It breaks down the full picture and what he’s telling friends/family to do.
What do you make of this shift?
All the best,
Pete Campbell Publisher, TrendLabs
P.S. JC says this “Chaos Cycle” isn’t just stocks – it might explain a lot of the geopolitical stuff we’ve seen lately, like moves on Venezuela, Iran, and more. Eye-opening stuff.
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a popular, lively tavern located at 2626 Wilshire Boulevard in Santa Monica during the 1960s-1990s, renowned for bawdy sing-alongs led by owner Bill “The Fox” Foster. It was a legendary hangout for college students and rugby players, featuring grandstand seating, beer chugging, and a tavern-style atmosphere. Facebook +3
Key Details About The Fox Inn (Historic):
Atmosphere: Known for its high-energy, “rowdy” atmosphere with communal singing of bawdy ballads, children’s songs, and chants like “Ziggy Zaggy Oi Oi Oi”.
The Act: Bill “The Fox” Foster often performed after downing pitchers of beer, famously singing to patrons, including specialized songs for those leaving to use the restroom.
Legacy: The venue was a staple for USC and UCLA students, as well as the Santa Monica Rugby Club.
Location: It was situated on Wilshire Blvd, directly across from The Horn nightclub.
People took out thousands of dollars in cash in fear that ATMs wouldn’t work.
Thousands canceled flights because they believed planes might simply fall out of the sky.
Stores across the globe sold out of generators, bottled water, and cans of Spam.
For younger folks, it may sound crazy, but the panic over the so-called Y2K bug was very real.
At the turn of the millennium, people around the world feared computers would crash on January 1, 2000 — misreading the “00” date as 1900 instead of 2000.
The problem was real. And real money was spent to solve it.
The Clinton administration said in December 1999 that preparing the U.S. for Y2K was probably “the single largest technology management challenge in history.”
Researchers at Gartner estimate the global cost of Y2K remediation — across governments and private companies — totaled between $300 billion and $600 billion.
In the end, the remediation worked. Aside from a few minor glitches (and perhaps a lingering surplus of canned Spam), the world’s technology systems continued running smoothly.
But while the public worried about computers crashing…
… another problem was quietly forming behind the scenes.
We had to move so quickly at the turn of the century largely because of the tech boom leading up to it.
The dot-com surge triggered a massive buildout of internet infrastructure, and that buildout required enormous quantities of raw materials.
So while consumers were stockpiling supplies…
… tech companies were scrambling to secure metals.
During the late 1990s and early 2000s, the tech boom triggered a surge in demand for critical materials used in electronics and networking equipment:
Copper – to carry electricity and data
Tin – used in electronic soldering
Gold – used in corrosion-resistant connectors
Rare earth elements – used in disk drives, displays, and fiber optics
The explosion of internet infrastructure, personal computers, and networking hardware meant the world suddenly needed far more metals than usual.
But mining and refining capacity couldn’t expand overnight.
The result was a classic supply bottleneck.
Prices for semiconductors and other hardware spiked. Companies like Cisco Systems Inc. (CSCO), Intel Corp. (INTC), and Dell Technologies Inc. (DELL) faced growing lead-time issues that slowed product rollouts.
But this metals shortage also created hidden investment opportunities.
Investors who anticipated which resources would become scarce had the chance to profit in extraordinary ways, much like investors who recently benefited from Nvidia Corp.’s (NVDA)nearly 1,000% gains during the AI compute bottleneck.
From 1998 to 2001, I recommended four mining stocks to my readers that went on to generate remarkable gains. These companies became the quiet winners of the late-1990s tech boom.
Today, let’s take a closer look at them — and how identifying a supply bottleneck early created enormous upside.
Then I’ll show you how this same profit-making “bottleneck” cycle is unfolding again thanks to AI… and where investors still have time to position themselves.
When bubbles pop, money flees hype and moves to quality. Futurist Eric Fry is sharing a list of “Buy Now” names that everyone could benefit from. These “AI Survivors” are the stocks you want to be in before the bubble pops. Get the list of free names and tickers here.
When the Internet Needed Copper
Back during the dot-com era, Antofagasta plc (ANTO.L) was not yet the global copper giant it is today.
In the mid-1990s, the company was still a diversified Chilean holding company involved in railways, finance, and industrial businesses.
But in 1996, Antofagasta spun off many of its non-mining assets into Quiñenco SA, one of Chile’s largest conglomerates.
That move transformed Antofagasta into a copper-focused mining company — just as the internet boom was beginning to drive enormous demand for the metal.
