GoKawiilNvidia founder and CEO Jensen Huang is, perhaps, one of the greatest corporate hype men of all time when it comes to his company. He may even surpass Salesforce’s Marc Benioff when it comes to relentless optimism in his company’s future and revenues.
Even so, he delivers on the hype, quarter after quarter.
Instead of cautioning you to view the proclamation that he’s found a “brand new $200 billion TAM for Nvidia” with skepticism, I’d argue he’s earned a bit of trust.
Huang positioned this massive new market at the feet of Nvidia’s new CPU product, Vera, which was introduced in March. Speaking on Wednesday’s earnings call — after Nvidia posted another record-breaking quarter with $81.6 billion in revenue and forecast $91 billion for the next — Huang pitched Vera as a potentially transformative product. And one that already has promising sales figures.
But no matter how well Nvidia delivers, Wall Street harbors anxiety over what will knock Nvidia from its perch.
Lately, such fears have centered on the CPU. Nvidia is the king of the GPU, whereas historically the CPU markets were owned by companies like Intel and AMD. (Nvidia has made CPUs previously, of course, but that’s not its core business.)
For example, last month Amazon Web Services crowed about a giant contract it signed with Meta for millions of Amazon’s homegrown AI CPUs. Amazon CEO Andy Jassy has been clear that he thinks AWS can do AI chips, both GPUs and CPUs, at least as well, and possibly better than Nvidia.
But now, with the Vera CPU, which is sold alone and bundled with its Rubin GPU, Huang believes he’s unlocked “a major new growth driver” for his company because Vera is, he believes, “the world’s first CPU, purpose-built for agentic AI,” Huang said on the call.
“Vera opens a brand new $200 billion TAM for Nvidia, a market we have never addressed before, and every major hyperscaler and system maker is partnering with us to deploy it. The world is rebuilding computing for agentic AI and robotic physical AI. Nvidia sits at the center of these transitions,” hype man Huang said.
He explained that while the “thinking” part of an AI model uses GPUs, agents mostly run on CPUs. They use CPUs to do their assigned tasks and will, he predicts, run their own form of CPU-driven PCs.
... continue reading