Core Viewpoint - The U.S. government plans to allow Nvidia to export its H200 chips to China, marking a significant shift in the company's efforts to maintain market access in the world's second-largest economy [2][3]. Group 1: Export Approval and Market Impact - The U.S. Department of Commerce is expected to approve the export of Nvidia's H200 chips, which outperform the previously approved H20 but are less powerful than Nvidia's top-tier Blackwell and upcoming Rubin series chips [2]. - This decision follows a meeting between President Trump and Nvidia CEO Jensen Huang, where they discussed the H200 export issue [2]. - Officials, including AI Director David Sacks and Commerce Secretary Howard Lutnick, support the H200 export as a compromise that allows Nvidia to compete in China without enabling China to surpass the U.S. in AI [2]. Group 2: Performance and Sales Potential - The H200 chip's performance is estimated to be nearly six times that of the H20, which could lead to billions in sales for Nvidia and assist Chinese tech giants struggling to access top-tier chips for model training [3][4]. - Huang emphasized the importance of allowing Nvidia to compete in the Chinese market due to the country's significant AI demand and talent pool [4]. Group 3: GPU Shipment Controversy - A blogger named Kakashii has raised doubts about Nvidia's reported shipment of 6 million Blackwell GPUs, suggesting discrepancies between reported revenue and shipment numbers [6][8]. - Kakashii's analysis indicates that the reported $111 billion in data center revenue does not align with the claimed shipment figures, leading to questions about the actual number of GPUs sold [8][9]. Group 4: Accounting and Depreciation Concerns - Michael Burry has expressed concerns regarding the accounting practices related to AI hardware depreciation, arguing that companies may be overstating profits by extending the useful life of expensive GPUs [14][15]. - Burry suggests that the rapid pace of AI hardware development makes longer depreciation periods unrealistic, potentially masking the true economic performance of companies investing in AI [16][17]. - The ongoing debate about depreciation methods in the tech industry highlights the need for accurate accounting practices, especially as companies invest heavily in AI infrastructure [18][22].

然而，对于关注这些科技巨头的投资者而言，问题的关键可能并非简单的"对与错"。 尽管延长折旧年 限确实能即时提升盈利数字，但其对公司基本面的实质影响或许有限。市场更关注的是AI投资的最终 回报，而非会计处理细节。 而更深层次的讨论已经转向折旧方法的选择，以及这些会计处理最终是否 会影响对AI投资长期价值的判断。 科技巨头延长AI芯片等设备的折旧年限确实能立竿见影地提升账面利润，例如Meta因此在今年前九个 月减少了23亿美元的费用。然而，分析称，这场会计技术辩论的实际影响可能有限，市场的最终焦点 仍是数千亿美元AI投资的长期回报率，而非会计处理的细枝末节。 随着科技巨头在人工智能领域投入数千亿美元巨资，一项看似平淡的会计处理——AI芯片等关键设备 的折旧方法，正意外成为市场争议的焦点，引发了关于企业是否借此美化盈利的激烈辩论。 据《华尔街日报》12月8日报道，近期，包括Meta、Alphabet、微软和亚马逊在内的公司纷纷延长了 其服务器和网络资产的预计使用年限。这一会计变更直接降低了当期折旧费用，从而推高了账面利 润，此举立即引起了部分投资者的警觉和审视。 知名"大空头"Michael Burry更是将此举称 ...

随着科技巨头在人工智能领域投入数千亿美元巨资，一项看似平淡的会计处理——AI芯片等关键设备 的折旧方法，正意外成为市场争议的焦点，引发了关于企业是否借此美化盈利的激烈辩论。 据《华尔街日报》12月8日报道，近期，包括Meta、Alphabet、微软和亚马逊在内的公司纷纷延长了其 服务器和网络资产的预计使用年限。这一会计变更直接降低了当期折旧费用，从而推高了账面利润，此 举立即引起了部分投资者的警觉和审视。 知名"大空头"Michael Burry更是将此举称为"现代常见的欺诈之一"，他在上月的一篇文章中写道，延长 资产使用年限会减少折旧费用并增加表观利润，这会导致资产估值过高和利润虚报。当巨额资本支出悬 于一线时，这种会计估计的调整足以牵动市场的敏感神经。 然而，对于关注这些科技巨头的投资者而言，问题的关键可能并非简单的"对与错"。尽管延长折旧年限 确实能即时提升盈利数字，但其对公司基本面的实质影响或许有限。市场更关注的是AI投资的最终回 报，而非会计处理细节。而更深层次的讨论已经转向折旧方法的选择，以及这些会计处理最终是否会影 响对AI投资长期价值的判断。 会计调整的"利润魔法" 折旧是确保资本投资成本在财 ...