- Investors think Nvidia is more creditworthy than the U.S. government…
- Why AI isn’t the 21st century railroad…
- CNBC called this new Elon Musk opportunity “the big market event of 2026.” Elon Musk is predicting this investment could jump 1,000x higher from here.
Dear Reader,
The Kiyosaki Letter:
- Investors now perceive Nvidia to be as creditworthy as the US government.
- Nvidia’s 5-year credit default swap (CDS) is trading at ~38 basis points, slightly below the US sovereign CDS, at 40 basis points.
- In other words, markets consider the world’s largest company to be less likely to default on its obligations than the US federal government.
I would merely add — and will add — one central stipulation.
The U.S. Won’t Technically Default
The United States government will not default on its obligations. Not officially, that is.
That is because it maintains access to a machine… these days a largely figurative machine… known commonly as a printing press.
Thus it can meet all its obligations, in nominal terms at least.
Its creditors may receive cents on the dollar — sawdust, that is — yet they will have their money in nominal terms.
Nvidia, meantime, lacks all access to this source of monetary mischief, the printing press.
Thus its default would represent an honest default. It contrasts greatly with Uncle Samuel’s dishonest default.
Yet the central point stands in place:
Investors presently place higher trust in a business concern than the government of the United States.
Spending on Data Centers Now Exceeds Gov’t. Spending on Transportation
The Kobeissi Letter likewise informs us that money consecrated to the construction of United States data centers recently scaled an annualized $50 billion.
Government spending on transportation, in comparison, registered $49.9 billion.
That is, data center construction spending presently exceeds government transportation spending.
Never before has that situation obtained — never.
Yet many artificial intelligence enthusiasts claim the vast expenditure is justified by the facts.
They often liken today’s artificial intelligence infrastructure to the 19th century’s railroad infrastructure.
As the railroad transformed 19th century America, they bellow, artificial intelligence will transform 21st century America.
Yet will it? Are the likenesses valid… or largely phantom?
The 19th Century’s “Can’t Lose” Investment
Economics commentator Charles Hugh Smith is far from convinced the likenesses are valid.
Or rather, that the likenesses are valid in a fashion unrecognized by the artificial intelligence drummers.
Mr. Smith — who has certainly not gone to Washington — argues that:
- The completion of the first transcontinental railroad in late 1869 sparked a speculative mania of raising capital to build railroads, which were seen as “can’t lose” investments in a technology that lowered transport costs from $1 to ten cents.
- But not all routes had the potential to become profitable, and the resulting collapse of the railroad bubble devastated the developed-world economies, triggering a deep economic downturn from 1873 to 1879 that was called “The Great Depression” at the time (or “The Long Depression”).
“Malinvestment”
Yet the vast expenditures on railroad represented not overinvestment, but malinvestment.:
- The term for speculative frenzies channeling vast sums into investments with difficult-to-assess risk profiles is mal-investment, and mal-investment on a large scale triggers financial panics and economic depressions in a well-understood feedback loop.
- And so, Mr. Smith, please sketch a parallel between railroads and artificial intelligence:
- The parallels with the AI speculative investment mania are obvious. Just as any railroad was viewed as guaranteed to be immensely profitable because railroads generated enormous efficiencies that reduced costs, all AI is guaranteed to be immensely profitable because AI generates enormous efficiencies that reduced costs…
- Those are the parallels of the railroad mania of the 1870s and the current AI mania. But that’s only half the story.
The Other Half of the Story You’re Not Being Told
Only half the story? Please then direct us to the story’s second half:
- Railroads did dramatically lower costs, turning unprofitable ventures into profitable ventures not by reducing production costs but by reducing transport costs, which prior to railroads might equal production costs.
- The differences between railroads and… generative AI are significant. While many railroads went bankrupt when the bubble burst, those that actually served expanding markets were eventually put to use as the tracks were still useful many years after being laid.
- A new locomotive type might enter service decades later, but the tracks remained useful and valuable for decades — with proper maintenance. The rails were not obsoleted every few years, nor did the entire rail lines have to be replaced every few years.
Unlike, that is, artificial intelligence infrastructure:
- AI is not permanent. It is constantly being obsoleted. A new class of lower-power consumption chips could obsolete the current class of AI chips, requiring a mass replacement of the entire processing foundation of AI.
- Innovations in software could reduce the processing demands, turning existing data centers into expenses rather than profit generators. AI software that users download onto their own computers negates the need for “renting” data centers (i.e. buying processing power) by generating models from the user’s own data.
- These are just a few potential forces undermining the utility, lifespan and profitability of the current build-out of data centers.
Maybe AI Isn’t as Efficient as They Claim
Mr. Smith proceeds to cite additional reasons why artificial intelligence may breed not efficiency, but inefficiency.
For example, the cost of distinguishing between “good AI” and “bad AI” are mounting. That is, the mounting cost of extinguishing “AI slop.”
For example, the costs of running artificial agents often exceed the labor costs of the human beings they were designed to replace.
For example, the unforeseen future costs of maintaining artificial intelligence systems.
Mr. Smith, in disturbing conclusion:
- The sums invested in AI data centers — and committed to planned data centers — are on a large enough scale that even the most robust economy is vulnerable to disruption when the revenues needed to justify these extraordinary sums fail to materialize and the total operational costs and costs of ownership become measurable…
- AI data centers are not the railroads of today. The AI boom shares all the risk profiles of previous speculative manias but lacks society-wide benefits while generating fast-metastasizing negative consequences and costs.
“This Time Is Different” Is Why It’s Always the Same
As I have argued before:
“This time is different,” is the eternal refrain of investors. And it always is different — in the particulars.
A railroad boom is not a dot-com boom is not a housing boom is not an artificial intelligence boom.
As I have also argued before:
It is these particulars that fox and deceive investors. It is why they habitually believe this time is different.
That is precisely why it is always the same.
Regards,
Brian Maher
for Freedom Financial News
