The Subprime Data Center Crisis
- URL: https://www.wheresyoured.at/the-subprime-data-center-crisis/
- Source: blog
- Author: Ed Zitron
- Local evidence: OpenClaw定时任务/AK-RSS-Digest(89源精选)/2026-07-23-AK-RSS-Digest.md
- Fetch method: opencli web read
- Added: 2026-07-23
中文摘要
文章用 CoreWeave、Meta、Google、BlackRock 等案例说明,数据中心项目常由独立实体融资,客户合同、GPU 资产和债务被放进项目公司,现金流断裂时风险路径会变得不透明。它的价值不在“AI 泡沫”结论,而是提醒读者跟踪 off-balance-sheet obligations、debt service coverage、customer concentration 和建设延期。
One-liner
判断 AI 数据中心风险,要看 SPV、偿债覆盖和客户集中度,而不只看“算力需求”。
Obsidian evidence excerpt
个实例难以在野外存活。随后提出 open-weight 逃逸路径:模型获得权重、包装成新实验室发布物,推理平台为了抢流量主动部署,扩散一旦发生就很难回收。
链接:https://seangoedecke.com/powerful-ais-might-escape-by-releasing-open-weight-models/
- 标题:The Subprime Data Center Crisis
评分:8.2/10
推荐语:Ed Zitron 这篇很长,也有他一贯的强情绪,但正文里有足够多的财务结构细节:AI 数据中心债务通过 SPV、VIE、租赁和非追索结构被拆开,风险不一定完整留在大厂资产负债表上。把 AI capex 和 2008 年 CDO 类比不一定完全严丝合缝,但它提供了一个值得盯的观察点:算力需求叙事正在被金融结构放大。
摘要:文章用 CoreWeave、Meta、Google、BlackRock 等案例说明,数据中心项目常由独立实体融资,客户合同、GPU 资产和债务被放进项目公司,现金流断裂时风险路径会变得不透明。它的价值不在“AI 泡沫”结论,而在提醒读者看 off-balance-sheet obligations、debt service coverage、customer concentration 和建设延期这些具体指标。
链接:https://www.wheresyoured.at/the-subprime-data-center-crisis/
- 标题:What's the deal with all the random weekly quota resets for agents lately?
评分:8.0/10
推荐语:Max Woolf 把一个看似很小的产品现象写成了 agent 商业模式观察:Codex、Claude Code 这类订阅制工具频繁重置周额度,短期像补偿,长期会改变重度用户的使用节奏和付费判断。文章最有意思的地方是把 quota reset 当成竞争手段看:当 frontier model 发布密集、替代品变多时,平台可能用免费额度把 power user 留在自己的 harness 里。
摘要:作者记录了 Codex 两周内多次周额度重置,以及随机重置给重度用户带来的反直觉体验:既像免费福利,也会制造“没用完就浪费”的焦虑。它给 agent 工具产品一个很具体的提醒:配额、重置时间、可见性和 API 化查询,会直接影响用户是否升级、降级或转去竞品。
链接:https://minimaxir.com/2026/07/agent-quota-reset/
## 未入选但已读
- Martin Alderson 的 Hugging Face / OpenAI
Fetched source / metadata
The Subprime Data Center Crisis
发布时间: 2026-07-22T16:08:51.000Z
原文链接: https://www.wheresyoured.at/the-subprime-data-center-crisis/
Thanks for reading this week’s free Where’s Your Ed At newsletter. Friday’s premium newsletter will ask the simple question: Is Oracle dying?
It’s been one year since I launched the premium newsletter, and I’ve decided to extend the discount on annual subscriptions. Between now and 12AM ET, July 26, you can get a permanent annual rate of just $60— a $10 discount on the usual price of $70 — for life. **Click here for the offer**.
In addition to getting access to the entire back catalog of premium posts, you’ll also receive one additional post each week — usually anywhere between 10,000 and 20,000 words — covering the most pressing topics in the AI bubble — the best value in tech analysis. Highlights include the **Hater's Guide To The Memory Crisis,** a guide to how AI made everything more expensive, **How OpenAI Kills Oracle** (which pairs nicely with **the Hater's Guide To Oracle**), **The Hater's Guide To NVIDIA**, The Hater's Guides To **Private Credit** and **Private Equity**, and how the entire **AI Compute Demand Story Is A Lie**.
- * *
Soundtrack: Dillinger Escape Plan — Black Bubblegum (2007)
In The Big Short, Mark Baum shook with anger as a CDO manager told him that the market for insuring mortgage bonds was about 20 times larger than the mortgage bond market, realizing in real-time that speculation driven by greed and hype had set up a massive systemic weakness under everybody’s noses.
To get specific, Baum (played by Steve Carell) is giving a short, dramatic summary of a much greater problem — that there were trillions of dollars of synthetic collateralized debt obligations (effectively bets on whether somebody else’s bucket of mortgages (well, mortgage bonds) will actually pay up) that allowed multiple people to bet on the same mortgages again and again, meaning that once said mortgages went belly-up, the carnage would be widespread and hard to contain.
This became even more chaotic when it became clear that the same mortgage bonds were attached to many different CDOs — one study found that 5500 different mortgage bonds had been placed or referenced in CDOs over 36,000 times. A mortgage bond (or mortgage-backed security) is a slice of a pool of payments from thousands of mortgages, with each slice sold off to different buyers at different levels of seniority, the most-senior ones getting paid first and taking losses last.
