CoWoS

本文為繁體中文版。English version: The AI Capex Money Map v0.2 — America Spends. Who Actually Keeps the Margin? 本站為文字版；含完整圖表的版本請見 Medium 原文。 大多數人現在都在問：「AI 是不是泡沫？」 這個問題重要，但不夠可操作。對投資人與供應鏈觀察者來說，更好的問題只有一句： 美國大型科技公司花出去的 AI Capex，最後流到誰的收入、誰的毛利、誰的護城河？ 這篇不是拆到每一根電纜的投行 BOM 模型，而是一張用公開資料建立的 v0.2 錢流地圖。它的目的不是假裝精準，而是把三件常被混在一起的事情分開來看：錢在哪裡變成營收、營收在哪裡變成毛利、瓶頸何時鬆解。 因為這三題的答案，往往不是同一批公司。 一、AI Capex 不是一個數字，是一組水管 Reuters 引述 Bridgewater 的估計：Alphabet、Amazon、Meta、Microsoft 四大 2026 年的 AI 基礎設施投資約 US$650B，高於 2025 年約 US$410B。先講清楚一件事——這是四大的地板數，不含 Oracle、Stargate、CoreWeave 這類 neocloud、xAI，也不含任何非美系業者。所以 $650B 是四家公司的下限，不是市場總額。 錢不會平均落下，而會進入性質不同的系統層支出。設備與材料則屬二階供應商 capex，不計入 hyperscaler 直接支出，以避免重複計算。 關鍵是——設備與材料（ASML、AMAT、TEL、Advantest…）不在這 $650B 裡。 那是台積電、SK Hynix 的資本支出，是二階供應商支出、是另一個分母。把它加進 hyperscaler 支出裡相加，就是 v0.1 犯的、也是很多市場圖表仍在犯的 double counting。 二、把箱子打開：成本重心已經從邏輯移到 HBM + 封裝 把「Compute Systems」這條水管打開，你會看到這一輪最反直覺的結構變化。 ...

繁體中文版：AI Capex 錢流地圖 v0.2｜美國出錢，誰真的收得到毛利？ The AI Capex Money Map v0.2 — America Spends. Who Actually Keeps the Margin? From $650B to HBM, CoWoS and power — mapping who gets paid, who keeps margin, and when the bottlenecks move. (The capex waterfall, cost-stack, bottleneck-clock, and regional margin-capture charts are figures in the original Medium version; this text edition keeps the surrounding reasoning — see Medium for the full visual breakdowns.) Most people are asking whether AI is a bubble. It is an important question, but not a very operational one. ...

From “What’s the next AI stock?” to “Where’s the next bottleneck, who gets paid, and what would prove us wrong?” Sinclair Huang This essay helps answer four practical questions: Which AI themes are real constraints rather than just attractive stories? Who can capture gross margin when a constraint binds? How long might the bottleneck last before capacity, substitution, or efficiency relieves it? What evidence would prove the thesis wrong? The main argument: large AI demand explains why the sector is hot; bottlenecks explain who gets paid; spillovers explain who absorbs hidden costs; monetised usage determines whether the buildout is sustainable. ...

Why is everyone suddenly talking about CoWoS, HBM, and ABF whenever AI, NVIDIA, or AI servers come up? Many people know they are important, but still get stuck the first time they run into these terms. This essay is a plain‑language walkthrough of what they actually are, why they are always mentioned together, and how they map onto Taiwan’s role in the global AI supply chain. When Google, Amazon, and Tesla are all designing their own chips, is Taiwan’s manufacturing ecosystem still structurally important — or just enjoying a temporary window? ...