In the high-stakes corridors of Silicon Valley and the trading desks of Wall Street, a quiet counter-offensive has been launched. As skepticism regarding the durability of the artificial intelligence boom mounts, Nvidia has circulated a detailed, internal document intended to dismantle the growing "AI bubble" narrative. The chipmaker, which has seen its valuation soar to stratospheric heights on the back of insatiable demand for its Hopper and Blackwell graphics processing units (GPUs), is no longer content to let the market debate its fate without input. According to a report by CNBC, the company has distributed a slide deck that serves as both a defense of its valuation and a direct rebuttal to critics who fear the industry is repeating the mistakes of the dot-com era.

The memo, described by insiders as a "sanity check" for jittery investors, arrives at a pivotal moment. While hyperscalers like Microsoft, Meta, and Google continue to pour tens of billions into capital expenditures, questions regarding the return on investment (ROI) for generative AI have graduated from whispers to shouting matches. Nvidia’s response is data-heavy, aggressive, and surprisingly specific, going so far as to name-check Michael Burry, the famed investor of "The Big Short" notoriety, to underscore the folly of betting against the AI wave. The document offers a rare glimpse into how the world’s most valuable chip company views its own market position: not as a speculative bubble, but as the foundational utility of a new industrial revolution.

The ‘Big Short’ Miscalculation and the Bear Case

Perhaps the most striking element of Nvidia’s internal memo is its willingness to engage directly with the personalities of the market. The deck highlights the trading activities of Michael Burry, whose Scion Asset Management famously held—and then folded—bearish positions against the semiconductor giant. By citing Burry, Nvidia is engaging in a sophisticated bit of investor psychology. As noted by CNBC, the memo points out that even the most celebrated skeptics have been forced to capitulate in the face of Nvidia’s earnings durability. The implication is clear: if the man who predicted the 2008 financial crisis couldn’t find the cracks in the AI thesis, the average portfolio manager should think twice before shorting the stock.

This rhetorical maneuver addresses a specific anxiety gripping the market. Throughout late 2024, distinct voices, including analysts from Goldman Sachs and Sequoia Capital, raised alarms about the "$600 billion question"—the gap between the massive infrastructure spending on chips and the relatively modest revenue currently generated by AI software. Nvidia’s memo attempts to reframe this skepticism not as prudence, but as a misunderstanding of the technology’s adoption curve. By using Burry as a foil, Nvidia suggests that the bear case is based on historical analogies that fail to account for the unique unit economics of generative AI.

The Economics of Inference: Turning One Dollar into Five

Moving beyond market psychology, the core of Nvidia’s defense rests on hard math regarding the profitability of its customers. The prevailing fear among institutional investors is that cloud service providers (CSPs) are stockpiling H100 chips they cannot profitably deploy. Nvidia’s memo counters this with a bold claim regarding unit economics. According to the data reviewed by CNBC, the chipmaker asserts that for every $1 a cloud provider spends on an Nvidia GPU server, they have the potential to generate $5 in GPU hosting revenue over a four-year period. This metric is designed to quell fears that hyperscalers are burning cash on hardware that will sit idle.

The document further breaks down the utility of these chips, distinguishing between "training" (teaching an AI model) and "inference" (running the model to generate responses). Critics have long argued that once the major models are trained, demand for chips will plummet. Nvidia’s internal data suggests the opposite: that the inference market is exploding. The memo cites the operational costs of Meta’s Llama 3 model, arguing that the efficiency gains in Nvidia’s newer architecture lower the cost of inference significantly, thereby stimulating higher volume usage. By framing the purchase of GPUs as a capital expenditure with a clear, high-margin payback period, Nvidia is telling Wall Street that its hardware is closer to an oil rig than a speculative internet domain name.

Exorcising the Ghost of Cisco Systems

No conversation about a tech bubble is complete without invoking the specter of Cisco Systems in the year 2000. At the height of the dot-com boom, Cisco was the "pick and shovel" provider for the internet, briefly becoming the world’s most valuable company before crashing when infrastructure supply outstripped demand. Nvidia’s memo explicitly tackles this comparison, arguing that the dynamics of modern accelerated computing are fundamentally different from the fiber-optic build-out of the late 90s. The company posits that unlike the static infrastructure of the internet era, AI infrastructure is programmable and continually improving, creating a flywheel effect where better hardware enables better software, which in turn demands more hardware.

Industry analysts have debated the validity of this comparison for months. A recent report from The Wall Street Journal noted that while Cisco’s price-to-earnings ratio peaked at over 100 during the dot-com bubble, Nvidia’s forward multiples have remained comparatively grounded due to its explosive earnings growth. Nvidia’s internal deck leans into this valuation argument, suggesting that the "bubble" exists only in the minds of those looking at stock price appreciation without looking at the corresponding explosion in free cash flow. They argue that the demand is not speculative hoarding, but a rational race for sovereign data capabilities and enterprise efficiency.

The Hyperscaler Capex Conundrum

The memo also serves as a proxy defense for Nvidia’s largest customers—Microsoft, Amazon, Alphabet, and Meta—who are under intense scrutiny for their ballooning capital expenditures. In recent earnings calls, these tech giants have signaled that the risk of under-investing in AI infrastructure is greater than the risk of over-investing. Nvidia’s document provides the mathematical cover for this strategy. By asserting that the hardware pays for itself within four years through hosting fees alone—excluding the value of the software running on top of it—Nvidia is arming these CIOs with the data needed to justify their budgets to their own shareholders.

However, independent verification of these figures remains a point of contention. While Nvidia claims a 5x return on hardware investment, reports from The Information and other tech-focused outlets suggest that pricing power for GPU rentals has been volatile. As more H100s flood the market, the hourly rate for compute has seen pressure in spot markets, even if long-term contracts remain robust. Nvidia’s memo appears to smooth over these short-term fluctuations, focusing instead on the long-term structural demand for compute power as AI models become multimodal and increasingly complex.

The Blackwell Era and Supply Constraints

Looking toward the immediate future, the memo likely touches upon the transition to the Blackwell architecture, Nvidia’s next-generation chip. The "bubble" narrative often relies on the idea that competition from AMD or internal chips from Google and Amazon will erode Nvidia’s margins. By emphasizing the proprietary software stack (CUDA) and the integrated nature of its new rack-scale systems, Nvidia is arguing that it has deepened its moat. The company is positioning itself not just as a component supplier, but as a platform provider, making it significantly harder for customers to switch vendors without incurring massive switching costs.

Ultimately, this secret memo reveals a company that is on the offensive. Rather than waiting for the market to decide if the AI boom is a sugar high, Nvidia is actively curating the narrative, using specific financial modeling and the capitulation of famous bears to cement its status. While the CNBC report highlights the existence of the document, the true test will be in the upcoming earnings cycles. If the 5-to-1 revenue model holds true for cloud providers, the bubble allegations will vanish. If it proves optimistic, the ghost of Cisco may yet have the last laugh. For now, Nvidia has put its cards on the table, challenging the street to find a flaw in its math.