NVIDIA Predicts DLSS 10 Will Offer Full Neural Rendering Interfaced with Game Engines for Much Better Visuals

wccftech.com:

NVIDIA placed its bets on AI very early and is now reaping the benefits, as evidenced by its incredible growth in the past year. It all began with gaming's Deep Learning Super Sampling, or DLSS, a technique focused on accelerating game performance with the power of AI (specifically, a trained neural network). That's when NVIDIA started putting Tensor Cores in all GeForce graphics cards from the RTX series onward; with the advent of real-time ray tracing, there was a strong need to recoup as much performance as possible.

Over time, NVIDIA evolved DLSS. Version 2.0 delivered much higher quality while maintaining its status of performance accelerator; version 3.0 added Frame Generation, which unlocked new levels of performance, especially in CPU-bound games; and version 3.5 focused on improving the quality of ray tracing under upscaling with the new Ray Reconstruction feature that just debuted in Cyberpunk 2077 to widespread acclaim.

In the final segment of the recent 'AI Visuals' roundtable hosted by Digital Foundry, NVIDIA's VP of Applied Deep Learning Research Bryan Catanzaro said he believes future releases of DLSS, perhaps in version 10, could take care of every aspect of rendering in a neural, AI-based system.

Back in 2018 at the NeurIPS conference, we actually put together a really cool demo of a world that was being rendered by a neural network, like, completely but it was being driven by a game engine. So, basically, what we were doing was using the game engine to generate information about where things are and then using that as an input to a neural network that would do all the rendering, so it was responsible basically for every part of the rendering process. Just getting that thing to run in real time in 2018 was