This Is How NVIDIA Is Using AI To Improve Game Performance
HWM Singapore|April 2019

A technique that gets smarter over time.

Koh Wanzi
This Is How NVIDIA Is Using AI To Improve Game Performance

NVIDIA’s new GeForce RTX graphics cards launched with several tantalizing hardware-based features that promised to improve performance and image quality. In addition to ray tracing acceleration, NVIDIA announced something called Deep Learning Super Sampling, or DLSS, which uses artificial intelligence to improve performance in games at higher resolutions and settings.

While DLSS was technically available on the RTX cards at launch, it wasn’t until recently that you could take advantage of it in games like Battlefield V and Metro Exodus. Here’s what you need to know about the new technology.

WHAT IS DLSS?

DLSS can be thought as a new form of anti-aliasing. That is something of an oversimplification, but it’s useful as a concept. The technology basically uses a deep neural network – running off the Tensor cores in RTX GPUs – to pull out multi-dimensional features of a particular scene and then combines details from multiple frames to construct a high-quality final image. Aliasing refers to the jagged outlines of an object in a scene, and anti-aliasing mitigates this by filling in the gaps between pixels. This is all very much an approximation though, and there are many different techniques, such as multi-sampling, fast approximate, and super-sampling.

This story is from the April 2019 edition of HWM Singapore.

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This story is from the April 2019 edition of HWM Singapore.

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