Nvidia's Risky Business was published on Tuesday, August 11th, 2026. Good morning. On January 1st, 1870, Jay Cooke, held 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 6 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, went 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% 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 in 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 tinderbox.
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 one, 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 US 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 2025, these four companies have, as of July 7th, 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 issuances 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, quote, "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. End quote.
I concluded, quote, "Implicit 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? End quote." 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 state of the art 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.
We've obviously been quite bearish on DeepMind thus far, and if we distill the case for why they'll still be able to train a true state of the art model in the future, it would go something like the following. The current setup clearly wasn't working. With the existing leadership team, their odds of catching up to Anthropic or OpenAI look extremely slim. Now that they've cleaned house, the new guys can start from a blank slate. Maybe they'll even acquire a new lab like SSI or Thinking Machines. With this new team, their odds of catching up to the frontier actually increase. Perhaps there's some world in which this happens, but we think the odds are basically zero. The issue with Google was not Jeff Dean nor Noam Shazeer, but rather their extremely bureaucratic, painfully slow, and strategically timid culture. Remember that DeepMind had an AI chatbot 1 year before ChatGPT, but was not allowed to release it due to fears of disrupting their core business.
Actually, you could make the case the problem was also Hassabis and DeepMind. I explained it in an update for Google I/O how Hassabis' vision of the frontier was fundamentally different from the other frontier labs because he believed in world models, not just text and code, and concluded, quote, "What falls out of Hassabis' vision are models with multimodality, in contrast to Claude, which outputs text only. And it must be said, not nearly as impressive coding capabilities." This gets to the point of this entire digression. I think it's possible that the reason Google was widely considered to be behind both Anthropic and OpenAI in terms of coding, particularly long-running agentic workflows that depend just as much on the harness as the model itself, simply comes down to their research team having other priorities. That's why the coding parts of this keynote fell on the anti-gravity team, not DeepMind, and why Hassabis was barely on stage, end quote. From this perspective, last week's events are less surprising, and were arguably foretold at I/O.
Hassabis might be right about world models being the path to AGI, but Google has run out of patience in terms of letting him find out. Google co-founder Sergey Brin is reportedly deeply involved and closely allied with Koray Kavukcuoglu, the new DeepMind CEO, and I won't be surprised if the company is pivoting to Anthropic's more text, and thus code-centered approach.
Google's infrastructure bet. What is fascinating about Google's position is that these machinations do not necessarily mean the Berkshire Hathaway bet was a bad one. Indeed, it's arguably good news. This is what the SemiAnalysis article is driving towards, and it's a point I made last week about Google's recent earnings, quote, "The story seems to be very similar to last quarter, with even more Google Cloud growth, 82% year-over-year, compared to 62% last quarter, and 32% a year ago, with 36% margins, compared to 33% last quarter, and 21% a year ago. I wondered then how much of this growth was actually Anthropic, and while we didn't get clear confirmation this quarter, I thought this answer from CEO Sundar Pichai in the earnings call about why Google needs to rent third-party capacity was notable.
I think on the, on the Broadcom deal, the main thing I would say is, look, there are, on the margin, there are very, very large customers of ours on, on cloud who we, we are trying to support them through this extraordinary moment and, and, and the incremental opportunities they are bringing to us. While a short-term cost over a few months may be very high, in the lifetime of the deal, as we bring more capacity on, is highly ROI positive, right? So, those are factors we are taking into account. So, are you willing to, you know, take upfront six-month deal to, to be able to serve that customer in what is a multi-year opportunity where the margins and the returns are very, very attractive over that multi-year horizon? So, hopefully that gives some color on how we thought about those opportunities.
That customer is almost certainly Anthropic. End quote. Again from SemiAnalysis: More than 20% of total TPU shipments from Q3 2026 to Q4 2027 are being sold directly to Anthropic. This is excluding the hundreds of thousands of TPUs GCP already rents to Anthropic today and the many hundreds of thousands more they've committed to rent to Anthropic and Meta over the next six quarters.
If you've ever listened to an interview of Google Cloud CEO Thomas Kurian, you know he's not AGI-pilled. In one podcast, for example, he argued that it's great for TPUs to become, quote, "general purpose infrastructure," end quote, that supports customers like Citadel, the Department of Energy, and generic high performance computing. And when asked why he was selling compute to Anthropic despite them competing with Gemini, he said this was the natural consequence of Google being a platform company.
Kurian said the same thing to me in the Sharp Tech interview.
