Relax! NVIDIA came up trumps with its quarterly earnings and so the global economy isn’t collapsing, at least for another three months or so. Or as CEO Jensen Huang notes smugly:
There has been a lot of talk about an AI bubble. From our vantage point we see something very different.
That’s a vantage point from the perspective of a 62% year-on-year revenue increase to hit $57 billion. Net income came in at $31.9 billion.
Huang says that NVIDIA was in the right place at the right time:
The world is undergoing three massive platform shifts at once. The first time since the dawn of Moore’s Law, NVIDIA is uniquely addressing each of the three transformations. The first transition is from CPU general purpose computing to GPU accelerated computing and Moore’s Law slows. The world has a massive investment in non-AI software from data processing to science and engineering simulations, representing hundreds of billions of dollars in compute — cloud computing spend each year.
Many of these applications, which ran once exclusively on CPUs are now rapidly shifting to CUDA GPUs. Accelerated computing has reached a tipping point. Secondly, AI has also reached a tipping point and is transforming existing applications while enabling entirely new ones. For existing applications, generative AI is replacing classical Machine Learning in search ranking, recommender systems, ad targeting, click-through prediction to content moderation. The very foundations of hyperscale infrastructure.
Meta’s GEM, a foundation model for ad recommendations trained on large-scale GPU clusters exemplifies this shift. In Q2, Meta reported over a five percent increase in ad conversions on Instagram and a three percent gain on Facebook feed driven by generative AI-based GEM. Transitioning to generative AI represents substantial revenue gains for hyperscalers.
Now a new wave is rising, agentic AI systems capable of reasoning, planning and using tools from coding assistance like Cursor and Claude Code to radiology tools like Aidoc, legal assistants like Harvey and AI chauffeurs like Tesla FSD and Waymo. These systems mark the next frontier of computing, the fastest-growing companies in the world today, OpenAI, Anthropic, xAI, Google, Cursor, Lovable, Replit, Cognition AI, OpenEvidence, Abridge, Tesla are pioneering agentic AI.
So there are three massive platform shifts. The transition to accelerated computing is foundational and necessary, essential in a post-Moore’s Law era. The transition to generative AI is transformational and necessary, supercharging existing applications and business models. And the transition to agentic and physical AI will be revolutionary, giving rise to new applications, companies, products and services.
That’s all good for NVIDIA, he added:
When you look at the totality of the spend, it’s really important to think about each 1 of those layers. They’re all growing. They’re related, but not the same, but the wonderful thing is that they all run on NVIDIA GPUs. Simultaneously, because the quality of the AI models are improving so incredibly. The adoption of it in the different use cases, whether it’s in code assistance, which NVIDIA uses fairly exhaustively, and we’re not the only one. I mean, the fastest-growing application in history, a combination of Cursor and Claude Code and code — OpenAI’s Codex and GitHub CoPilot. These applications are the fastest-growing in history.
But…
Still, everything still hinges on an alarmingly small number of mega-customers. In the latest quarter, 61% of revenue came from four clients – and the dependency is increasing, up from 56% three months ago. The company is also spending nearly half of its revenue – $26 billion – renting its own chips back from its customers, over twice as much as it did three months ago.
Relax, says Huang:
Using cash to fund our growth, no company has grown at the scale that we’re talking about and have the connection and the depth and the breadth of supply chain that NVIDIA has. The reason why our entire customer base can rely on us is because we’ve secured a really resilient supply chain, and we have the balance sheet to support them.
When we make purchases, our suppliers can take it to the bank. When we make forecast and we plan with them, they take us seriously because of our balance sheet. We’re not making up the off-take. We know what our off-take is, and because they’ve been planning with us for so many years, our reputation and our credibility is incredible. And so it takes really strong balance sheet to do that, to support the level of growth and the rate of growth and the magnitude associated with that.
That said, he chose to point to NVIDIA’s relationship with OpenAI as a proof point of long-term fiscal stability. That’s OpenAI that has yet to turn a profit and is itself the subject of lots of nervous speculation of a ‘bubble bursting’ nature. Nonetheless Huang said:
I delivered the first AI supercomputer ever made to OpenAI. And so we’ve had a close and wonderful relationship with OpenAI since then. And everything that OpenAI does runs on NVIDIA today. So all the clouds that they deploy in, whether it’s training and inference runs NVIDIA and we love working with them.
The partnership that we have with them is one, so that we could work even deeper from a technical perspective so that we could support their accelerated growth. This is a company that’s growing incredibly fast. And don’t just look at what is said in the press, look at all the ecosystem partners and all the developers that are connected to OpenAI, and they’re all driving consumption of it. and the quality of the AI that’s being produced, huge step-up since a year ago. And so the quality of response is extraordinary.
So we invest in OpenAI for a deep partnership in co-development to expand our ecosystem and support their growth. And of course, rather than giving up a share of our company, we get a share of their company. And we invested in them, in one of the most consequential once-in-a-generation companies that we have a share of. And so I fully expect that investment to translate to extraordinary returns.
Overall, Huang pitches that he is confident NVIDIA is on top of potential constraints on future growth:
When you’re growing at the rate that we are and the scale that we are, how could anything be easy? What NVIDIA is doing obviously has never been done before. And we’ve created a whole new industry. Now on the one hand, we are transitioning computing from general purpose and classical or traditional computing to accelerated computing and AI. That’s on the one hand. On the other hand, we created a whole new industry called AI factories. The idea that in order for software to run, you need these factories to generate it, generate every single token instead of retrieving information that was pre-created. And so I think this whole transition requires extraordinary scale.
And all the way from the supply chain. Of course, the supply chain, we have much better visibility and control over because obviously, we’re incredibly good at managing our supply chain. We have great partners that we’ve worked with for 33 years. And so the supply chain part of it, we’re quite confident. Now looking down our supply chain, we’ve now established partnerships with so many players in land and power and shell.
Huang concludes:
None of these things are easy, but they’re all attractable and they’re all solvable things. And the most important thing that we have to do is do a good job planning we plan up the supply chain, down the supply chain. We have established a whole lot of partners. And so we have a lot of routes to market. And very importantly, our architecture has to deliver the best value to the customers that we have… I think that we’re more successful this year at this point than we were last year at this point. The number of customers coming to us and the number of platforms coming to us after they’ve explored others, is increasing, not decreasing.
My take
And breathe out…for now.
See you back here in three months time for another round of ‘will the bubble burst?’.