A touch off topic since the review did not cover DLSS (coming in later article). This is my best understand of DLSS 3. I am not up to speed on how DLSS 4 changes things, but I assume the concept is the same. I don't claim to be an expert and cutting through the marketing BS is not easy.
Deep Learning Super Sampling (DLSS) uses "AI" to boost gaming performance and visual quality. It consists of two main features:
1) Upscaling
- Renders the game at a lower resolution, then uses a trained neural network to upscale it to a higher resolution.
- Enhances anti-aliasing and detail, allowing higher framerates without requiring as much GPU power as native resolution.
2) Frame Generation
- Inserts extra frames that are AI-generated rather than fully rendered. This can effectively double (or more) the displayed framerate.
- Crucially (and the contentious part), it works concurrently with the GPU’s rendering. As soon as a real frame is finished rendering, DLSS immediately begins predicting the next AI-generated frame and displays it. Meanwhile, the GPU is busy rendering the subsequent “real” frame.
Because these "AI frames" are extrapolations, they rely on motion vectors, optical flow, and depth data to guess how the scene and user inputs evolve between rendered frames. Although user commands influence the game engine’s updates (and thereby the motion vectors), the AI’s predictions still reflect slightly older data, so Frame Generation does not reduce input lag. In fast-paced games, this can lead to a sense of detachment—your inputs are processed, but the AI frame you see may not perfectly capture your latest actions.
Despite this limitation, DLSS Frame Generation provides a substantial framerate boost as seen by the human. Coupled with DLSS Upscaling, it can enable higher resolutions and potentially smoother visuals, balancing real-time performance and image fidelity through AI-driven techniques. How useful DLSS is to you really depends on your desired "balance".