Pavan Davuluri

take advantage of being able to semantically understand screen content.

In fact, local closed captioning in Windows today on Copilot Plus devices and live translation capabilities in Copilot Plus devices are using local AI models to be able to do these real-time on the fly.

That's a great question, especially in the world of AI.

And I think in my mind, there's a couple of different ways to think about that space.

One, there's a set of capabilities that we think customers will expect out of the Windows user experience on a frequent, recurring enough basis to our conversation that we just want them integrated into the workflows and just kind of be a part of Windows as you think about it.

There, we have a real responsibility for making sure performance, battery life, latency are all well within all other parameters of the operating system.

So it feels like AI is a part of the device, part of your Windows experience, not a thing that got added on later, for instance.

And so for there, a great example for us are these Copilot Plus devices where we've had the ability to work closely with our silicon partners for making sure they have the capability in the silicon platform.

We, as a Windows platform, are able to deliver certain guarantees to the end user because we can expect those base capabilities in the platform and in the use cases that show up in those devices in themselves.

And so neural processors, memory bandwidth on the silicon themselves,

Expectations around system configurations for the hardware itself are all great ways for us for making sure any one of these devices has a certain guarantee of experience.

The other end of the spectrum is where customers know and expect Windows devices to have a diversity of capabilities based on what the device can do for you.

GPUs and gaming are a great example.

Where you as a user know for AAA titles, you have to have a certain level of GPU card performance, a certain level of memory, your GDR specs and so on.

And so we have a lot of developers, enthusiasts in the AI space in Windows for sure, and a certain class of customers as well, who are okay with the ability to be able to take advantage of AI on the devices that they have right now and understand that

you can get better AI performance as a platform gets better.

And so we have customers who use GPUs today.

And the beauty with the framework that we have built with Windows ML is Windows ML lets us take advantage of NPUs for these deep integrated Windows experiences where it makes sense, fully allows us to take advantage of GPUs for either customers, app developers, AI enthusiasts, or developers themselves to be able to take advantage of GPUs for running local AI, knowing that the performance will vary based on the platform.

I think the short answer is yes.

And that's the beauty of it at the end of the day.