Jensen Huang
speaker
987 appearances
31 recordings
5 series
first heard Nov 2024
last heard 1 Sep
Jensen Huang’s voice in public audio — every appearance, attributed to the second.
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recordings per month · last 12 monthsRecordings per month over the last 12 months — 28 in all, peaking in Aug 2026 with 11.
Appearances
We're in every cloud, we're on-prem, we're at the edge.
And so we're able to address markets that, frankly, nobody else can because of the architecture of our company and the entire full-stack AI factory platform that we have.
An XPU is a specialized chip.
NVIDIA's GPU is a general purpose accelerator.
We accelerate the entire lifecycle of AI from data processing, which data processing to pre-training, to post-training, to agentic AI inferencing.
We accelerate every single AI model in the world.
Inside a gigawatt, if we were just to extrapolate, in a gigawatt, Hopper was about $18 billion of economics for NVIDIA per gigawatt.
Grace Blackwell is about $25 billion.
And the Vera Rubin generation, it's about $40 plus billion per gigawatt of total NVIDIA compute economics.
And the reason for that is because we've been expanding beyond the GPU to one type of switch after another type of networking.
And now the amount of chips, there's like seven different types of NVIDIA chips that has to go into an AI factory.
An XPU would be a replacement of one of those.
My sense is that we'll continue to be in every single cloud, we'll continue to be in every single AI factory.
Some of those racks might be augmented with XPUs.
And so in those cases, NVIDIA's networking, NVIDIA's switching, NVIDIA's CPUs would also have an opportunity to participate.
And we make it easier
for the customers to be able to extend out their AI factory using exactly the same system architecture and networking architecture.
In the case of MediaTek, it allows MediaTek to offer an end-to-end solution that is complete.
That XPU otherwise would have to go and solve MV-Link switching problems, a whole bunch of NICS problems, a whole bunch of Ethernet switching, scale-outs, scale-up,
scale across, scale in.
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