If you want to learn more, go check this Nature article on how stock-market crash of AI could have a knock-on effects for funding and jobs

www.nature.com/articles/d41...

Ultimately, the fate of this high-stakes market is uncertain. We may see a swift, painful correction like the Dot-Com crash, or perhaps a long, slow "deflation" as the underlying technology slowly catches up to its valuation. The only certainty is extreme volatility ahead.

This situation draws strong parallels to the Dot-Com Bubble of the late 1990s. The underlying technology (the internet) was revolutionary, but most companies chasing the hype went bust because their sky-high valuations had no basis in real cash flow.

Beyond Nvidia, the bubble is defined by the core issue of profitability. Current AI models are incredibly expensive to run. Many popular consumer LLMs lose money per interaction due to immense compute costs, meaning high user engagement equals higher losses.

A sharp and sudden drop of NVDA would immediately trigger a powerful domino effect across the entire sector. This massive systemic shock would swiftly crash the NASDAQ, confirming the collapse of the entire Artificial Intelligence market.

NVDA’s market cap is colossal and represents over 15% of the NASDAQ 100 Index. The NASDAQ is the key US stock exchange where most major tech firms like Apple, Microsoft, and Amazon are listed. NVDA’s size makes it a huge systemic risk.

The main issue is that Nvidia’s stock has soared to historic highs, reflecting a blind belief in endless AI spending. This massive valuation has created classic bubble conditions, becoming detached from the near-term profitability of the AI applications themselves.

These hyperscalers fear becoming perpetually dependent on a single supplier, which drives up their own operating costs and cedes long-term control. This is why they are rushing to develop their own custom chips (ASICs) like Google’s TPUs and Amazon’s Trainium.

This singular dependency is precisely what concerns major tech CEOs (all except Nvidia's own, Jensen Huang, of course). Giants like Microsoft, Google, Amazon, and Meta are collectively spending billions to buy NVDA chips of their own.

To secure its ecosystem, Nvidia has strategically taken stakes in key AI players like OpenAI and Perplexity. This means that if Nvidia collapses, the companies built on its infrastructure, financing, and hardware are instantly at risk.

Nvidia is the essential supplier of the "mega calculators"that is to say the supercomputers and infrastructure running all current AI. This dominance has earned them massive financial power, generating billions, including an astounding $165 billion in yearly revenue growth.

Nvidia (NVDA) is a US chipmaker famous for its GPUs. Today, these Graphics Processing Units are the only viable hardware for training the complex Large Language Models (LLMs) like GPT-4, giving NVDA a near-monopoly on the current AI gold rush.