TheRetroArcade
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Joined: Feb 2026
Joined: Feb 2026
The latest details suggest a real disconnect between the ground truth of a game and the DLSS 5 layer.
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We've been trying to get answers out of Nvidia about DLSS 5 for a couple days now, and we're still waiting to hear if we'll get them. But techtuber Daniel Owen has got some. Detailed in a new video, Jacob Freeman, GeForce evangelist, has provided some rather enlightening details about what DLSS 5 is actually doing.
And it seems right now to be far less smart than I expected.
Given the demos over at the GPU Technology Conference (GTC) this week were being run using a pair of RTX 5090 graphics cards—one to render the games normally and another $4,000 GPU to run the DLSS 5 compute path—it seemed like maybe there was something beyond just the AI filter it seemed on first flush when Jen-Hsun dropped it at the beginning of his GTC keynote this week.
But no, answers direct from Nvidia itself suggest that all the current early preview iteration of DLSS 5 is using as an input is a static, 2D image. As Freeman says: "DLSS 5 takes a 2D frame plus motion vectors as input."
So, unless Freeman is grossly oversimplifying things here, it really is essentially taking a screenshot of a game and applying an AI filter to it. Sure, it's impressive that Nvidia has delivered the compute pathways to allow for this to be done at such a rate of licks that it can effectively be used in real-time during a scene, and that it seems to be able to maintain consistency between those frames, too, but the actual technical elements of the DLSS 5 'enhancements' don't really sound that in-depth.
The DLSS 5 model is only ever aware of the motion vectors attached to a static image (where objects in the scene have come from and where they're going) and a single 2D image. It has no understanding, beyond the flat surface of that frame, of the 3D geometry or depth of a scene, or of the specifics of any lighting found outside of the image in front of it.
Freeman notes the DLSS 5 model has been trained like this, and is designed to be able to infer information about "complex scene semantics such as characters, hair, fabric and translucent skin, along with environmental lighting conditions like front-lit, back-lit or overcast—all by analysing a single frame."
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Every Thursday
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Every Friday
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From the creators of Edge: A weekly videogame industry newsletter with analysis from expert writers, guidance from professionals, and insight into what's on the horizon.
Every Thursday
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Hardware nerds unite, sign up to our free tech newsletter for a weekly digest of the hottest new tech, the latest gadgets on the test bench, and much more.
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We've been trying to get answers out of Nvidia about DLSS 5 for a couple days now, and we're still waiting to hear if we'll get them. But techtuber Daniel Owen has got some. Detailed in a new video, Jacob Freeman, GeForce evangelist, has provided some rather enlightening details about what DLSS 5 is actually doing.
And it seems right now to be far less smart than I expected.
Given the demos over at the GPU Technology Conference (GTC) this week were being run using a pair of RTX 5090 graphics cards—one to render the games normally and another $4,000 GPU to run the DLSS 5 compute path—it seemed like maybe there was something beyond just the AI filter it seemed on first flush when Jen-Hsun dropped it at the beginning of his GTC keynote this week.
But no, answers direct from Nvidia itself suggest that all the current early preview iteration of DLSS 5 is using as an input is a static, 2D image. As Freeman says: "DLSS 5 takes a 2D frame plus motion vectors as input."
So, unless Freeman is grossly oversimplifying things here, it really is essentially taking a screenshot of a game and applying an AI filter to it. Sure, it's impressive that Nvidia has delivered the compute pathways to allow for this to be done at such a rate of licks that it can effectively be used in real-time during a scene, and that it seems to be able to maintain consistency between those frames, too, but the actual technical elements of the DLSS 5 'enhancements' don't really sound that in-depth.
The DLSS 5 model is only ever aware of the motion vectors attached to a static image (where objects in the scene have come from and where they're going) and a single 2D image. It has no understanding, beyond the flat surface of that frame, of the 3D geometry or depth of a scene, or of the specifics of any lighting found outside of the image in front of it.
Freeman notes the DLSS 5 model has been trained like this, and is designed to be able to infer information about "complex scene semantics such as characters, hair, fabric and translucent skin, along with environmental lighting conditions like front-lit, back-lit or overcast—all by analysing a single frame."
Keep up to date with the most important stories and the best deals, as picked by the PC Gamer team.
So, it all just comes down ...Read more: Full article on www.pcgamer.com
What do you think about this?