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| System Name | Silent/X1 Yoga/S25U-1TB |
|---|---|
| Processor | Ryzen 9800X3D @ 5.4ghz AC 1.18 V, TG AM5 High Performance Heatspreader/1185 G7/Snapdragon 8 Elite |
| Motherboard | ASUS ROG Strix X870-I, chipset fans replaced with Noctua A14x25 G2 |
| Cooling | Optimus Block, HWLabs Copper 240/40 x2, D5/Res, 4x Noctua A12x25, 1x A14G2, Conductonaut Extreme |
| Memory | 64 GB Dominator Titanium White 6000 MT, 130 ns tRFC, active cooled, TG Putty Pro |
| Video Card(s) | RTX 3080 Ti Founders Edition, Conductonaut Extreme, 40 W/mK 3D Graphite pads, Corsair XG7 Waterblock |
| Storage | Intel Optane DC P1600X 118 GB, Samsung 990 Pro 2 TB |
| Display(s) | 34" 240 Hz 3440x1440 34GS95Q LG MLA+ W-OLED, 31.5" 165 Hz 1440P NanoIPS Ultragear, MX900 dual VESA |
| Case | Sliger SM570 CNC Alu 13-Litre, 3D printed feet, TG Minuspad Extreme, LINKUP Ultra PCIe 4.0 x16 White |
| Audio Device(s) | Audeze Maxwell Ultraviolet w/upgrade pads & Leather LCD headband, Galaxy Buds 3 Pro, Razer Nommo Pro |
| Power Supply | SF1000 Plat, 13 A transparent custom cables, Sentinel Pro 1500 Online Double Conversion UPS w/Noctua |
| Mouse | Razer Viper V3 Pro 8 KHz Mercury White w/Pulsar Supergrip tape, Razer Atlas, Razer Strider Chroma |
| Keyboard | Wooting 60HE+ module, TOFU-R CNC Alu/Brass, SS Prismcaps W+Jellykey, LekkerL60 V2, TLabs Leath/Suede |
| Software | Windows 11 IoT Enterprise LTSC 24H2 |
| Benchmark Scores | Legendary |
NVIDIA has leveraged their expertise in neural networks and deep learning to release an interesting new feature with their R530 driver branch, an AI video stream upscaler designed to take advantage of RTX Tensor Cores when playing video content within Chromium based browsers. Our previous news article on RTX Video Super Resolution (VSR) covered the release of Chrome 110 stable, which included support for this technology. The latest version of Microsoft Edge, based on Chromium, also officially supports RTX VSR. Owners of NVIDIA RTX graphics cards may have been puzzled by exactly how to enable this feature however, either in Chrome 110 or in the NVIDIA Control Panel, since the relevant 'NvidiaVpSuperResolution' setting is enabled by default within Chrome, but the required accompanying driver has only just been released, three weeks later.
To use RTX VSR, you'll need a RTX 30 or 40-series graphics card, be running the latest NVIDIA GeForce Graphics Driver, and have enabled the "RTX Video Enhancement" option within the NVIDIA Control Panel, under the "Adjust video image settings" submenu. There are four quality presets, with "1" being the lowest and "4" being the highest, while also using the most GPU resources. Owners of RTX 20-series cards will have to wait for NVIDIA to enable this functionality for their GPUs, once the engineering work is completed for that architecture.
Some comparison screenshots, taken on my personal system with a 3080 Ti and a 1440p monitor, it seems the technology is most noticeable when applied to videos at 720p resolution and below.
Similar to the well received NVIDIA Shield TV, which could take 720p or 1080p content and upscale it to 4K at up to 30 frames per second using the AI hardware within the Tegra X1+, RTX VSR is a further, more advanced development. Using the more powerful hardware on modern RTX graphics cards, RTX VSR automatically upscales content played from within your browser between 360p and 1440p, to 4K, improving detail and removing the compression artifacts streamed content is known for.
NVIDIA's RTX VSR FAQ and blog post answers some common questions and provides further details on how the technology works.
You can take a look at NVIDIA's comparison video or try enabling the feature yourself to decide how well NVIDIA's efforts have paid off. As we've seen with other AI based deep learning solutions, the technology will continue to improve with time. In it's current state, RTX VSR seems particularly well suited for increasing the clarity of videos uploaded at lower resolutions or bitrates, such as older videos or live streamed content from Twitch or YouTube. Those using capped or slower network connections limiting their streaming options should also appreciate being able to efficiently consume content without sacrificing too much in image quality. I can't wait to see where the iterative path leads, as this technology could be as impactful in video media as AI based upscalers were for gaming!
