Huang said Nvidia's new rack-scale system is built for inference, the workload that he believes drives AI factories and represents the future of AI.
This is the AI future. This is where AI wants to go. It's designed for inference, this one workload. And this workload is what drives AI factories.
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Jensen Huang says the energy required for AI computing is likely about 1,000 times what is currently available.
The amount of energy that we need for [AI] computing is likely probably 1,000 times more than we currently have
Jensen Huang said Nvidia's revenue per gigawatt rises from about $18B for Hopper to $25B for Grace Blackwell and $40B for Vera Rubin, with productivity improving several-fold each generation.
In the case of Hopper, we were at about $18 billion per gigawatt. For Grace Blackwell, we're about $25 billion per gigawatt. And for Vera Rubin, it's about $40 billion per gigawatt. And the productivity is X factors increase in each generation.
Jensen Huang said customers are racing to adopt the next generation of Nvidia systems as quickly as possible.
And so customers want to race to the next generation as fast as they can.
Jensen Huang says AI agents are transforming how every company works, and that capability and security must advance together.
“AI agents are transforming how every company works, and capability and security must advance together,” said Jensen Huang, founder and CEO of NVIDIA.
Huang says a new industrial revolution is beginning and Europe should produce AI rather than merely consume it to join a thriving AI economy.
We are now at the beginnings of a new industrial revolution. We started [music] the new journey to building a new industry. We're going to have [music] a thriving AI economy here in Europe to be part of this AI economy. You don't want to just be consuming the AI. You want to be producing the AI.