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Beneath the Surface

Too Much of a Big Nothing

Loading ...Bill Bonner

August 5, 2025 • 4 minute, 44 second read


big techmarket concentrationmarket valuation

Too Much of a Big Nothing

“During the dot-com days, one could take just about any company public and reap fortunes. All you had to do was to make sky-high projections for growth, say you were in the Internet space, and go along with unscrupulous investment bankers and their analysts.”

— Vivek Wadhwa

August 5, 2025 — Two companies — Nvidia and Microsoft — each are worth more than $4 trillion. Together, that’s more than India’s and Japan’s combined annual output.

Price is what you pay, as Buffett puts it. Value is what you get. Our question for today: how much value will investors really get from the Magnificent 7?

Our Law of Conservation of Value tells us that prices cannot stray too far or too long from value. And value depends on output. Investors ought to be able to look to a future stream of income and from it earn their money back…and more.

Even in the dot-com bubble in 1999 the top companies were not as valuable or as concentrated as they are today. Nvidia, Microsoft, Alphabet, Apple Meta, Tesla and Amazon — together, these companies make up a third of the total US stock market value, an amount roughly equal to China’s GDP.

Part of the appeal of these Mag 7 stocks is that they are widely believed to be taking advantage of AI technology. In the case of Nvidia, of course, that is the central appeal. But the others are investing heavily in AI too.

In 2024 and 2025, Meta, Amazon, Microsoft, Google and Tesla will put more than half a trillion into AI. The revenue from these investments is expected to be around $35 billion. Amazon, for example, has invested more than $100 billion, which is thought to generate an extra $5 billion in revenue.

We don’t know how reliable or meaningful these figures are. What we do know is that they aren’t very impressive. As in the dot-com boom of the late ‘90s, AI is not paying off. This is an in-put story, with huge investments made in the hope of creating AI-based wealth. But so far, the output doesn’t measure up.

You can go to ChatGPT, for example, and pay for the service. Many people use it occasionally — including us. But few pay for it — also including us. This would be fine, except that so much investment has gone into AI development that anything less than spectacular results will look like failure. One estimate, from Goldman Sachs, for example, showed that the Mag 7 would have to produce $600 billion in extra annual revenue to make sense of their investment.

Michael Roberts:

So while the excitement of AI takes the stock market to new heights… a huge investment of money and resources, astronomical payments to AI trainers, and the construction of huge data centers [there]…so far no significant revenue has been generated and there is almost no profit. This is a steroid-friendly version of the dot-com bubble.

The appeal of the dot-com era was the idea that more information would lead to higher GDP growth rates with less need for capital investment. Costly trial-and-error expansion would be replaced by less costly, more precise, knowledge-driven growth, or so it was believed.

It didn’t work out that way. Productivity and growth rates generally softened throughout the 21st century. Capital investment went down. The Internet/Information Revolution did not compensate for the decline; it seems to have made it worse. The OECD adds detail:

In the last half century, we have filled offices and pockets with increasingly faster computers, but the increase in labor productivity in developed economies has declined from about 2% annually in the 1990s to 0.8% in the last decade. Even the production per worker of China, which once increased rapidly, has stopped. Research efficiency has decreased. Today, the average scientist produces less groundbreaking ideas per dollar than his colleagues in the 1960s. Despite the rise of intangible assets, total investment has generally been weak since the global financial crisis, which has directly worsened the slowdown in labor productivity.

Will that change with AI? Probably not. The defining curse of the Information Revolution was too much information. It piled up. It got distorted and misinterpreted. It took time and money to store and sort. And much of it was either false or useless.

Now cometh AI, adding to the too-much-info problem. Already, it generates news and reports that fill our in-boxes and waste our time. And an Israeli company just announced that it can twist and turn (distort) the news in real time.

Which leaves, at least for now, AI and the Mag 7 in an old-fashioned financial bubble. Stock prices are far higher than actual sales and profits can account for. So one way or another price and value will have to come back together. While it is not impossible that some breakthrough will lead to a big burst of productivity gains and growth, it is more likely that stock prices will fall.

Regards,

Bill Bonner
Bonner Private Research & Grey Swan Investment Fraternity

Continued Below…

P.S.: Bill’s insights echo ours – we’re still mindful that markets may not decline right away. And that any decline we do get may be of the garden-variety seasonal pullback.

But a high concentration in just a few stocks – widely owned by investors specifically, or as the biggest components of passive index ETFs – pose a growing danger.

And that’s not even taking into account economic concerns like a slowing job market, stubborn inflation, and President Trump’s ongoing Great Reset of the American economy, which will have some bumps along the way.

Hence our suggestion to take some profits off the table and increase your cash position slightly.

Your thoughts? Please send them here: addison@greyswanfraternity.com


Autonomous Weapons

October 29, 2025 • John Robb

In the past, weapon systems took decades to build and changed slowly. Autonomy changes this. For example, new capabilities developed by field tests or simulation (testing scenarios in full physics simulators depicting actual environments) could be downloaded to existing weapon systems, making it possible to upgrade a weapon system significantly without any meaningful hardware changes. A process of improvement that used to take many years would shrink to weeks and, in time, days.

Autonomous Weapons
The Great Repricing of Power

October 29, 2025 • Addison Wiggin

Markets heard what they wanted. NVIDIA’s stock surged premarket on news that Trump would discuss the company’s Blackwell AI chip with Xi, pushing it to an unprecedented $5 trillion valuation.

Meanwhile, China quietly bought its first cargoes of U.S. soybeans this season — a symbolic gesture that reminded traders that diplomacy still runs on trade.

“It’s not détente,” wrote  Bloomberg’s Jennifer Welch this morning, “It is a dealmaking with a timer.” Wall Street is ambivalent on peace, but they do like profits.

In the background, China’s biotech sector continues its ethically murky sprint forward — this week, reports surfaced of Chinese scientists creating monkeys engineered to exhibit schizophrenia and autism.

The Great Repricing of Power
About Yesterday’s Rally

October 29, 2025 • Addison Wiggin

A high concentration of capital in a few stocks at the top ranks high among the features we detailed in Anatomy of a Stock Market Bubble.  

On days like yesterday, headlines urge investors to buy. However, they also underscore the fragility of this terrifying bull market: just a handful of names can make the difference between a big up day and a big down day.

About Yesterday’s Rally
American Autonomy

October 28, 2025 • John Robb

America’s role in the world isn’t that of the world’s policeman (a temporary post-World War II role foisted upon the U.S. due to the Cold War) or as the destination of immigrants (for most of the 20th century, when we saw the most significant increases in individual incomes and quality of life, the U.S. didn’t accept many immigrants). Instead, the role the U.S. has played throughout its existence is as the world’s leader in the production, adoption, and socioeconomic integration of new technologies. We figured out how to do it successfully first, and the world followed.

American Autonomy