“We're expecting next year just with all of the design wins that we have in high performance computing and AI infrastructures, we are on a very, very fast ramp with our first data center CPU to a multi-billion dollar product line.”

In context

“l be able to offer enterprise customers all over the world with their vast sales force and vast network of resellers a fully integrated, if you will, fully optimized, at least end-to-end AI solution. And so that's basically it, bringing AI to Ethernet for the world's enterprise. Operator: Thank you. Your next question comes from the line of Joe Moore of Morgan Stanley. Your line is open. Joseph Moore: Great. Thank you. I'm wondering if you could talk a little bit more about Grace Hopper and how you see the ability to leverage kind of the microprocessor, how you see that as a TAM expander. And what applications do you see using Grace Hopper versus more traditional H100 applications? Jensen Huang: Yeah. Thanks for the question. Grace Hopper is in production -- in high volume production now. We're expecting next year just with all of the design wins that we have in high performance computing and AI infrastructures, we are on a very, very fast ramp with our first data center CPU to a multi-billion dollar product line. This is going to be a very large product line for us. The capability of Grace Hopper is really quite spectacular. It has the ability to create computing nodes that simultaneously has very fast memory, as well as very large memory. In the areas of vector databases or semantic surge, what is called RAG, retrieval augmented generation. So that you could have a generative AI model be able to refer to proprietary data or a factual data before it generates a response, that data is quite large. And you can also have applications or generative models where the context length is very high. You basically store it in entire book into end-to-end system memory before you ask your questions. And so the context length can be quite large this way. The generative models has the ability to still be able to”