00:00 Speaker A
When I am an Nvidia investor, I listen to this Patrick. There are some bulls on the street, I know, who are actually getting more enthusiastic about the second half. And I am curious what you think about that, and under the reasons for the excitement they talk about it, as you suggested, there can be this China -in line chip. They talk about, hey, listening, the cloud giants, we have heard, they continue to spend, spending, spending and the company with Saudi Arabia and the VAE. Am I missing something, Patrick?
01:03 Patrick
No, I think, uh, nvidia has been loaded for a while, and that is when, when Blackwell strikes, uh, what, um, does many more tokens per dollar per second, and many of the hyperscalers are actually waiting, uh, on Blackwell. I think they didn't buy as many H -series as they could have because the economy is so good for them. I also like the move where Nvidia Blackwell has divided a bit, UH, by retiring to an aggressive chassis design where you can actually use many of the same components for the Blackwell 200 if you did for the Blackwell 300. So, the second half is, will be great. Uh, the Capex predictions indicate that that, and Nvidia seems to have everything in line. Uh, looks like a little less risk than the first half.
02:59 Speaker A
I want to change acceleration, Patrick, get your opinion about another technical story, which was Salesforce that acquires computer science for $ 8 billion. Here was the skeptical Take I, I saw RBC's Rishi Jaluria. Rishi who tells his customers, while the deal can be logical on paper, integrate Mulesoft, Tableau and Data Cloud and uses that combination for Power Agent Force, given the lack of integration of Salesforce assets, we ask this vision, he says. Moreover, even if this logic is useful, we wonder if this was the case, whether there is a big advantage to buy computer science versus cooperation. What is your response to that, Patrick?
4:03 AM Patrick
So I like the statement here. UH, with all the CIOs I meet, one of their top five obstacles to rolling out and scales of generative AI is the lack of a coherent data management strategy and the tools to be able to collect all that data. In the Gen Ai World you go from the east and you go from the west in contrast to the, the ML world, which was north and south. And what that means is, uh, instead of alone, say, uh, activating CRM data, you connect CRM with ERP with SCM with all these other data sets. And that is why this makes sense to me. It is also, uh, parallel to the great growth in DataWolk that we have seen, UH, with Salesforce. We have seen this enormous growth with even companies such as SAP, right? The precursor of Big Gen AI promotion is getting your data in line. I do think that the comment is fair about a lack of integration, but I expect that integration will happen and have to happen at a very fast pace. Complexity is again one of those top issues. And if Salesforce, UH, can reduce part of that complexity, reducing some of those steps, some of those operational challenges can reduce, I think they have something here.
