“Exiting Q4 2024, is it possible to get to $1.5 billion? It is possible, right, because Lisa mentioned earlier, we'll see sequential increase in each quarter and more back-end loaded in second-half and we do have a supplies more than $3.5 billion.”

In context

“compared to the competition. And what that means is for large language models that are many tens of billions of parameters you make -- you could potentially do the workload in fewer GPUs. So, it's a substantial system savings and allows you to do much more work within the same system. In terms of what customers are using MI300 for today, I would say there are a number of customers using it for large language model inferencing and there are also customers that are using it for training. So I think the whole point is being a strong partner. When you put these AI systems in-place, they are sometimes mixed-use systems. So they would be used for both training and inference. Mitch Haws: John, we have time for two more questions. Jean Hu: Yeah, Harsh. Let me answer your question about the MI300. Exiting Q4 2024, is it possible to get to $1.5 billion? It is possible, right, because Lisa mentioned earlier, we'll see sequential increase in each quarter and more back-end loaded in second-half and we do have a supplies more than $3.5 billion. And of course we will continue to make progress with our customers. So the math, yeah, it's possible, but right now we are really looking at focus on the execution of the current $3.5 billion plus. Operator: And the next question comes from the line of Stacy Rasgon with Bernstein Research. Please proceed with your question. Stacy Rasgon: Hi, guys. Thanks for taking my questions. For the first one, you talked about the -- you expected a more shallow ramp of the MI300 and it's clearly doing better than that. So, some of the upside I guess in the near-term is that being pulled forward from the second-half or is this like a step-up or is it more of a step-up in-demand both in the first half and the second-half relative to what you were seeing before? Like how do I interpret that by shallow co”