Isn’t DLSS by defintion always an AI slop filter?

Not really, DLSS mostly just reduces the resolution of a game and then upscales it back up. It does a pretty good job of making the game still look (almost) exactly the same. This, however, completely changes what you’re looking at.

DLSS is short for Deep Learning Super Sampling, it does the upscaling using deep learning, what people also call AI. The upscaler has to be trained on images. Depending on how you train it you either get something that looks almost exactly the same as the game at a higher resolution or you get AI slop.

I’m aware of how it works, but the results aren’t bad. Worst case scenario is you get some ghosting with DLSS, but it’s far from what I’d call AI slop.

But it literally follows the same process. Why is one slop, but not the other? You’re being hypocrital.

One is upscaling the image while preserving it as much as possible, the other is applying a filter to try and “enhance” it. What’s hard to get?

How is “upscaling while preserving it” not literally the exact same philosophy as “enhance by applying a filter?” You just don’t like the specific filter, it’s very literally the same process.

Current DLSS intent: We can only render this at like 720p with enough frames, so let’s do that and use AI anti-aliasing tricks so that when we present it at 4k, none of the jaggies are visible on-screen like they would be with raw 720p upscaling.

DLSS5 intent: Using our pile of stolen artwork neural net that we can now render at 60fps+ let’s “reimagine” the entire look of the game as we present it on screen, even if it was already running at 4k just fine.

Ideally you’d have a DLSS-like system trained specifically trained for only one game instead of a general system. Then you can train it on 4k with highest settings and you should get something that doesn’t mess with the style of the game.