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AMD's debut

Although limited in scope, AMD’s FSR2.0 debut has raised our GPU hopes

Enlarge / AMD’s artistic interpretation of how FSR works. It’s a bit more complicated than this four-box rendering implies—especially when we consider how much better FSR 2.0 is.Out of all the battles between graphics card manufacturers, the fight over image upsampling and reconstruction is the most interesting to follow, mostly because more gamers can actually…

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AMD's artistic interpretation of how FSR works. It's a bit more complicated than this four-box rendering implies—especially when we consider how much better FSR 2.0 is.

Enlarge / AMD’s artistic interpretation of how FSR works. This is a complicated picture, especially when you consider the improved FSR 2.0.

Out of all the battles between graphics card manufacturers, the fight over image upsampling and reconstruction is the most interesting to follow, mostly because more gamers can actually take advantage of the results. This week, that battle has become even hotter, thanks to AMD finally landing a considerable blow.

Despite only being tested on one game, AMD’s FidelityFX Super Resolution feature (FSR), passed the sniff test last year. This week’s updated “2.0” version works on a larger number of GPUs in the wild than Nvidia’s comparable option, and it lets players get closer to good-enough pixel counts when running on 1440p or 4K panels. But the caveats in play leave us viewing the results as good news for older or midrange GPUs rather than the solution to the supply issues everyone is facing.

A brief explainer on Nvidia DLSS and AMD FSR

Image upsampling, as delivered by the likes of Nvidia and AMD, can take a game with a smaller pixel resolution and intelligently blow it up to fill popular screen resolutions like 1080p, 1440p, and 4K. These systems will produce images that look as sharp as raw pixels if they work properly.

The rollout of Nvidia’s deep learning super-sampling (DLSS) in 2018 came with asterisks, however; it required newer “RTX”-level GPUs, made only by Nvidia, and leaned on dedicated rendering cores. Nvidia’s sales pitch at the time centered on machine learning. After running countless 3D game-rendering scenarios in real time, Nvidia came up with a variety of formulas that could be used to predict which pixels of your games will be drawn next. These formulas could be run on RTX GPUs and produce remarkably accurate guesses in real-time, rendering games looking great without any added latency. Why should your game render the entirety of a 4K-resolution scene, Nvidia essentially asked, if our machine learning model can interpret some

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