Ziad Asghar19:10
Thank you, Hugo. You can see the potential of this collaboration, right? This vast platform that we have with us, which is basically Android, and how we're able to bring that to the XR space along with Android XR on the Moohan-like platform. We also have our partners at XREAL, who I believe Chi will be going on today also on the stage. And this actually uses again our technology as well, working with what XREAL has done on Project Aura. This is a lighter platform with optical see-through, again giving the consumers all the options to be able to really bring all those advantages to the consumers and our partners. Again, it utilizes the six degrees of freedom perception technology and many of the capabilities that we have in our solutions through the wired compute device.
All right. So, continuing on the Android XR theme now, I want to first of all thank all of our great Snapdragon Spaces partners who have done amazing experiences that they have created on Snapdragon Spaces. I want to today talk about how we want to take their investments and the work that they have done and move into the Android XR realm. So, again, I'm super excited today to be announcing the Snapdragon Spaces compatibility plugin for Android XR. It's available now. You can absolutely start to download it and start to work on it. This is, there's going to be a session tomorrow at 1:00 p.m. where we're going to actually work with Unity to be able to show you the full experience as to how you can take your application and your work onto the Android XR platform. And actually, one of our partners, Siru, did that exercise, and in about a couple of days, they were actually able to take their work from Spaces onto Android XR. Very promising and very, very exciting as to what we have coming up next with our developer partners.
All right, so I talked about this slide in the beginning, and if you notice, what I really wanted to spend a little bit of time on was the rightmost part on this slide, which is that we have talked about how we can offload a lot of the work on the AI and the rendering side when we talk about doing AI processing on these light devices. But I also want to talk about how this device itself has the capability to be an individual device that you use just as a standalone device. That means to be able to do certain amount of AI processing on that device. And that's what I want to talk about next. Now, AI is super central when it comes to XR, whether we talk about MR or whether we talk about AR. Now, when you discuss MR, one of the challenges that people have had is the availability of content. But today we can apply techniques like Gaussian splatting and NeRFs and others to be able to bring 2D content into the 3D content realm. We can take models that are basically speech-to-3D, text-to-3D models. We have models like Sora and Stable Diffusion and others that basically enable us to be able to bring amazing content into the MR space. At the same time, you can go into a game and you can say, 'Well, create me this sword,' and GenAI can actually create that for you on the fly. What I envision is basically that the device knows your likes and dislikes and the colors and textures and the themes that you like. And it's actually able to create a world that's suited to you and to you, just each one of you. It's not a world that basically a graphic designer creates in one place and everybody gets to see it, but it is something that's customized to each one of you. And that's the personalized experience that I believe generative AI can bring in MR. Similarly, on the AR side, like I said earlier, you can actually have an agent, an assistant that's sitting on your glass that can help you with fitness, that can help you with navigation, but really what it is is it can actually take full tasks, break it down into smaller pieces, and actually execute them for you. That is the promise of AR with AI. And similarly, if you see on the slide, I think the key part also is the contextual information that we are able to get. We have these amazing technologies within our solutions such as the Snapdragon XR and AR product lines where you can actually take the content, the context, and be able to put it into this sensing hub. And if you look at the context information that you have on a watch versus the context information that you may have on a smartphone or an auto, it's very different. But you can imagine now that if I could combine that context, I can do generative AI far better than what you can do on a single device. What do I mean by that? With a smart glass, it's able to see what I'm able to see. It's able to hear what I hear. With a smartwatch, I know the heart rate, I need the stress level, I know the activity level. If you can combine all of that into a generative AI experience, you really get to a point where basically you can have true personalized hybrid AI. And that's what we're driving the technology towards. Of course, we're working with all of our partners today to be able to make that happen.
All right, so we spent a little bit of time talking about all the devices today. The devices that you see coming up, they're all driven by our platform, the Snapdragon AR1 Gen 1. Now, I'm very, very excited to be talking about a new member of our product roadmap, which is the Snapdragon AR1 Plus Gen 1. And we've actually made this happen with all that we hear from our partners. And we have it launching today. This platform is going to be the world's most advanced solution for AI smart glasses. Why do I say it's the most advanced solution for AI smart glasses? If you look at the key vectors that are important from an AI smart glasses perspective, you need a smaller package. You need it to be able to fit on the side of your glasses. Well, we've reduced that by 20%. We've improved the power by 7% in many of the key use cases. And most importantly, one of the key features is the camera technology. We've brought in basically massive multi-frame engine and motion-compensated temporal filtering to get to the highest-end camera capability. You can imagine you're sitting in a dark restaurant in the night. You have a menu in front of you. You want your smart glasses to be able to read that text on it. That requires this technology. So we brought that into space. But something that I'm really, really excited about is what I said on the previous topic, which was this device can do on-device language models. Can you imagine the session that you do with ChatGPT? You can actually do it just on a smart glass, not connected to the cloud, not connected to a smartphone, not relying on any other device. So we can run a billion-parameter model natively on this smart glass with very good time-to-first-token and about 13 tokens per second, which is actually pretty darn fast. But I don't want to just talk about it. I actually want to show you the world's first on-glass language model demo. So with that, I'll actually talk about how we have these three different models that are running.
Interestingly, I can get a language model to run on this frame, but I can't keep my mic on. But nonetheless, world's first small language model demo. So, we'll be talking about taking three models there. And if I can get the device, I'd like to give you guys a demo.
Okay. So, hopefully you'll be able to see what is being projected and what I'm seeing on my glasses over here. Ask your question after the chime. What is Newton's third law of motion?