Why Microsoft built a fungible fleet and said no to OpenAI

Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

1. 42:41

   Yeah, it's a great question because, see, the thing that we realized, and I'm glad we did, is that the concept of building a fleet that truly was fungible, fungible for all the parts of the lifecycle of AI, fungible across geographies, and fungible across generations, right? Right. So because one of the key things is when you have, let's take even what Jensen and team are doing, right? I mean, they're at a pace. In fact, one of the things I like is the speed of light, right? We now have GB300s bringing, you know, that we're bringing up. So you don't want to have ordered a bunch of GB200s that are getting plugged in only to find the GB300s are in full production. So you kind of have to make sure you're continuously modernizing, you're spreading the fleet all over, you are really truly fungible by workload, and you're adding to that the software

2. 43:37

   optimizations we talked about. So to me, that is the decision we made. And we said, look, sometimes you may have to say no to some of the demand, including some of the open AI demand, right? Because sometimes, you know, Sam may say, hey, build me a dedicated, you know, big, you know, whatever, multi-gigawatt data center in one location for training. Makes sense from an open MAI perspective. doesn't make sense from a long-term infrastructure build-out for Azure.

3. 44:04

   And that's where I thought they did the right thing to give them flexibility to go procure that from others while maintaining, again, a significant book of business from OpenAI, but more importantly, giving ourselves the flexibility with other customers, our own 1P. Remember, like one of the things that we don't want to do is be short on, you know, we talk about Azure. In fact, some of the times our investors are overly fixated on the Azure number.

4. 44:30

   But remember, for me, the high margin business for me is co-pilot. It is security co-pilot. It's GitHub co-pilot. It's the healthcare co-pilot. So we want to make sure we have a balanced way to approach the returns that the investors have. And so that's kind of one of the other misunderstood, perhaps in our investor base in particular, which I find pretty strange and funny because I think they want to hold Microsoft because of the portfolio we have.

5. 44:55

   But man, are they fixated on the growth number of one little thing called Azure. On that point, Azure grew 39% in the quarter on a staggering $93 billion run rate. And I think that compares to GCP that grew at 32% and AWS closer to 20%. But could Azure, because you did give compute to 1P and because you did give compute to research, it sounds like Azure could have grown 41%, 42% had you had more compute to offer. Absolutely. There's no question. There's no question. So that's why I think the internal thing is to balance out what we think, again, is in the long-term interests of our shareholders and also to serve our customers well. And also not to kind of, you know, one of the other things was, you know, people talk about concentration risk, right?

6. 45:45

   We obviously want a lot of open AI, but we also want other customers. And so we're shaping the demand here, you know, we are in a supply, you know, we're not demand constrained, we're supply constrained. So we are shaping the demand such that it matches the supply in the optimal way with a long-term view. To that point, Satya, you talked about 400 billion, it's incredible number