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Why Today's AI Boom Differs From the Internet Bubble
AI: The Largest Industrial Buildout Since the Railroad
As a percentage of GDP, the current artificial intelligence buildout is the largest industrial buildout since the American railroad buildout of the 19th century.
Image Source: EpochAI
However, for many investors, the pain and the memory of the late-1990s internet boom and the subsequent bust 2000 bust are still fresh in their minds. Which begs the question for investors: “What part of the AI cycle are we in currently?” In today’s commentary, I will be contrasting the AI boom to the internet boom of the 1990s, providing evidence and data that underscored my belief that we are merely in the third inning of nine in the AI boom.
AI: There is No “Dark Fiber”
During the dot-com bubble of the late 1990s, telecom companies invested more than $500 billion (financed through cheap corporate debt) to dig trenches across land and under oceans, believing that internet traffic would create permanent demand for bandwidth. However, these telecom companies overestimated the need for fiber and overinvested. By the time the internet bubble popped, more than 90% of transcontinental and transatlantic fiber sat “dark” and unused, leading to plunging stock prices and widespread bankruptcies.
Today, a key part of the bear argument is that history is repeating itself, except this time, the overinvesting is occurring in NVIDIA ((NVDA - Free Report) ) GPUs. However, the evidence contradicts such a sentiment. The NVIDIA H1000 is a three-year-old training chip. Its rental price is up a staggering 22% month-over-month to $3.28 an hour. Instead of these outdated chips sitting “dark,” hyperscalers are paying a premium for them.
Image Source:TradingView
AI Companies are More Profitable than Internet Companies
In 1999, a massive wave of internet initial public offerings hit. Of these new issues, roughly 75% operated at a net loss. Today, tech IPOs have a GAAP profitability rate of ~50% due to because private markets have stricter expectations. Today’s top AI companies like Alphabet ((GOOGL - Free Report) ), Advanced Micro Devices ((AMD - Free Report) ), and Micron ((MU - Free Report) ) are highly profitable. For instance, last quarter, Micron generated $28.86 billion in net income.
Image Source: Zacks Investment Research
AI Valuations are Reasonable
At the peak of the internet bubble, the average price-to-earnings ratio was over 200x. Conversely, leading AI names have extremely reasonable P/E ratios, as valuations have been held down recently by geopolitical concerns. For example, Dell ((DELL - Free Report) ) has a P/E ratio of 28.52x. On the other hand, Cisco ((CSCO - Free Report) ), one of the leading internet-related names of the time, peaked with a 200x P/E.
Image Source: Zacks Investment Research
Bottom Line
While the sheer scale of the AI buildout naturally draws comparisons to the internet bubble of the late-90s, equating the two overlooks key economic realities. Backed by immediate hardware utilization, robust profitability, and low valuations, the AI boom rests on a far stronger foundation than the internet boom.
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Image: Shutterstock
Why Today's AI Boom Differs From the Internet Bubble
AI: The Largest Industrial Buildout Since the Railroad
As a percentage of GDP, the current artificial intelligence buildout is the largest industrial buildout since the American railroad buildout of the 19th century.
Image Source: EpochAI
However, for many investors, the pain and the memory of the late-1990s internet boom and the subsequent bust 2000 bust are still fresh in their minds. Which begs the question for investors: “What part of the AI cycle are we in currently?” In today’s commentary, I will be contrasting the AI boom to the internet boom of the 1990s, providing evidence and data that underscored my belief that we are merely in the third inning of nine in the AI boom.
AI: There is No “Dark Fiber”
During the dot-com bubble of the late 1990s, telecom companies invested more than $500 billion (financed through cheap corporate debt) to dig trenches across land and under oceans, believing that internet traffic would create permanent demand for bandwidth. However, these telecom companies overestimated the need for fiber and overinvested. By the time the internet bubble popped, more than 90% of transcontinental and transatlantic fiber sat “dark” and unused, leading to plunging stock prices and widespread bankruptcies.
Today, a key part of the bear argument is that history is repeating itself, except this time, the overinvesting is occurring in NVIDIA ((NVDA - Free Report) ) GPUs. However, the evidence contradicts such a sentiment. The NVIDIA H1000 is a three-year-old training chip. Its rental price is up a staggering 22% month-over-month to $3.28 an hour. Instead of these outdated chips sitting “dark,” hyperscalers are paying a premium for them.
Image Source:TradingView
AI Companies are More Profitable than Internet Companies
In 1999, a massive wave of internet initial public offerings hit. Of these new issues, roughly 75% operated at a net loss. Today, tech IPOs have a GAAP profitability rate of ~50% due to because private markets have stricter expectations. Today’s top AI companies like Alphabet ((GOOGL - Free Report) ), Advanced Micro Devices ((AMD - Free Report) ), and Micron ((MU - Free Report) ) are highly profitable. For instance, last quarter, Micron generated $28.86 billion in net income.
Image Source: Zacks Investment Research
AI Valuations are Reasonable
At the peak of the internet bubble, the average price-to-earnings ratio was over 200x. Conversely, leading AI names have extremely reasonable P/E ratios, as valuations have been held down recently by geopolitical concerns. For example, Dell ((DELL - Free Report) ) has a P/E ratio of 28.52x. On the other hand, Cisco ((CSCO - Free Report) ), one of the leading internet-related names of the time, peaked with a 200x P/E.
Image Source: Zacks Investment Research
Bottom Line
While the sheer scale of the AI buildout naturally draws comparisons to the internet bubble of the late-90s, equating the two overlooks key economic realities. Backed by immediate hardware utilization, robust profitability, and low valuations, the AI boom rests on a far stronger foundation than the internet boom.