Jensen Huang – TPU competition, why we should sell chips to China, & Nvidia’s supply chain moat
In a Nutshell
Jensen Huang defends Nvidia's irreplaceable moat in AI via massive supply chain commitments ($100B+), CUDA ecosystem superiority over TPUs/ASICS, and extreme architecture leaps (e.g., Blackwell 50x Hopper), enabling accelerated computing beyond just matrix multiplies for diverse workloads. He argues for selling compliant chips to China to lock 50% of global AI developers into the American tech stack, fostering open-source contributions and US leadership across AI's five layers, rather than conceding the world's second-largest market to Huawei/SMIC amid their abundant energy and manufacturing. Export controls risk bifurcating ecosystems, accelerating China's domestic chips, while US compute/process node leads (e.g., 1.6nm vs. 7nm) ensure America stays ahead if it competes globally.
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Valuations of software companies have crashed because people expect AI to commoditize software. Naive view: Nvidia sends GDS2 file to TSMC, which builds logic dies and switches, packages with HBM from SK Hynix, Micron, Samsung, then to ODM in Taiwan for rack assembly. Nvidia makes software that others manufacture; if software commoditizes, does Nvidia?
Something must transform electrons to tokens, making tokens more valuable over time—hard to commoditize. Transformation from electrons to tokens is an incredible journey, like making one molecule or token more valuable than another. Requires artistry, engineering, science, invention—we're watching it happen. Manufacturing and science involved is far from deeply understood; journey far from over. Will become more efficient.
Input is electrons, output is tokens. In the middle is Nvidia. Our job is to do as much as necessary and as little as possible to enable that transformation at incredible capabilities.
"As little as possible" means partnering for what isn't needed. Nvidia has largest ecosystem of partners: supply chain upstream/downstream, computer companies, application developers, model makers. AI is a five-layer cake with ecosystems across all layers. Do as little as possible, but necessary part is insanely hard—not commoditizable.
Enterprise software companies are mostly tool makers (e.g., Excel, PowerPoint, Cadence, Synopsys). Opposite of commoditization: number of agents and tool users will grow exponentially, skyrocketing tool instances (e.g., Synopsys Design Compiler, floor planners, layout tools, design rule checkers). Today limited by engineers; tomorrow engineers supported by agents exploring design space unprecedentedly. Tool use will skyrocket software companies. Hasn't happened yet because agents not good enough at using tools. Companies will build agents or agents will improve—combination of both.
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