competition in the AI chip market, particularly how major tech companies like Google and Meta are accelerating their development of custom chips to reduce reliance on Nvidia's GPUs, with predictions that ASIC shipments will surpass Nvidia's AI GPU shipments as early as next year [1][2]. Group 1: Market Dynamics - Nvidia has historically dominated the AI chip market, holding over 80% market share in AI servers, while ASIC-based servers currently account for only 8% to 11% [2][4]. - Google is expected to ship between 1.5 million to 2 million of its self-developed AI chips (TPUs) this year, while Amazon's AWS is projected to ship 1.4 million to 1.5 million ASICs, bringing their combined shipments close to half of Nvidia's estimated annual GPU shipments of 5 million to 6 million [2][4]. Group 2: Cost Efficiency - The key advantage driving tech giants to develop their own chips is the reduction in Total Cost of Ownership (TCO), with ASICs potentially saving 30% to 50% in TCO compared to GPUs [3]. - Google claims its TPUs can deliver three times the performance of Nvidia GPUs per unit of energy consumed, highlighting the efficiency of custom chips [3]. Group 3: Competitive Landscape - Meta is focusing on launching its new high-performance ASIC chip "MTIA T-V1" in Q4 of this year, aiming to outperform Nvidia's next-generation AI GPU "Rubin" [5]. - Despite ambitious plans, Meta faces production challenges due to limited advanced packaging capacity from TSMC, which can only provide 300,000 to 400,000 units, creating a bottleneck [5]. Group 4: Nvidia's Response - In response to the competitive threat, Nvidia has opened its proprietary "NVIDIA NVLink" communication protocol to facilitate integration with other companies' CPUs or ASICs, aiming to retain its major clients [6]. - Nvidia's established software ecosystem, CUDA, remains a significant barrier for competitors, as it allows AI developers to efficiently build and deploy applications, maintaining Nvidia's competitive edge [6].

①美联储欲放宽对大型银行强化补充杠杆率要求 鲍威尔称停发银行准备金利息的建议并不能省钱 美联储提议放松关键银行资本规则计划，拟修改美国大型银行强化补充杠杆率（eSLR）规则，将大型 银行控股公司资本要求从5%降至3.5%-4.5%，子公司从6%降至相同范围，旨在增强美债市场韧性，让 银行有更大灵活性购买美债。美联储以5比2通过该提议，鲍威尔支持修订，但理事巴尔和库格勒反对， 认为这会增加银行倒闭风险。公众可在未来60天内提出意见，银行业预计将争取更多豁免或规则放松。 此外，鲍威尔在国会山听证会上表示，停止为银行准备金付息不能省钱，恢复稀缺准备金制度将充满挑 战并可能引发动荡。准备金余额利息（IORB）是美联储控制短期利率的重要工具，尤其在充裕准备金 制度下。此前，德州参议员Ted Cruz提议终止付息，声称十年内可节省1.1万亿美元，但鲍威尔认为这不 可行。 国鸣证券秦毅：美联储提议降低大型银行补充杠杆率，大型银行资产负债表相对安全资产规模大增，监 管层放松是审慎之举，美国银行、高盛、JP摩根等大型银行受益。大型银行控股公司层面释放核心资本 约130亿美元，银行子公司层面核心资本减少约2100亿美元。该提议的 ...

Key Takeaways C3.ai reported FY 2025 revenues of $389.1M, up 25%, with FY 2026 guidance of up to $484.5M. C3.ai secured a U.S. Air Force contract raise to $450M and expanded oil and gas sector bookings. Partnerships with MSFT and GOOGL help position AI as a top app on Azure and Google Cloud.NVIDIA Corporation’s (NVDA) data center graphics processing units (GPUs) for artificial intelligence (AI) tasks have boosted its business, while C3.ai, Inc.’s (AI) AI applications have won over a diverse client base.  ...

Broadcom Inc (AVGO US) Upgrade to Buy: ASIC potential to knock our socks off Turning positive on Broadcom driven by better ASIC visibility: We were previously less bullish as we wanted to see better visibility into the ASIC customer pipeline emerge. We also had concerns about Apple share loss in the wireless segment as well as a potential VMware slowdown. However, we turn positive on Broadcom as we now believe its ASIC revenues will significantly beat market expectations from better ASIC project visibility ...