 And here are the ARM booths. So who are you? So I'm Michael McGee. I'm the Tech Lead of Develop Relations. And I'm just here to show you some demonstrations. So this is the ARM Mali area? Yeah, so we're showing here our capabilities of our graphics processing units. So this demonstration here has a Mali T760 MP8 implementation. And what I'm about to launch here, this is Android 5 running in a 64-bit environment. And we are showing here a demonstration using the Epic Unreal Engine in native 64-bit application. So I can walk around, for example, to prove that it's fully interactive. So the 64-bit and the GPUs are on the 64-bit. The ARM processor just accelerates everything? Yes. So we're seeing various different use cases for 64-bit, including gaming. And what we're showing here is this is just basically a straight port of the engine to run on 64-bit. But there's plenty of optimization left to do to fully utilize the 64-bit capabilities. What kind of optimizations are still in the works? So from the CPU side, we can take better use of the neon generation co-processor as well as increased registers, things like that. On the GPU side, we've implemented ASTC textures for all of the texturing you can see, as well as PLS, Pixel local storage, which basically gives you better capabilities. So certain post-processing steps, you can now utilize the on-chip memory to accelerate that. So in this instance, you can see the bloom and the particle effects are accelerated with the use of PLS. Cool. And you have another demo right here? Yes, this demonstration we actually showed last year. This is P4P4 with Rockchip 3288. Exactly. So this, again, is a T760, but in an MP4 configuration. And we're basically showing the graphical richness that a mid-ranged other device like this is capable of doing. This demonstration is actually also using the Enlighten engine. So this is real-time global illumination from Geomerics, which you can see in several popular titles as well. Cool. And this is a different use of the GPU right here, right? Yes, exactly. So not only do our GPUs just do graphics, you can also run general processing, compute activities on them as well. So for example, we have some camera algorithms running here. So in this instance, we are showing image stabilization. If I switch the camera to the other side, let's get something interesting. For example, this. On the left, you can see the image preview after image stabilization, whereas on the right is the raw camera feed. So this example of image stabilization, you don't need dedicated hardware for. You can run it on the GPU itself. Nice. Is this shipping, or is this something that's kind of like a demo of the future of optimization? Actually, we have a production device with the exact same chip set in this one here. So this is the Lenovo Note 8. In this particular demonstration, we're showing also low-level lighting. So if you can look in the camera here, on the left is the low-level lighting algorithm, lighting up the dark scene. On the right is the original camera footage. And you can see a distinct difference and clarity in any picture. Nice. So you are improving a bunch of stuff with imaging using the GPU. Exactly. And it's not just imaging that you can apply general purpose computing capabilities to. You can do it with video, for example, and a whole host of different applications. Nice. So this is kind of like GPU compute for imaging? Yes, exactly. All right. So shipping, the latest GPU showcase, and big low. And the T760 GPU.