In the end, the only thing you really need to know is that financial institutions built CDOs that threw together bonds in ever-more complex and dangerous ways, selling synthetic CDOs to bet on the outcomes, with different CDOs having different bonds covering the same pools of mortgages — bonds that were routinely rated by agencies at a higher grade than they should’ve been. When IMF Chief Economist Raghuram Rajan attempted to warn the financial services industry at the Kansas City Fed’s 2005 Jackson Hole symposium about the instability of the system, former US Treasury Secretary (and close friend of Jeffrey Epstein) Larry Summers referred to his concerns as “misguided.”
Meanwhile, the industry was handing out awards. On July 1, 2005 Lehman Brothers would receive one of Euromoney’s “Awards For Excellence,” where it was named the “Credits Derivatives House Of The Year.” Euromoney also referred to Lehman, a financial institution that was leveraged 25.3x in 2005, as “one of the more conservative credit derivatives houses.” It added that the company, which routinely overvalued its CDOs, was being able to take on the heavy burden of synthetic CDOs because it “...understands the arbitrage-driven economics of cash CDOs, the way that loan deliverable credit default swaps track the loan markets, how high-yield CDS trade (like bonds), and so on.”
Three years later on January 1, 2008 — nine-and-a-half months before its collapse — Risk Magazine would name Lehman Brothers’ “Point” risk management system as its “In-House System of the Year,” saying it “...stood out for the breadth of its coverage and depth and quality of its functionality.”
All of this started because of a flood of overseas money in the early 2000s buying up U.S. Treasuries as a result of a “global savings glut” — a fancy way of saying that there was too much money floating around — pushing yields down, leaving investors with far fewer places to get those all-important yields.
Low interest rates in the early 2000s (a direct response to the collapse of the dot com bubble) dropped mortgage rates to “generationally low” levels, and financial institutions realized they had an opportunity, as government policies had allowed them to loosen underwriting standards at exactly the time that foreign investors were desperate for places to park their money — mortgage-backed securities, and their associated derivatives. More mortgages meant more mortgage-backed securities, so banks made it _incredibly_ easy to get a mortgage, to the point that in 2006, 20% of all new mortgages were subprime.
You’re probably wondering why nobody feared they’d get burned by this endless stack of different interconnected debts, and that’s because they’d “spread all that risk out” across credit default swaps with insurers, not realizing that insurers could and would become insolvent if everybody tried to make a claim at once.
This was all avoidable, and there were many warnings, and just as many people lining up to protect the grift. In June 2005, Larry Kudlow would say that housing bears were “wrong again,” dismissing those concerned with increasing default rates as “bubbleheads” that “don’t do their homework.” In September 2006, financier Michael Milken would refer to CDOs in the Wall Street Journal as a “financial innovation” that “helped to spread risk and create tens of millions of jobs by freeing up investment capital for growing businesses,” saying that they would “increase prosperity by multiplying the value of human capital, social capital and real assets.”
In other words, the argument was that the “financial innovation” of ever-expanding financial speculation was good for the economy because it created more money out of thin air, with the “risk” spread out _somewhere_, in a _way that you shouldn’t think about because everything is going to be fine._ Everybody would keep building houses forever, the numbers would only ever keep increasing, every new house would add a new mortgage to a new mortgage-backed security, and the line would only ever go up.
To put it all very simply, the great financial crisis was caused by inflated demand for housing caused by a mixture of historically-low interest rates and banks incentivizing bad habits as a means of increasing the value of speculative assets. In the end, “mortgage-backed securities” stopped existing as ways to invest in large swaths of mortgage payments, and more as high-risk financial vehicles that promised to be an infinite money glitch where nobody could lose because there would always be more demand for mortgages _and_, by extension, _collateralized debt obligations made up of mortgage-backed securities._
It all broke because eventually those speculative assets had to interact with the real world, by which I mean mortgage defaults began to spike starting in 2005 with the expiration of teaser rates and multiple fed rate hikes throughout 2006 making adjustable-rate mortgages creep upwards. As mortgages collapsed, CDOs — and their connected synthetic CDOs — collapsed with them, crushed by the weight of the consequences of offering so many people so many mortgages under volatile and unrealistic terms, and assuming that nothing bad would ever happen _because nothing bad had happened yet._
And, fundamentally, the great financial crisis was caused by massive speculation based on demand that was, in and of itself, an illusion created by the financial institution itself to justify further investment.
Say, that kinda reminds me of something!
Data Center SPVs Are The AI Bubble’s CDOs
I realize that the comparison between an AI data center and a CDO might seem a _little ridiculous_, but they’re actually remarkably similar. I’m going to generalize here, because each of these deals has weird little unique terms that make them, well, _more dangerous._
- When somebody decides to build an AI data center, they form a special purpose vehicle (much like a CDO), which then raises debt, in some cases slices it into tranches and, in most cases, sells them to institutional investors, asset managers or banks.
- Think of the SPV as its own little company (owned by the holding company, CoreWeave for example), and when somebody signs a contract with an AI data center company (say, OpenAI), they actually are signing a deal with the _SPV_ rather than the company itself.
- When the SPV receives the funds from the debt raise, it makes payments to contractors and suppliers (EG: NVIDIA for GPUs), and receives the revenue from the customer contract, assuming said customer is paying (or has anything to pay for).
- During construction (IE: pre-revenue), interest payments are taken out of the SPV from a pre-funded interest reserve account.
- When a customer pays, the SPV uses those funds to pa