News that Microsoft had been developing its own AI-powered upscaler for games, called Automatic Super Resolution, first came to light back in February, before it became clear that this system would only be available on Copilot+ AI PCs. At the moment, the only systems in this ecosystem are Snapdragon X laptops from Dell, Asus, MSI, and others. But as Microsoft explains in a blog on how Automatic Super Resolution works, the PC just needs to have a suitable NPU in its main processor, so it could become available to more gamers.
Super resolution, or upscaling as it is generally called, involves rendering a frame at a lower resolution before running a bunch of math operations to to raise the resolution to that of the monitor. The obvious benefit is that the game will run a lot faster, but upscaling often creates lots of visual artefacts, especially with transparent objects, particles, and fast motion.
Nvidia uses a convolution neural network, via Tensor cores on GeForce RTX graphics cards, to scan an upscaled frame and clean up any issues. Intel does the same with its Arc-specific XeSS but its generalised version is the same as AMD's FSR—a lot of clever shader routines calculate the best possible upscaled frame, rather than using AI.
Microsoft's Automatic Super Resolution (ASR) works a little bit like DLSS and Arc-only XeSS, in that a neural network is used in the upscaling algorithm. But rather than use the specialised cores in a GPU, ASR runs the network on an NPU, a neural processing unit. At present, these are only found in certain CPUs—Intel's Meteor Lake, some of AMD's APUs, and Qualcomm's Snapdragon X—and handle math routines that are common in AI workloads.
The idea behind the inclusion of an NPU in a processor is that AI stuff can be offloaded from the CPU or GPU, and run on a low-power section of the chip. They're a bit like the matrix cores you get in an Intel Alchemist GPU.
But even if you have a PC with any of those chips, you won't necessarily be able to
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