Hock Tan: Correct.
Stacy Rasgon: Got it. Okay. Thank you.
Operator: Our next question comes from the line of Aaron Rakers with Wells Fargo.
Aaron Rakers: Yes. Thanks for taking the question. I wanted to ask kind of continuing on the VMware discussion a little bit. Hock, now that you’ve had the asset for a little while, I’m curious of how you how the go-to-market strategy looks with VMware relative to the prior software acquisitions that you’ve done. What I’m really getting at is kind of like how have you kind of thought about the segmentation of the customer base of VMware? Are you — I know there’s been some discussion around your channel engagement, VM legacy VMware channel in the past. So I’m just kind of curious of how you’ve been managing that go-to-market.
Hock Tan: I think now we haven’t had it for that long, to be honest. It’s like three months, about three months. But yes, it’s what — and it seems to be that things to work out, but things seem to be progressing very well as we had hoped it would. Because where we are focusing our go-to-market — and more than go to market, where we are focusing our resources on don’t just go to market but on engineering a very improved VCF stack, which we have and selling it out there and being able to then support it and in the process that help customers deploy and start to really make it stand up in your data centers. All that focus is on the largest, I would say, 2,000 strategic customers. These are guys who want to still have significant distributed data center on-prem.
Many of our customers is looking at a hybrid situation, not trying to use the word too loosely. Basically, a lot of these customers had some very legacy but critical mainframe. That’s an old platform not growing, except it’s still vital. Then what they have in modernizing workloads cut today and in the future, is they really have a choice, which they are taking both angles of running a lot of applications in data centers on-prem distributed data centers on-prem, which can handle these modernized workloads while at the same time to — because of elastic demand, to be able to also put some of these applications into public cloud. Today’s environment, most of these customers do not have an on-prem data center that resembles what’s in the cloud, which is very high availability, very low latency, highly resilient, which is one we are offering with VMware Cloud Foundation of VCF.
It’s exactly replicate what they get in a public cloud. And they love it. Now three months. But we are seeing it in the level of bookings we are generating over the last three months.
Aaron Rakers: Thank you.
Operator: Our next question comes from the line of Chris Danely with Citi. Your line is open.
Chris Danely: Thanks, for letting me ask question. I have just a question on the AI upside in terms of a customer perspective. How much of the upside is coming from new versus existing customers? And then how do you see the customer base going forward? I think it’s going to broaden. And we know how you like to price. So if you do get a bunch of new customers for these products, could there be some better pricing and better margins as well? Hopefully, they’re not listening to the call.
Hock Tan: Chris, thanks for this question. Love it. Because perhaps let me try to perhaps give you a sense how we think of the AI market, the new generative AI market, so to speak, using it very loosely and generically as well. It’s really — we see it as two broad segments. One segment is hyperscalers, especially very large hyperscalers with huge, huge consumer subscriber base. You probably can guess who this few people are, very large subscriber base and very — an almost infinite amount of data. And their model is getting subscribers to keep using this platform they have. And through that, be able to generate a better experience for not only the subscribers, but a better advertising opportunity for their advertising clients.
It’s a great ROI as we are seeing ROI that comes very quickly. And the investment continues vigorously with those — with that segment, comprising very few players. But we will choose subscriber base, but with the scale to invest a lot. And here, ASICs custom silicon, custom AI accelerators makes plenty of sense and that’s where we focus that attention on. They also buy as a scale out those AI accelerators, through clusters increasing large clusters because of the way the models are running, the foundation models run and large language models need to generate those parameters. They buy a lot of networking together with it. But in comparison, obviously, to the value of AI accelerators we sell. Now the network working side, while growing its small percentage compared to the size, the value of the accelerators.
That’s one big segment we have. The other segment we have, which is smaller is the enterprise, what I broadly call enterprise segment in AI. Here, you’re talking about companies, large not so large, but large who wants to do — who have AI initiatives going on. All these big news and hype about AI being the savior to productivity and all that gets all these companies on multiple on their own initiatives. And here, short of going to public cloud, they’re trying to run it on-prem. If they try to run it on-prem, they take standard silicon for an AI accelerators as much as possible. And here, in terms of the AI accelerator, we don’t have a market. That’s the merchant silicon market. But in the networking side as they tie it together with their data centers, they do buy all those are — our networking components beginning with switches, routers even through people like Arista 7800 but switches for sure, and the various other components I mentioned.
And that’s a different sense market that we have. So it’s an interesting mix, and we see both.
Chris Danely: Thanks a lot, Hock.
Operator: Our next question comes from the line of Karl Ackerman with BNP Paribas. Your line is open.
