That doesn't guarantee maanHimself is the original author, but it's looking likely.
Programmer: OpenDLSS...
Jensen : Wait. Not like that! (╯°□°）╯︵┻━┻
But the line is drawn when it involves CUDA and any part of their closed source compilers (nvcc).
There are obvious reasons why they are closed source, but it’s becoming pointless since Deepseek have open sourced their AI compiler and compute libraries with DeepGEMM and eventually they will catch up.
At least their support helps the open-weight ecosystem.
They care when the agendas align, and they don't when they won't.
What kind of sorcery is this ? Very impressive work !
Nowadays it takes one well written prompt to a frontier LLM to produce something like this.
LLMs are really good at deobfuscating or even decompiling code.
The current implementation is more of a tech demo than a practical way to play games (+ officially it's available in 1 game). It's _fast enough_ to make some impressive YouTube videos but you most likely won't want to play anything with it yet.
Nvidia has stated that they're still working on improving the performance. No doubt future hardware generations will also include further hardware optimisations.
The potential for this kind of technology is pretty awesome, especially given that people have also found ways to add this to emulators.
Again, I hope I’m wrong and we see new cards summer/autumn 2027, but I would not bet my savings on it.
RTX 5060: 9.9 ms at 1080p
RTX 5070: 10.2 ms at 1440p
RTX 5080: 13.7 ms at 2160p
RTX 5090: 8.2 ms at 2160p
I think its somehow needs to talk (write) about the things that are in the context and removal is there so AI predicts that it should be there.
This is how I feel about every single project announcement on HN recently, they are already bragging about models all over the place, why shouldn't they go full way down being replaced by the Borg?
Unfortunately it is slop, beyond the comprehension of the author unless they are experienced with DLSS internals to explain it in depth.
Isn't the mote that Nvidia has is they work with studios to generate the training data from the game, then they ship a model per game?
Or is my knowledge outdated here and they're just using a single generalised model?
> Isn't the mote that Nvidia has is they work with studios to generate the training data from the game, then they ship a model per game?
That was true for the very first version of DLSS, from DLSS 2 on the models have been universal - the per-game adjustments are done on the inference end by changing the effect intensity or masking out objects
They have a technical report on the neural rendering part of DLSS 5 which goes into it: https://research.nvidia.com/labs/adlr/files/DLSS5_Report.pdf
They don't. Only DLSS 1 was trained specifically per each game.
there's no way that's true!?
> The temporal path is implemented, but in the demo: the network's history input lanes and its per-pixel blend logit drive a reprojected feedback loop (docs/frame.md). The dlss5vk tool runs single frames with no history, which is what the reference captures were made with.
From this I assume the network uses the (via motion vectors) reprojected previous frame in order to increase temporal stability, i.e. similarity over adjacent frames. But this isn't strictly necessary, and apart from it, DLSS 5 is a pure post-process filter. So you could apply it to an old animated CGI movie like Final Fantasy (2001) [1]. Which should make it look significantly more realistic, at the cost of some flicker or other temporal instability.
One could also apply it to still images, like old renders from Tomb Raider [2], where temporal stability is not a factor. The difference to conventional text-to-image models with a "make it photorealistic" prompt would be that DLSS 5 strongly adheres to the underlying geometry.
1: https://www.imdb.com/title/tt0173840/
2: https://www.tombraiderchronicles.com/images/artwork-high-res...
Especially egregious if both adding and removing the thing happens in one commit. Git should be telling the story, and if it can't then there _is_ no story!
AI probably should not be writing docs, commit logs or comments.
