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Nvidia is building a walled garden with DLSS — and it’s working

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Over the past two years, Nvidia changed games not with ray tracing, but with DLSS. It’s now enough of a reason to go with Team Green, even if it shouldn’t be.
I just reviewed AMD’s new Radeon RX 6600, which is a budget GPU that squarely targets 1080p gamers. It’s a decent option, especially in a time when GPU prices are through the roof, but it exposed a trend that I’ve seen brewing over the past few graphics card launches. Nvidia’s Deep Learning Super Sampling (DLSS) tech is too good to ignore, no matter how powerful the competition is from AMD. In a time when resolutions and refresh rates continue to climb, and demanding features like ray tracing are becoming the norm, upscaling is essential to run the latest games in their full glory. AMD offers an alternative to DLSS in the form of FidelityFX Super Resolution (FSR). But FSR isn’t a reason to buy an AMD graphics card, and DLSS is a reason to buy an Nvidia one even if it shouldn’t be. Nvidia only offers DLSS on its last two generations of graphics cards — in particular, RTX 30-series and 20-series cards. Walling off features like this isn’t something new for Nvidia. For years, it restricted its G-Sync variable refresh rate technology to monitors that included a dedicated (and costly) proprietary module, instead of adopting the open-source FreeSync developed by AMD. Similarly, many machine learning applications are built to run using Nvidia’s CUDA GPU computing platform, not the OpenCL platform that AMD cards use. Developers have fixed the problem in software libraries like TensorFlow, but there’s still a trend with these libraries: CUDA gets first priority. That leaves us with DLSS, which is also a technology restricted only to Nvidia hardware. There’s a good reason why — DLSS uses an A.I. model that can only run on the Tensor cores on recent Nvidia graphics cards.

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