So running on edge has many benefits. I think my colleague went over some of these uh yesterday and I'll just you know run through this uh really quick also. So certainly like latency is important for those who are keen. Um any of these like real-time camera use cases like filters where you're looking to replace backgrounds or like video calls like real-time latency is king over there. So that's you know on device can help with that. Privacy is also critical for any use cases where you know you have sensitive details, you're doing some kind of summarizing uh documentation which is sensitive offline use cases where you have poor connectivity and costs like you know I've seen so many presentations uh this uh uh AI engineer event where uh people are complaining about the number of tokens that are getting used and this and that but I think uh ondevice always offers this hybrid approach where if you're looking for like how do i really offset you know uh running things on the edge versus on cloud and where can i get the best balance? I think there's a there is something here.

So here's one use case where you're augmenting knowledge and you know for example you can build a skill to query Wikipedia allowing the agent to query uh and respond to any encyclopedia question. So this is a this is a skill that's already available in our app that's uh that's there. So you can kind of see that it's able to create this all on device. It's taking your input, it's feeding it, it's able to understand. So the reasoning and the thinking capability are new in the new model and that the the ondevice capabilities have gotten a lot more powerful. Another similar ex example is going to be on expanding like the core capabilities. So for instance, you can also pair photos and it's going to read the photo and have image understanding and generate music also all on device.

The AI edge portal is a benchmarking tool which could be of interest for those who are looking to deploy broadly on Android. So this is a cloud-based benchmarking service called AI edge portal. Um yeah sorry one more thing on this slide is uh the next part is acceleration. So CPU and GPU are pretty universal right now. Uh NPU acceleration is also another focus. So we have completed uh integration with Qualcomm MediaTek and we are also focusing on additional integrations with other uh partners. I think the NPU is going to give you at least like 3 to 10x improvement in performance and it's going to be a gamecher in terms of the amount of energy you're going to use uh and the amount of performance you're looking for to unlock those use cases. Our runtime is also very performant versus llama. At least on like mobile, we've seen up to like 35 times faster performance.