公众号记得加星标⭐️，第一时间看推送不会错过。 讨论在美国生产芯片时，人们最关心的问题之一是这一过程的可持续性，因为对于像台积电这样的公 司来说，在美国生产会导致毛利率大幅下降。 台积电在美国晶圆厂运营成本大幅上升，但此次生产转移有着更为深远的意义。 特朗普政府特别重视"美国制造"理念，尤其关注半导体领域。因此，台积电和三星等公司加大了在美 国的投资，以构建更具韧性的供应链。这家台湾芯片巨头计划将其对美国供应链的投资增加至多3000 亿美元，其中包括在亚利桑那州建设晶圆厂、先进封装和研发设施。然而，根据分析师Jukan on X分 享并由SemiAnalysis汇总的数据，台积电在美国生产芯片将使其利润率遭受重大损失。 参考链接 | | | Taiwan | us | | --- | --- | --- | --- | | Item | Unit | Fab 18 Phase 1-3 | Fab 21, Phase 1 | | Fab capex | US$ | 27,000,000,000 | 14,380,000,000 | | Wafer fab equipment | US$ | 22,950,000 ...

Core Viewpoint - Barclays analysts indicate that Rio Tinto's first investor briefing under new CEO Simon Trott largely meets market expectations, with Trott aiming for a "leaner" and "more agile" company strategy, potentially leading to a 2030 EBITDA forecast that exceeds Barclays' estimate by approximately $5 billion and the market average by about $7 billion [1] Group 1 - The briefing aligns with market expectations, suggesting a positive reception from analysts [1] - Trott's leadership is focused on making Rio Tinto more efficient and responsive [1] - The projected EBITDA for 2030 is significantly higher than previous estimates, indicating strong future performance potential [1] Group 2 - Despite the positive outlook, analysts note that market expectations were already high prior to the briefing [1] - The production guidance for 2026 appears weaker compared to market averages, which may lead to downward adjustments in market expectations [1]

Core Viewpoint - The company announced a focus on capital expenditures related to its core business development, indicating a trend of decreasing capital spending in the absence of new line investments [1] Group 1: Capital Expenditures - The company's capital expenditures are primarily directed towards fixed asset investments for existing production lines, technological upgrades, and equity investments aligned with strategic planning [1] - As previous equity investment projects' capital contributions are gradually fulfilled, capital expenditures are expected to decline [1] Group 2: Depreciation - The company anticipates that depreciation in 2025 will not differ significantly from 2024, as new production lines reach their operational standards and mature LTPS production lines approach the end of their depreciation period [1] - Following the peak in depreciation, the company expects depreciation amounts to begin to decrease in the absence of new line investments [1]

Core Insights - Major companies plan to invest $1 trillion in AI data centers over the next five years, with a focus on depreciation as a key financial consideration [2] - The lifespan of AI GPUs is uncertain, with companies like Google, Oracle, and Microsoft estimating a maximum lifespan of six years, but potentially shorter [2][4] - Investors are concerned about the depreciation period, as longer asset lifespans lead to smaller impacts on profits [2] Depreciation Challenges - AI GPUs are relatively new, with NVIDIA's first AI-specific processor launched around 2018, and the current AI boom starting in late 2022 [4] - NVIDIA's data center revenue surged from $15 billion to $115 billion in the fiscal year ending January 2023 [4] - There is no historical reference for the lifespan of GPUs, making it difficult for companies to estimate depreciation accurately [4][5] Market Reactions - CoreWeave has set a six-year depreciation cycle for GPUs, indicating a data-driven approach to asset valuation [4][5] - Despite high demand for NVIDIA's A100 and H100 chips, CoreWeave's stock fell 16% after earnings guidance was affected by third-party data center developer delays [5][6] - The stock of Oracle has also dropped 34% since reaching a historical high in September [6] Skepticism in the Market - Short-seller Michael Burry has expressed doubts about the longevity of AI chips, suggesting that companies may be overstating their lifespan and underestimating depreciation costs [6] - Burry believes that the actual lifespan of server equipment is around two to three years, which could inflate reported earnings [6] Technological Advancements - AI chips may depreciate within six years due to wear and tear or obsolescence from newer models [8] - NVIDIA's CEO has indicated that older chip models will lose significant value as new models are released [8] - Amazon has shortened the expected lifespan of some servers from six years to five years due to rapid technological advancements [8][9] Strategic Procurement - Microsoft is diversifying its AI chip procurement to avoid over-investment in any single generation of processors [9] - The rapid iteration of technology in the AI sector complicates depreciation estimates, requiring careful financial forecasting [9]