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Published · transcript-backedSatya Nadella: commitment
12 Nov 2025 Dwarkesh Podcast Satya Nadella — How Microsoft is preparing for AGI
“The way we are going to do it is to have a close loop between our own MAI models and our silicon, because I feel like that’s what gives you the birthright to do your own silicon, where you literally have designed the microarchitecture with what you’re doing, and then you keep pace with your own models.”
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Everything needed to verify it.
- Speaker
- Satya Nadella
- Attribution
- Verified speaker
- Claim type
- commitment
- Recorded
- 12 Nov 2025
- Publisher
- Dwarkesh Podcast
Transcript context
…And when you look at where they are, Google’s way ahead of everyone else. They’ve been doing it for the longest. They’re going to make something like five to seven million chips of their own TPUs. You look at Amazon and they’re trying to make three to five million [Lifetime shipment units]. But when we look at what Microsoft is ordering of their own chips, it’s way below that number. You’ve had a program for just as long. What’s going on with your internal chips? It’s a good question. A couple of things. One is that the thing that is the biggest competitor for any new accelerator is kind of even the previous generation of Nvidia. In a fleet, what I’m going to look at is the overall TCO. The bar I have, even for our own… By the way, I was just looking at the data for Maia 200 which looks great, except that one of the things that we learned even on the compute side… We had a lot of Intel, then we introduced AMD, and then we introduced Cobalt. That’s how we scaled it. We have good existence proof of, at least in core compute, how to build your own silicon and then manage a fleet where all three are at play in some balance. Because by the way, even Google’s buying Nvidia, and so is Amazon. It makes sense because Nvidia is innovating and it’s the general-purpose thing. All models run on it and customer demand is there. Because if you build your own vertical thing, you better have your own model, which is either going to use it for training or inference, and you have to generate your own demand for it or subsidize the demand for it. So therefore you want to make sure you scale it appropriately. The way we are going to do it is to have a close loop between our own MAI models and our silicon, because I feel like that’s what gives you the birthright to do your own silicon, where you literally have designed the microarchitecture with what you’re doing, and then you keep pace with your own models. In our case, the good news here is that OpenAI has a program which we have access to. So therefore to think that Microsoft is not going to have something that’s— What level of access do you have to that?…
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