During the late 1990s, the company began developing the massive Los Pelambres copper mine in Chile’s Coquimbo Region. Construction started in 1997. Initial production began in 1999. By 2001, the mine had reached full capacity.
Los Pelambres quickly transformed Antofagasta from a relatively small mining group into a major global copper producer. In the early 2000s, the mine accounted for roughly three-quarters of the company’s revenue.
I recommended Antofagasta to my readers on December 18, 1998 — about a year before the mine began production.
Over the next three years, the stock soared 205%, while the S&P 500 was essentially flat.
Over six years, Antofagasta delivered an astonishing 778% gain, while the S&P continued to nurse its losses, down 27%!
Antofagasta built capacity during the investment phase of the 1990s, and then benefited enormously once the metals bottleneck tightened.
But it wasn’t the only copper producer positioned to win.
While tech companies were building the internet, companies like Freeport-McMoRan Inc. (FCX) were supplying the physical materials that made the emerging digital world possible.
Freeport’s crown jewel was the Grasberg Mine in Indonesia, one of the most important copper and gold mines on Earth.
Because Grasberg was already operating at scale, Freeport could immediately ramp up production as demand surged. The company didn’t need to build new capacity to benefit from the bottleneck — it simply needed to keep producing.
I recommended Freeport to my readers on April 26, 1999.
Over the next three years, the stock rose 37%, while the S&P 500 slumped 18%.
Over six years, Freeport soared 193%, while the broader market lost 7%.
Copper wasn’t the only opportunity of the time…
The Other Metals That Made Investors Rich
During the late 1990s, Cameco Corp. (CCJ) controlled some of the richest uranium deposits in the world in Canada’s Athabasca Basin.
Its McArthur River and Key Lake mines had extremely high uranium grades, giving Cameco some of the lowest production costs in the entire industry.
Now, uranium wasn’t central to the internet infrastructure buildout. Prices were relatively weak during most of the dot-com era. So you might wonder why Cameco belongs on this list.
The answer is simple: cost advantage. Because its deposits were so rich, Cameco remained profitable even during periods of weak uranium prices.
Then, shortly after the dot-com era ended, uranium experienced its own supply crunch. And Cameco was perfectly positioned to benefit.
I recommended the company to my readers on July 9, 1999.
Over three years, the stock rose 36%, while the S&P 500 declined by nearly 30%.
Over six years, Cameco rocketed 640% as the S&P was still 5% underwater.
My final bottleneck winner came from another corner of the mining world.
Impala Platinum Holdings (IMPUY) was one of the largest producers of platinum-group metals in the world.
These metals — platinum, palladium, rhodium, iridium, and osmium — are used in:
automotive catalytic converters
electronics components
chemical processing
petroleum refining
During the late 1990s, demand for these metals increased sharply as global manufacturing expanded. Meanwhile, tightening emissions standards increased demand for catalytic converters.
The price of platinum surged from roughly $350–$400 per ounce to more than $600. Because Impala was already a major supplier, those rising prices flowed straight into the company’s profits.
I recommended Impala on March 30, 2001.
Over the following three years, the stock rose 176%, compared to just 2% for the S&P 500.
Over six years, Impala soared 872%, while the S&P gained only 36%.
The lesson is clear.
During major tech booms, materials and infrastructure often become bottlenecks.
And the companies that control those bottlenecks can generate extraordinary returns.
Where the Next Bottleneck Is Forming
Today, we’re seeing something very similar unfold during the AI Revolution.
Artificial intelligence requires enormous quantities of infrastructure, including chips, electricity, memory, and critical metals.
And whenever demand for infrastructure rises faster than supply can respond, bottlenecks emerge.
For investors who identify them early, the upside can be highly asymmetric.
In general, I look for four things:
Where demand is overwhelming supply
Which companies control the choke point
Whether increasing supply will be easy or difficult
And whether the market has recognized the opportunity yet
Of course, identifying these bottlenecks in real time is easier said than done.
But right now, several new constraints are beginning to appear across the AI supply chain.
And the companies positioned to solve those constraints could become some of the biggest winners of the next phase of the AI boom.
During this free broadcast, I’ll explain why new shortages in metals, electricity, and memory could soon become the next major bottlenecks in the AI Revolution.
I’ll also reveal 15 companies already positioned to benefit from these developing constraints.
If history is any guide, the next Nvidia Corp. (NVDA)-style winner may not come from AI software — but from the companies solving AI’s biggest infrastructure challenges.
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