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英伟达的冒险生意:从铁路泡沫到AI资本开支

英伟达的冒险生意

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AI资本开支与融资动态是行业核心议题,本文数据详实、视角独特,建议关注算力投资与云厂商格局的从业者细读。

Nvidia’s Risky Business

Tuesday, August 11, 2026

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On January 1, 1870, Jay Cooke, hailed as an American hero for his role in financing the Union effort in the Civil War, signed a contract that would, if you squint, lead to world war.

In 1864, Congress had created the Northern Pacific Railway Company with the goal of linking the Great Lakes and Puget Sound with tracks that would eventually run from Duluth to Tacoma; the charter included 40 million acres of land adjacent to the proposed line in exchange for accomplishing the build-out. For the ensuing six years, however, Northern Pacific struggled to secure financing, even as the Union Pacific and Central Pacific railroads built towards each other, driving the golden spike linking Sacramento and Omaha in May 1869.

Northern Pacific had approached Cooke about funding in 1866, but lacked the generous federal guarantees that undergirded Union Pacific and Central Pacific (which, it should be noted, led to an incredible amount of graft); Cooke, himself no stranger to the financial power of the federal government, wasn’t interested. Ultimately, however, Northern Pacific gave him an offer he couldn’t resist: a commission of 12 percent on every bond, and $200 of Northern Pacific stock for every $1,000 in bonds he sold.

Cooke soon found that his institutional peers agreed with his earlier refusal, and weren’t interested in his bonds, so he leaned on the same tactics he honed selling war bonds: appeals to patriotism, control of the media, and promises of railroad fortunes, backed by industrial-scale distribution. At the peak Cooke employed 1,500 salespeople and funded 1,300 newspapers (through a combination of advertising and direct payments) with a brand burnished by the Civil War. Retail investors could already buy railway bonds; Cooke made them his primary funding mechanism.

This was, to be certain, an incredible innovation. It used to be the case that if you couldn’t get loans from the government or from banks, you couldn’t get much money at all. The problem was that Northern Pacific’s capital needs were endless, and by September 1873, as credit tightened worldwide thanks to a crash on the Vienna stock exchange and the demonetization of silver, Cooke, who had been funding Northern Pacific from deposits in between bond issuances, could find no more buyers. The subsequent bankruptcy of Jay Cooke & Company triggered the Panic of 1873, culminating in endless railroad bankruptcies across the country, a multi-year depression, multi-decade deflation, and, one could argue, the financial conditions that made Europe, four decades later, into a tinder box.

Northern Pacific did eventually finish their line, by the way, with multiple bankruptcies along the way; ultimately, they were one of four railroads that were merged to form the Burlington Northern Railroad. Burlington Northern would eventually merge with the Atchison, Topeka and Santa Fe Railway to form BNSF Railway; Berkshire Hathaway would purchase the parent corporation in 2009.

Blowing Through Debt

If this story sounds vaguely familiar it might be because Cooke is — for obvious reasons — a central character in Liaquat Ahamed’s new book, 1873, released earlier this year. Ahamed is not shy about drawing a link between the collapse of the railroad buildout and the current AI moment; the book’s very first page — even before page 1 — is about translating sums of money, and concludes thusly:

In order to grasp the true significance of sums of money that relate to the economic situation of whole countries — such as the size of the indemnity imposed on France after the Franco-Prussian war — it is most useful not simply to make allowances for changes in the cost of living but instead to adjust for changes in the size of economies. To translate such figures into comparable 2026 magnitudes, multiply by a factor of 1,200. Thus the $500 million that went into U.S. railway bonds annually during the boom years of the early 1870s would today be the equivalent of $600 billion, roughly what is projected to be invested by major tech companies in 2026.

Microsoft CEO Satya Nadella is certainly aware of the connection: he cited 1873 as “the book to be read” on the company’s recent earnings call. Perhaps it’s not a coincidence, then, that Microsoft, alone amongst the hyperscalers, still boasts substantial free cash flow — $19.6 billion last quarter. Microsoft is the one hyperscaler still abiding by the dictum used to deny the existence of a bubble: its CapEx isn’t funded by debt.

This was, believe it or not, a defense that could be used for nearly all of Big Tech a year ago; then, between September and November, Oracle, Meta, Alphabet, and Amazon issued a combined $80 billion in debt for building out infrastructure. That was only the beginning: after raising a combined $108 billion in all of 2025, these four companies have, as of July 7, already raised $194 billion this year. Unsurprisingly, spreads are rising, and 86% of the bonds issued this year are already trading at higher yields than at issuance. Cover for recent issuance has fallen to less than 2x, from 5x in February.

The real shock, however, came at the beginning of June, when Google announced it would raise $85 billion in equity, including a special $10 billion issuance to the aforementioned Berkshire Hathaway. I wrote at the time in The Google Capital Company:

It is worth noting that $10 billion is a relatively small amount of money to both companies. To that end, perhaps the primary utility is as a signaling mechanism. On Google’s side, the signal is that the expected demand is actually far greater than anyone thinks, and that the company is ready and willing to fund supply using all means at its disposal, including equity; for them Berkshire Hathaway’s investment is an endorsement of this view and a validation of the wisdom of the investment. And, on the flip side, if the signal is correct, then Berkshire Hathaway is getting a deal and putting its cash flow machines to work building the future.

I concluded:

Implicit in this analysis was that there was enough compute capacity in the world to be bought; what happens, however, when and if there isn’t? What if the ultimate battle — the one that determines who gets compute — becomes a matter of who can bring the most cash to bear? And what if that advantage compounds, such that the company with the most cash capacity ends up with the most compute capacity (which we already know they will sell, in addition to using themselves) driving the ability to generate more cash? In that world, what company would be your best bet?

The implied answer, of course, was Google.

DeepMind Drama

Google right now is no one’s bet, at least in terms of the frontier. After the departure of DeepMind CEO Demis Hassabis (technically promoted to chairman, but no longer in charge of day-to-day operations) and Gemini co-lead and former Chief Scientist Jeff Dean, along with a host of other prominent researchers, SemiAnalysis declared that Gemini is Cooked:

For all intents and purposes, we believe DeepMind is no longer a frontier lab. We said as much a few months ago to our Tokenomics clients due to large numbers of departures from their reinforcement learning teams and poor compute allocation. Google will continue meandering on and releasing models, but their odds of reaching SOTA again have dropped to zero.

Furthermore, the biggest beneficiary of today’s news is neither Anthropic nor OpenAI—it’s Google Cloud. Whereas Gemini and GCP used to desperately fight for compute allocation, it’s now clear that Thomas Kurian won. We expect GCP revenue growth to meaningfully accelerate as a result.

From later in the post:

We’ve obviously been quite bearish on DeepMind thus far, and if we had to steelman the case for why they’ll still be able to train a true SOTA model in the future, it would go something like the following:

更进一步:量化金融体系

看懂新闻只是起点——沿量化金融路径,把它变成能交付的工程能力

进入量化体系 →

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