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AI has avoided bubble status because of immediate infrastructure usage, validating Nvidia‘s (NVDA) valuation.
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GPUs are fully monetized, unlike the dotcom era’s “dark fiber.”
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Positive ROIC from AI investments encourages ongoing investments in the technology.
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Nvidia (NASDAQ:NVDA) is at the forefront of the artificial intelligence (AI) revolution, providing the essential GPUs that drive this transformative technology. In contrast to the dotcom bubble of the late 1990s, when massive investments in internet infrastructure led to 97% of America’s fiber optic cables remaining “dark” — laid but unused as demand lagged behind speculative overbuilds — the AI era demonstrates true utilization.
Every GPU shipped is promptly reserved, deployed, and generates revenue. There are no “dark GPUs”; instead, they operate at such intensity that overheating during training sessions is a frequent challenge. This reflects genuine, immediate demand rather than mere hype.
Valuations further differentiate the periods: dotcom tech stocks often traded at 150 to 180 times trailing earnings, while current AI frontrunners average around 40 times. Some AI hardware purchasers have reported improved return on ivested capital (ROIC), but results vary across the industry.
This solid groundwork distinguishes AI from historical bubbles and primes leading companies like Nvidia for substantial expansion.
The absence of idle GPUs underscores a fundamental shift in how infrastructure is built and used. In the telecom bubble, companies like WorldCom boasted about laying thousands of miles of fiber, but without optics, switches, or actual traffic, it sat dormant. Today, AI data centers absorb every chip produced.
Technical papers highlight GPUs “melting” under load, a sign of intense, productive activity. This isn’t speculation; it’s driven by hyperscalers like Microsoft (NASDAQ:MSFT) and Amazon (NASDAQ:AMZN) scaling models for practical applications in search, advertising, and cloud services.
For Nvidia, this means sustained orders. As the dominant GPU provider with over 80% market share in AI accelerators, the company benefits directly from this zero-inventory reality. Goldman Sachs estimates AI infrastructure spending hitting $3 trillion to $4 trillion by 2030. McKinsey forecasts are even higher, at $6.7 trillion for global data centers alone. Nvidia’s chips power most of this expansion, translating to reliable revenue streams.
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This full utilization propels Nvidia’s financials forward. In its second quarter results, the AI chipmaker guided for $54 billion in revenue for the next quarter, up massively from prior years. Analysts project data center revenue alone reaching $300 billion in calendar 2026. That’s fueled by demand for Blackwell chips and beyond, where ROIC remains positive for buyers.
Unlike the dotcom overbuild, AI’s economics work because outputs — like efficient AI models — create value immediately. Skeptics argue AI lacks proven profitability, but leaders like Sam Altman and Bill Gates counter that it’s early innings, with transformative potential in healthcare, energy, and more.
Nvidia’s gross margins hover at 73%, supporting reinvestment in R&D and maintaining its edge over competitors like Advanced Micro Devices (NASDAQ:AMD).
However, debate is contentious on whether AI is overhyped. Some analysts call it 17 times bigger than the dotcom bubble, citing high P/E ratios — Nvidia at 57 and Palantir Technologies (NYSE:PLTR) over 600. Critics also point to uncertain payoffs, with MIT finding 95% of generative AI pilot projects failing.
Yet, proponents like Mark Cuban emphasize the light-bulb moment: AI is infrastructure for a new industrial revolution, not a quick flip. Goldman Sachs notes valuations aren’t extreme, and liquidity supports growth. The key is that utilization trumps speculation.
For Nvidia, this debate favors bulls. As capex surges — hyperscalers plan on spending $371 billion in 2025 alone and Nvidia captures the lion’s share. No dark GPUs mean no glut, stabilizing prices and margins.
Nvidia’s market cap stands at $4.93 trillion, having briefly crossed over the $5 trillion threshold. Doubling to $10 trillion requires continued execution. Consensus earnings for fiscal 2026 are $4.53 per share, rising to $6.63 in 2027. At a 40x multiple, that implies stock prices around $257 by 2027, pushing its market cap toward $10 trillion with share count growth.
AI’s scaling laws demand more compute, and Nvidia leads. With $600 billion in annual data center capex expected soon, Nvidia could see revenues triple. Barriers such as its CUDA software ecosystem lock in customers. Risks exist — competition, regulation, and export limits — but demand’s reality outweighs them. By 2030, as AI integrates everywhere, a $10 trillion valuation for Nvidia looks readily achievable.