DLSS 3 debuted with the RTX 40-series graphics cards, adding Frame Generation technology. With 4x upscaling and frame generation, neural rendering potentially allows a game to only fully render 1/8 (12.5%) of the pixels. Most recently,
DLSS 3.5 offered improved denoising algorithms for ray tracing games with the introduction of Ray Reconstruction technology.
The above timeline raises questions about where Nvidia might go next with future versions of DLSS. And of course, "Deep Learning Super Sampling" no longer really applies, as the last two additions have targeted other aspects of rendering. Digital Foundry asked that question to the group: “Where do you see DLSS in the future? What other problem areas could machine learning tackle in a good way?”
Bryan Catanzaro immediately brought up the topic of full neural rendering. This idea isn’t quite as far out as it may seem. Catanzaro reminded the panel that, at the NeurIPS conference in 2018, Nvidia researchers showed an open-world demo of a world being rendered in real-time using a neural network. During that demo the UE4 game engine provided data about what objects were in a scene, where they were, and so on, and the neural rendering provided
all the on-screen graphics.
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