AI industry needs to earn $600 billion per year to pay for massive hardware spend — fears of an AI bubble intensify in wake of Sequoia report
The AI bubble is reaching a tipping point?
Despite massive investments in AI infrastructure by high-tech giants, revenue growth from AI has yet to materialize, indicating a significant gap in the ecosystem's end-user value. In fact, David Cahn, a partner at Sequoia Capital, believes that AI companies will have to earn about $600 billion per year to pay for their AI infrastructure, such as datacenters.
Nvidia earned $47.5 billion in datacenter hardware revenue last year (with most hardware being compute GPUs for AI and HPC applications). Companies like AWS, Google, Meta, Microsoft, and many others invested heavily in their AI infrastructure in 2023 for applications like OpenAI's ChatGPT. However, will they earn that investment back? David Cahn believes this could mean that we are witnessing the growth of a financial bubble.
Simple Math
Cahn's math is relatively simple. First, he doubles Nvidia's run-rate revenue forecast to cover the total AI data center costs (GPUs are half; the rest includes energy, buildings, and backup generators). Then, he doubles that amount again to account for a 50% gross margin for end-users, such as startups or businesses buying AI compute from companies like AWS or Microsoft Azure, which must make money, too.
Cloud providers, notably Microsoft, are heavily investing in GPU stockpiles. Nvidia reported that half of its datacenter revenue comes from large cloud providers, with Microsoft alone likely contributing around 22% of Nvidia's Q4 FY2024 revenue. Meanwhile, the company sold some $19 billion worth of datacenter GPUs in Q1 FY2025.
The introduction of Nvidia's B100/B200 processors, promising 2.5 times better performance while costing only 25% more, will likely drive further investments and create another supply shortage.
According to the analyst, OpenAI, which uses Microsoft's Azure infrastructure, has seen a substantial increase in revenue, from $1.6 billion in late 2023 to $3.4 billion in 2024. This growth underscores OpenAI's dominant position in the market, far outpacing other startups that are still struggling to reach a $100 million revenue mark. Yet investments in AI hardware are growing.
Even optimistic projections for major tech companies' AI revenues fall short, Cahn says. Assuming Google, Microsoft, Apple, and Meta each generate $10 billion annually from AI and other companies like Oracle, ByteDance, Alibaba, Tencent, X, and Tesla generate $5 billion each, there remains a $500 billion gap.
Get Tom's Hardware's best news and in-depth reviews, straight to your inbox.
AI industry needs to learn how to earn
There are significant challenges to the optimistic view of AI infrastructure investments. Unlike physical infrastructure, AI GPU computing could be commoditized as new players enter the scene (AMD, Intel, not to mention custom processors from Google, Meta, and Microsoft), particularly in the field of inference, leading to intense price competition. Speculative investments often result in high losses, and new processors rapidly devalue older ones, contrary to physical infrastructure's more stable value.
Ultimately, while AI holds transformative potential and companies like Nvidia play a crucial role, the road ahead will be long and challenging as businesses and startups have yet to invent applications that make money.
Cahn believes the industry must temper expectations of quick profits from AI advancements, recognizing the speculative nature of current investments and the need for sustained innovation and value creation. If it does not, the bubble worth hundreds of billions of dollars is set to blow, potentially leading to a global economic crisis, but we are speculating here, of course.
Anton Shilov is a contributing writer at Tom’s Hardware. Over the past couple of decades, he has covered everything from CPUs and GPUs to supercomputers and from modern process technologies and latest fab tools to high-tech industry trends.
-
vijosef His first achievement will be to invent Keynesian lies so obscure that it will take us centuries to unmask them.Reply -
bit_user Applying a blanket software margin of 50% is pretty hilarious. I also find the 50% overhead of building & operating the datacenter to be somewhat suspect. I think he's just applying historical figures atop this new hardware, even though the hardware is disproportionately more expensive.Reply
If the datacenter overhead ends up being more like 25%, then you get $187B. It's hard to know exactly what's meant by that software 50% margin, but software does have to be written & models obviously have to be trained. So, maybe costs go up to $200B. Yes, they'll want some profit on top of that, but they probably have some appetite for depressed margins, so long as they believe revenues will continue to grow and perhaps hardware costs will eventually start to decline.
I just think the approach of "Take hardware costs and double them. Then, double again." is laughably naive. And apart from a little money in some NASDAQ index fund, I say this with no substantial vested interest. -
bit_user Reply
Startups? He's using Nvidia's revenue as the top line figure. I'm not sure how startups tie into this story, unless you're way off on a tangent.Notton said:I want convincing evidence these startups are not a Ponzi scheme.
As for your statement, they're not a ponzi scheme if they execute to their business plan and don't engage in embezzlement. As long as investors have transparency into the revenue model of the company, then they should be sophisticated enough to evaluate the risks for themselves and decide if it's a sound investment. -
Notton Reply
I am talking about this line.bit_user said:Startups? He's using Nvidia's revenue as the top line figure. I'm not sure how startups tie into this story, unless you're way off on a tangent.
As for your statement, they're not a ponzi scheme if they execute to their business plan and don't engage in embezzlement. As long as investors have transparency into the revenue model of the company, then they should be sophisticated enough to evaluate the risks for themselves and decide if it's a sound investment.
"Companies like AWS, Google, Meta, Microsoft, and many others invested heavily in their AI"
It's pretty clear that AWS, Google, Meta, and Microsoft have an abundance of cash, but the "many others"? doubtful -
hotaru251 ReplyAI industry needs to learn how to earn
thats easier said than done. most "ai" stuff has so little value to most people outside of fomo.
ppl might spend early on into some new fad of ai but long term most ppl wont care to spend for it as honeymoon phase ends..
current "ai" just has no real "must have purchase" factor. -
NedSmelly This is worrisome, regardless of how the figures were extrapolated. The key point is that these companies need to monetise to get ROI on their massive expenditures on AI. I don't think it's going to be achieved by nickel-and-diming end users - it's going to be service contracts with other corporations and enterprise seeking to cut their own costs through automation. This is setting the scene for some major social repercussions, such as with the labour market.Reply -
bit_user Reply
Dunno about that. Some people would be pretty unhappy if you took away Siri and Alexa.hotaru251 said:thats easier said than done. most "ai" stuff has so little value to most people outside of fomo.
Also, depending on how broadly you define "AI", it's now a mainstay of many other industries. I can tell you that it basically killed off most classical computer vision approaches, and I'm talking about in actual deployed products. In fact, Tesla's self-driving software is fundamentally AI-based. -
A Stoner Not sure if AI is ever going to meet the goals of those investing. You can feed it oodles of points and it will never, ever, understand anything in an intelligent fashion. It seems to have some capability of piecing together various existing things and combining them differently to make unique results, kind of like my grandmother taking hundreds of pieces of old clothes and making a quilt out of it. She did not make the patchcloth designs, they came from someone else. She just cut them up, organized them, and then stitched them all together.Reply
AI kind of seems to work like that, but in a more mechanical rather than organic way. -
why_wolf Reply
Funny that mention Alexa since it famously lost Amazon billions. They could never figure how exactly to make money from it. Siri is frankly the same though Apple seems to treat it more like a loss leader to keep people in the iVerse.bit_user said:Dunno about that. Some people would be pretty unhappy if you took away Siri and Alexa.
Also, depending on how broadly you define "AI", it's now a mainstay of many other industries. I can tell you that it basically killed off most classical computer vision approaches, and I'm talking about in actual deployed products. In fact, Tesla's self-driving software is fundamentally AI-based.