On Aug. 28, This Figure From Nvidia Will Confirm an Artificial Intelligence (AI) Bubble That’s in the Early Stages of Bursting

Since the start of 2023, no trend has been more responsible for pushing Wall Street’s major stock indexes to new highs than the rally in artificial intelligence.

The appeal of AI lies in the long-term ability of software and systems to learn without human intervention. This gives AI-powered software and systems the potential to become more efficient at performing tasks, and may evolve to learn new skills. With an addressable market spanning most sectors and industries, analysts at PwC believe that AI could add $15.7 trillion to the global economy by 2030.

Although dozens of companies have benefited from the AI ​​revolution, none has been a model of success more than the semiconductor giant. Nvidia (NASDAQ: NVDA).

Source: Getty Images.

NVIDIA Leads the Next Leap Forward in Commercial Innovation

In a short time, Nvidia’s H100 GPU has become the preferred chip Companies are using the technology to power generative AI solutions and train large language models. With demand outpacing supply, Nvidia has had no problem significantly increasing the price of its H100 GPUs to between $30,000 and $40,000 per chip, or roughly two to three times what its main competitors are charging for their AI data center hardware.

The beauty of the higher price points is that they directly benefit Nvidia’s bottom line. Over the past five reported fiscal quarters, ending April 28, 2024, the company’s adjusted gross profit margin has increased by about 14 percentage points to 78.35%.

Nvidia hasn’t been shy about investing in the future either. The company is set to launch its new Blackwell platform next year, which will boost computing power in six areas, including quantum computing and generative AI, and will be more power efficient than its predecessor. Meanwhile, CEO Jensen Huang announced in June its all-new Rubin GPU architecture, which will run on a different processor (known as Vera) and debut in 2026.

The final piece of the puzzle that has helped Nvidia’s market cap grow by more than $2.8 trillion since the start of 2023 is its CUDA platform. This is the software platform that developers use to build LLMs, and it works alongside the company’s leading hardware to keep enterprise customers loyal to its ecosystem of solutions.

Although it has seemingly served as a perfect operating platform, Wall Street will likely see just how fallible Nvidia and AI as a technology as a whole are on August 28.

This very important number from Nvidia may indicate the AI ​​bubble has burst

Next Wednesday, August 28, Wall Street’s favorite AI company will report its fiscal second-quarter operating results.

Over the past five quarters, Nvidia has done nothing less than smash analysts’ highest expectations. A combination of strong enterprise demand for its AI-powered GPUs, exceptional pricing power, and limited competition has allowed the company to build a backlog that would make any tech company green with envy.

But the headline revenue and earnings numbers won’t tell the whole story by August 28. Even if sales and earnings beat analysts’ consensus, another key number could signal the end of the AI ​​euphoria. I’m talking about Nvidia’s adjusted gross profit margin. Nvidia’s “adjusted” gross profit margin strips out the impact of stock-based compensation, acquisition-related expenses, and some other costs.

NVDA Gross Profit Margin Chart (Quarterly)

Following NVIDIA’s fiscal Q1 results release, Huang and his team provided guidance for fiscal Q2 adjusted gross profit margin of 75.5% (+/- 50 basis points). This guidance indicates a 235 to 335 basis points decline from the first quarter.

While the expected 285 basis point average decline in adjusted gross margin may seem like nothing at all given that Nvidia’s adjusted gross margin has expanded by about 1,370 basis points over the past five quarters, the reasons behind this expected decline are real concern.

Nvidia’s computing advantages are unlikely to save itself from the inevitable predicament.

While demand has been undeniably strong for Nvidia’s H100 GPU, it’s the company’s pricing power that has done most of the hard work. Sales growth has easily outpaced cost-of-revenue increases, suggesting that pricing power, fueled by the ongoing AI-GPU scarcity, is the primary driver for the company.

The problem for Nvidia is that it’s not the only show in town. Advanced Micro Devices (NASDAQ: AMD) AMD is ramping up production of its MI300X AI GPUs, which are 50% to 75% cheaper than Nvidia’s H100 GPUs. AMD also didn’t have the early-stage chip manufacturing issues that Nvidia did.

Moreover, Nvidia’s four largest customers by net sales – Microsoft, Meta platforms (NASDAQ: META), Amazonand alphabet — All of them are developing AI GPUs internally for their own data centers. And even with these internally developed chips for complementary roles, they are ultimately cheaper and more accessible than Nvidia’s hardware. These companies account for about 40% of Nvidia’s sales, all of which suggests less reliance on Wall Street’s favorite AI company in the future.

To make matters worse, reports emerged more than two weeks ago that Nvidia’s prized Blackwell chip would be delayed by “at least three months” due to design flaws and supplier constraints. Nvidia’s inability to meet enterprise demand in a timely manner opens the door for AMD, Samsungand Huawei is stealing the share.

Nvidia’s biggest gross margin gain has come from the scarcity of AI-powered GPUs. But as new chips come to market and the company’s biggest customers fill up valuable “real estate” in their data centers with in-house chips, Nvidia will inevitably find its original pricing power eroded. The company’s median forecast for a 285 basis point decline in adjusted gross margin quarter-over-quarter is evidence that the AI ​​euphoria is fading.

Source: Getty Images.

When the AI ​​bubble bursts, no company is likely to be affected more than NVIDIA.

Looking beyond Nvidia’s August 28 report, history is another barrier to the AI ​​revolution.

Since the advent of the Internet three decades ago, we have not seen an interesting innovation, technology or trend that has a huge market reach and avoids a bubble burst at an early stage. Without exception, investors always overestimate the use cases and consumer/enterprise acceptance of a new technology or trend, which ultimately leads to disappointment, fading euphoria and a bubble burst.

Including the internet, we have seen this play out with genome decoding, business-to-business trade and communication, housing, Chinese stocks, nanotechnology, 3D printing, cryptocurrencies, cannabis, blockchain technology, virtual/augmented reality, and the virtual universe.

To add to this point, few of the companies building AI data centers have specific plans for how they will use the technology to drive sales and profits. For example, Meta Platforms is investing more than $10 billion in Nvidia’s H100 GPUs, but it has no immediate plans to leverage that investment in its AI data center.

The simple fact that most companies lack a clear business plan when it comes to AI makes it abundantly clear that we are dealing with the next bubble in a long line of bubbles.

This does not mean that AI cannot do this, recently (Keyword!) New technology will certainly dramatically change the growth trajectory for American companies—but there is no doubt that the technology will take time to mature.

If the AI ​​bubble bursts, as history suggests, no company will be more hurt than Nvidia. And next week’s adjusted gross profit margin should provide confirmation that the bubble has already begun to burst.

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Prediction: On August 28, this Nvidia figure will confirm that the AI ​​bubble is in the early stages of bursting Originally posted by The Motley Fool

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