The boom in Generative AI is real if Nvidia’s shares are anything to go by. Indeed, Nvidia became the largest company on the planet by market cap briefly last month, its market cap rising ten times in a year and a half to over $3trn. It is not just its market cap but also its revenues and profits which have been ,soaring. So unlike other narrative driven stories, this has fundamental legs. However, the share price and market cap are not just indicators of today’s fundamentals but well into the future. And this is where the debate is between those who believe AI is a hype atleast compared to the sustainability of growth implied by stock prices or those who believe AI is a game changer.
Here’s a nuanced take by someone who believes in a bit of both i.e, AI will be a game changer for consumer, enterprises and economies alike but not necessarily for investors today. This blog by Sequoia’s David Cahn is actually a follow up to his original post from September last year, which tried to give a sense about the economics for those who are spending billions on buying Nvidia’s chips – how will they make money? Turns out that the math he put out in September required the users of Nvidia’s chip laden data centers run by the likes of Amazon, Microsoft and Google, to generate about $200bn of revenues to justify the spend. The new post upgrades that number to $600bn.
“It’s easy to calculate this metric directly. All you have to do is to take Nvidia’s run-rate revenue forecast and multiply it by 2x to reflect the total cost of AI data centers (GPUs are half of the total cost of ownership—the other half includes energy, buildings, backup generators, etc). Then you multiply by 2x again, to reflect a 50% gross margin for the end-user of the GPU, (e.g., the startup or business buying AI compute from Azure or AWS or GCP, who needs to make money as well).”
The math is clear but why doubt the $600bn potential?
“The Information recently reported that OpenAI’s revenue is now $3.4B, up from $1.6B in late 2023. While we’ve seen a handful of startups scale revenues into the <$100M range, the gap between OpenAI and everyone else continues to loom large. Outside of ChatGPT, how many AI products are consumers really using today? Consider how much value you get from Netflix for $15.49/month or Spotify for $11.99. Long term, AI companies will need to deliver significant value for consumers to continue opening their wallets.”
The author goes on to rebut the criticism that how the GPU data centers are much like the railroad infrastructure which when built will see use cases emerging and value gets created eventually. His rebuttal argues how there isn’t much monopolistic aspect to the data centre unlike the railroad and technological obsolescence through new generation of chips means continuous investments. He also helpfully reminds us how even rail roads led to losses for investors when it reached speculative territory.
“A huge amount of economic value is going to be created by AI. Company builders focused on delivering value to end users will be rewarded handsomely. We are living through what has the potential to be a generation-defining technology wave. Companies like Nvidia deserve enormous credit for the role they’ve played in enabling this transition, and are likely to play a critical role in the ecosystem for a long time to come.
Speculative frenzies are part of technology, and so they are not something to be afraid of. Those who remain level-headed through this moment have the chance to build extremely important companies. But we need to make sure not to believe in the delusion that has now spread from Silicon Valley to the rest of the country, and indeed the world. That delusion says that we’re all going to get rich quick, because AGI is coming tomorrow, and we all need to stockpile the only valuable resource, which is GPUs.
In reality, the road ahead is going to be a long one. It will have ups and downs. But almost certainly it will be worthwhile.”
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