Jaden Schaefer

I think because they kind of have this design, it's very forward looking.

I think this matters because model sizes are continuing to grow.

And I think as companies are increasingly, you know, expecting lower latency, they're expecting kind of this always on AI service rather than a batch style workload, right?

Like you're not going to, I think in the olden days or olden days, but like in the past, it was kind of like, hey, we need like an AI model that's going to go and

run through and do this massive project, it's going to get this huge batch done for us, and then we're going to be done.

When you're looking at like how consumers and how the enterprise is using it today, people are pinging this all day, every day, always, it needs to always be on no one wants latency.

And so it needs to kind of accommodate for that not just like this huge fluctuating, big usage, and then a lull, it's kind of like we're getting this constant steady usage.

So

beyond just like the performance, I think the power efficiency is a really key part of all of this data centers right now, they're already straining against energy constraints, we have even to the top levels of the government talking about, look, you guys need to be building power, power generation, or you know, power creation in some way alongside your data centers, because there just isn't enough.

And that cost gets passed on to the consumer.

Like if you live in an area with a

And they're all getting subsidized.

You are paying for it.

Essentially, your power is going to be more expensive.

So I think the AI workloads are getting really intense right now.

But essentially, by designing this chip and creating its own silicone, Microsoft can tune Maya specifically to its data center layouts, which is a really interesting thought.

Microsoft being, you know, one of the biggest players buying and building these data centers, they could build a chip that's specifically designed for how they structure and run their data centers.

That's, you know, that's like the cooling systems and it's kind of the software framework and they can do all of this to reduce any sort of wasted power and they can smooth out the deployment at scale.

So I think that's a really interesting vertical integration.

It's difficult to achieve with any sort of off the shelf GPU alone that you might get from an NVIDIA or anyone else.