Here we go again with Nvidia falling on earnings. What the sellers are missing

At this point, it's undeniable that the issue with Nvidia stock is sentiment, or rather disbelief. Yep, that's it. Disbelief. There's no other way to explain the muted stock reaction to Nvidia's quarterly report — not only after Wednesday night's blowout, but over the past several quarters. "Demand has gone parabolic," CEO Jensen Huang said to close out the call. Last quarter, he said demand was "skyrocketing." You almost feel bad for him. He's going to run out of words soon to describe the demand. Arguably, the most interesting part of Nvidia's report is its new reporting framework — specifically, breaking down its data center business by the hyperscalers (Amazon, Alphabet, Meta, and Microsoft) and non-hyperscale customers. Listen, the hyperscalers are important. They're spending hundreds of billions on capital expenditures to build new data centers. They've been the main course for the last $200 worth of Nvidia stock gains. But what if they were only the appetizer? On the call, Huang said Nvidia revenue will grow faster than the growth of hyperscale capex. So, if hyperscale capex is what got us here, and Huang expects Nvidia revenue to outpace future hyperscale capex growth going forward, where does the upside come from? Everyone and everywhere else. We covered this in our earnings analysis Wednesday night. But let's spend a minute going deeper into these non-hyperscalers. That group consists of purpose-built AI computing providers called neoclouds (think CoreWeave, Nebius, and Iren). It also includes industrial companies and other enterprises with on-premise computing infrastructure; countries building out their own AI infrastructure in what Nvidia calls sovereign AI; and other smaller AI players. Nvidia's official name for this sub-segment is AI Clouds, Industrial and Enterprise (ACIE). Huand said the customers in the ACIE cohort are "fairly poorly understood," attributing that in part to how fragmented the market is. This may work in Nvidia's favor over the long run, helping to address one of the biggest fundamental concerns held by some investors: hyperscalers developing their own custom AI chips. Huang said that because this ACIE opportunity is an amalgamation of so many smaller AI players, there is no real demand for custom semiconductor solutions. He said these AI native neoclouds don't want to deal with the complexities of designing a chip — it takes years and lots of money — or ensuring all parts of a data center work together as they should. What they want is to be up and running as fast as possible with as high a utilization rate as possible. They need to be able to run every model and serve everyone, everywhere, all the time. For that, the neoclouds need to be vertically integrated, and to build vertically integrated data centers, from the hardware to the networking and software, you need Nvidia. As Huang put it, Nvidia brings to market the most rentable architecture, with the best total cost of ownership and easiest financing. "Our share of that, of course, is very, very large. We're fairly unique in our ability to be able to serve this industry. Our platform is built like it's vertically integrated, so that everything works. But then we disassemble it, so that people can build and buy it in the configuration they want and assemble it the way they like." It gets better. It's not just a large share. It's nearly a 100% share, and a huge amount is inference computing — that's when the models are being used after they've been trained; in other words, whenever you're interacting with ChatGPT, that's inference. Unlike training, which is more cyclical, inference scales with adoption, which is going up and to the right. And at a rapid clip. This is in addition to the inference revenue boost the hyperscale subsegment is now getting from Anthropic, now that the Claude model maker is using Nvidia silicon. "This segment is very fragmented, requires a fairly integrated a really well-integrated platform solution and a very large go-to-market, and that segment, all of the inference, 100% of that, the vast majority of that is Nvidia," Huang added. This is a lot to chew on. Let's recap. Huang believes Nvidia's ACIE customers could end up dwarfing the hyperscalers, arguing the industrial and enterprise markets represent some $50 trillion to $80 trillion of the world economy (the global gross domestic product was $111 trillion in 2024, according to the World Bank). Plus, Huang said AI will help grow the size of that pie over time. So, in this portion of the market, Nvidia is seemingly the only plug-and-play provider of all the computing technology needed to stand up data centers — or AI factories, to use Nvidia's term. To be sure, Nvidia may face some competition on the neocloud front. Most immediately, Club name Alphabet and private equity giant Blackstone are developing an AI infrastructure company that runs on Google's custom Tensor Processing Units (TPUs). If this comes online, it would be a neocloud runnin