Update: After further testing of a YouTube stream of in game content, set to 480p and 720p, isolated differences between RTX VSR enabled at setting '4' and disabled can be shown.
Looking closely at the barrels, trees, textures on the surfaces, text on the container, and straight lines for example the roof of the service station, we can see image quality improvements with RTX VSR enabled and set to '4' quality.
While these image quality improvements certainly exist, I have some questions as to how many owners of RTX 30 and 40-series graphics cards spend their time watching low resolution streams, since improvements are much less obvious when using higher resolution source material. This technology seems ideally suited to portable applications, where there is limited internet bandwidth available, such as smartphones on mobile networks, or laptops on the go using slow wireless connections. Unfortunately, NVIDIA requires laptops to be plugged into mains power to use RTX VSR, due to the additional power drawn by the Tensor Cores required for image processing (most laptops would use iGPU via Optimus under light graphics loads, and RTX VSR requires the discrete GPU to be active), and there are no smartphones that have RTX features. The way I see it, it's a zero effort (after initial setup, which takes a minute or so) way to get slightly better image quality, scaling less as you go up in source resolution, with a negligible draw on system resources. There is also the case where many older videos from the earlier days of the internet tend to be only available in relatively low resolution, so this technology can certainly come into play to offer a more contemporary image quality.
View at TechPowerUp Main Site
To use RTX VSR, you'll need a RTX 30 or 40-series graphics card, be running the latest NVIDIA GeForce Graphics Driver, and have enabled the "RTX Video Enhancement" option within the NVIDIA Control Panel, under the "Adjust video image settings" submenu. There are four quality presets, with "1" being the lowest and "4" being the highest, while also using the most GPU resources. Owners of RTX 20-series cards will have to wait for NVIDIA to enable this functionality for their GPUs, once the engineering work is completed for that architecture.
Some comparison screenshots, taken on my personal system with a 3080 Ti and a 1440p monitor, it seems the technology is most noticeable when applied to videos at 720p resolution and below.
Similar to the well received NVIDIA Shield TV, which could take 720p or 1080p content and upscale it to 4K at up to 30 frames per second using the AI hardware within the Tegra X1+, RTX VSR is a further, more advanced development. Using the more powerful hardware on modern RTX graphics cards, RTX VSR automatically upscales content played from within your browser between 360p and 1440p, to 4K, improving detail and removing the compression artifacts streamed content is known for.
NVIDIA's RTX VSR FAQ and blog post answers some common questions and provides further details on how the technology works.
You can take a look at NVIDIA's comparison video or try enabling the feature yourself to decide how well NVIDIA's efforts have paid off. As we've seen with other AI based deep learning solutions, the technology will continue to improve with time. In it's current state, RTX VSR seems particularly well suited for increasing the clarity of videos uploaded at lower resolutions or bitrates, such as older videos or live streamed content from Twitch or YouTube. Those using capped or slower network connections limiting their streaming options should also appreciate being able to efficiently consume content without sacrificing too much in image quality. I can't wait to see where the iterative path leads, as this technology could be as impactful in video media as AI based upscalers were for gaming!
Update: After further testing of a YouTube stream of in game content, set to 480p and 720p, isolated differences between RTX VSR enabled at setting '4' and disabled can be shown.
Looking closely at the barrels, trees, textures on the surfaces, text on the container, and straight lines for example the roof of the service station, we can see image quality improvements with RTX VSR enabled and set to '4' quality.
While these image quality improvements certainly exist, I have some questions as to how many owners of RTX 30 and 40-series graphics cards spend their time watching low resolution streams, since improvements are much less obvious when using higher resolution source material. This technology seems ideally suited to portable applications, where there is limited internet bandwidth available, such as smartphones on mobile networks, or laptops on the go using slow wireless connections. Unfortunately, NVIDIA requires laptops to be plugged into mains power to use RTX VSR, due to the additional power drawn by the Tensor Cores required for image processing (most laptops would use iGPU via Optimus under light graphics loads, and RTX VSR requires the discrete GPU to be active), and there are no smartphones that have RTX features. The way I see it, it's a zero effort (after initial setup, which takes a minute or so) way to get slightly better image quality, scaling less as you go up in source resolution, with a negligible draw on system resources. There is also the case where many older videos from the earlier days of the internet tend to be only available in relatively low resolution, so this technology can certainly come into play to offer a more contemporary image quality.
View at TechPowerUp Main Site
