So that’s what we’re working through. You might have seen our lead times have improved. That’s reflective of the H100, and our lead times from the other parts are certainly longer, and that’s what we’re working our way through when supply commitments and as the demand comes in. I hope that was helpful.
Yvonne McGill: Yes, I might add, from a traditional server standpoint, we’re expecting modest growth, so growth in the upcoming year. AI servers, certainly a very strong growth, especially from a year-over-year standpoint. And then storage, will lag a bit, but we expect tailwinds as the year progresses in the storage portfolio.
Amit Daryanani: That’s perfect. Thank you very much.
Operator: We will now take our next question from Krish Sankar with TD Cowen.
Unidentified Analyst: Hi, thanks so much for taking that question. This is Steven [ph] calling on behalf of Krish. Jeff, if I could, I wanted to double-click a little bit on the storage business. During the January quarter, just given the better-than-seasonal strength there, can you talk about whether that was driven by sort of the early wave of follow-on AI storage demand, following several quarters of AI server demand, or is that coming from traditional storage demand? And secondly, sort of looking out here in the near term, I guess when we look at your PowerStore and PowerScale products, which part of the portfolio are your AI-focused customers spending more of their CapEx dollars on? And any thoughts on, for every dollar an AI server is being spent, is it like $0.50 or $0.75 or about another dollar of incremental AI storage spending for the down line?
Jeff Clarke: Sure, let’s see if I can unpack that question into a few answers. So we look at the demand that we referred to, which was beyond normal seasonality. We had year-over-year demand growth in the unstructured space, ECS, as well as PowerScale. They grew quarter-over-quarter and year-over-year on a demand basis. Those are generally good indicators, as I mentioned earlier, around AI file and object, which are the data classes that generally feed the AI engines. So when I think about AI and the now new products that I mentioned earlier with better read and write performance, better coherency performance in these complex workloads, better density, the 710 era, that’s F710 to be specific, and F210 on PowerScale, and the object scale XF960, those are the types of products that go into these AI workloads.
Our progress in traditional storage was good too. We were ahead of our normal seasonality, what we’ve expected from Q3 to Q4 across our traditional storage business. Although we commented this in our talking points, it was down year-over-year, but better than we expected across mid-range, across our data protection products and our high-end storage products. And then if I think long-term going forward, as we look at the opportunity, and again, we referenced the $152 billion in our web deck, but we’ve done some analysis that’s available out in the public domain, but we’re looking at an opportunity where every dollar that is for a AI server, GPU server, there’s $2 to a growing $3 of professional services around that, networking around that, storage around that.
I won’t parse it down specifically, but what was really important is there’s a drag that the opportunity in the marketplace continues to grow, not only around the computational asset itself, but the network fabric that it’s needed, the storage subsystem to feed it, and then ultimately the professional services to help customers deploy it, but more importantly, figure out where their data is, how to prepare the data. And then ultimately, one of our additional value propositions across that whole spectrum is a financing arm, from the ability to provide the infrastructure of all types, the ability to provide services around that, and then the financing around it, we believe is very much part of our differentiation in the marketplace, particularly as this scales to the enterprise.
Rob Williams: Okay, thanks for your question, Steven.
Operator: And your next question comes from the line of Steven Fox with Fox Advisors.
Steven Fox: Hi, good afternoon. I guess, Jeff, just to follow up on that, I understand the traditional lag between storage and servers, but it seems like based on everything you said, there’s a chance that storage continues to have a little bit more momentum near-term relative to servers. I guess, what am I missing in that, I guess, between going from inference to production type of workloads and seeing some of that extra two to three dollars? Like, why wouldn’t we expect better server growth, rather better storage growth quicker this fiscal year? Thanks.
Jeff Clarke: Well, we believe we reflected that in our guidance for the year in ISG. The opportunities as the richer datasets that are beyond text, text today isn’t very data intensive and can be compressed quite efficiently. As we go to richer data structure, data sets, this unstructured data opportunity exists as we move towards inference and in production. So that’s the opportunity, to be able to call the rate of which enterprise will deploy AI at scale. It’s all upside from my point of view, that we are literally in the early innings of enterprises deploying and moving from proof-of-concept and understanding this helps them drive a massive productivity inside of their enterprise and to allow them to really disrupt how they bring their products and service to the marketplace and how they serve their customers.
Just like we are internally, many customers are going through understanding that and building their agendas. And this is a multi-year cycle. We believe that’s the opportunity here. We’ve said publicly the productivity benefit alone is a once in a generation or once in several generation productivity uplift. And then the ability to think about how you build products and build your services to serve your customers. There’s tremendous capability here that we believe enterprises are in their early characterization and understanding. And it’s a long deployment cycle that we believe will benefit from and that we’re leading the industry in.
Steven Fox: That’s helpful.
Jeff Clarke: Thank you for the questions, appreciate it.
Steven Fox: Of course.
Operator: We will take our next question from the Asiya Merchant with Citigroup.
Asiya Merchant: Hey, thank you for very much for taking my question. Great results by the way. Just a quick question. I know you guys refreshed sort of your AI cam as part of this presentation. Just the questions that I get from investors, as you think about the 150 billion cam that you guys are highlighting now in 27, given Dell’s share in storage, obviously your server, mainstream server share and overall share cam in servers. How do you guys think about your share in this 152 billion market by 27? Should we assume the share that you guys have now for servers and storage translates itself into the 150 billion share cam equivalent? Thank you.
