Jaeden Schaefer

like remains that they're very expensive they're very supply constrained it's hard to get them and so i think google was kind of pioneering this whole approach uh years ago they had their tensor processing unit their tpus which are now on you know they're offered as a cloud service rather than kind of a standalone hardware amazon also followed up and kind of copied google they did tranium

And Inferentia, it's kind of their in-house accelerators for training and inference.

And then recently they also rolled out a new generation that they were kind of aiming at improving some of the price performance and, you know, for like larger models and stuff.

So we see Google doing it.

We do see Amazon with AWS doing it.

So it kind of only makes sense that we're seeing Microsoft get more serious about this.

And I mean, they already had this, the 100 version of this chip.

Now this is the 200 version.

I think Microsoft is now really solidly positioned with Maya kind of as like a peer for some of those other alternatives from Google and Amazon.

And so in their big announcement, they said that it delivered roughly three times the FP4 performance of third generation Amazon Tranium chips and exceeded the FP8 performance of Google's seventh generation TPUs.

So

I think while those types of comparisons often depend on, you know, specific workloads, if we're being 100% honest, I think they do show that Microsoft's in like, they're really trying to be competitive, not just internally, but also across the broader AI kind of cloud market, they know that this isn't just them that it's going to be using these for training, they're going to have other customers and other people doing this.

So

I think it's really important to remember Maya is not, you know, being treated as sort of an experimental side project.

Microsoft says that the chip is already powering internal workloads, which includes models developed by its superintelligence team and also some of their core features of Copilot.

So saying that right now, their AI assistant that is, you know, on like open or on office on,

on all of their enterprise tools.

It is using this.

So by deploying this internally first, I think Microsoft can kind of validate the performance in the reliability, the cost savings, and then they can go and kind of roll this out to other people.

And it's honestly, I mean, that's the greatest validation.