#Nvidia_Technology

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But you need two video cards Nvidia DLSS and AMD FSR upscalers have their own variants of frame generation technology, which work differently and are available on different video cards. But it turns out that these technologies can be made to work together. [caption id="attachment_85199" align="aligncenter" width="780"] Nvidia DLSS 3 and AMD FSR 3[/caption] The authors from QuasarZone decided to check whether it would be possible to make the HR generation technologies of two companies work on one PC, and it turned out that it would work. But only in a very specific way, and the results are ambiguous. [caption id="attachment_85200" align="aligncenter" width="780"] Nvidia DLSS 3 and AMD FSR 3[/caption] Frame generation technologies in Nvidia DLSS 3 and AMD FSR 3 forced to work together This all works thanks to the fact that AMD has an AFMF generator built into the driver, otherwise it probably would not have been possible to implement the idea. However, the system must still have two different 3D maps. In this case, the authors of the idea used the RTX 4090 and RX 6600. The game (in this case, several projects, including Cyberpunk 2077) was rendered on an RTX 4090 card. It also allowed DLSS 3 to be activated with frame generation. Next, the RX 6600, to which the monitor is connected, comes into operation. Technically it is used for image output, but the AMD driver allows you to improve performance through AFMF before outputting the image. That is, the AMD frame generator adds frames to a picture that the Nvidia generator had previously added frames to. At the same time, productivity increases greatly. Almost three times the original value and twice the value obtained after the generator in DLSS 3. This implementation, surprisingly, does not cause any special technical problems. Is it possible that the 1% Low indicator may even decrease in a number of games, although in Cyberpunk it has increased. In addition, it is worth remembering that AFMF technology turns off as soon as the player starts moving the camera quickly, but in quiet modes it automatically turns back on. Unfortunately, the authors did not pay attention to image quality, which is very important, given two technologies for completing frame drawing.

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January 8 It looks like Nvidia GeForce RTX 40 Super video cards will be presented in early 2024 at CES 2024. At least Nvidia has already announced a special event. [caption id="attachment_80889" align="aligncenter" width="600"] Nvidia's[/caption] It will take place on January 8th. Nvidia, of course, does not say anything directly about the new video cards, but the event is called GeForce Special Address, which indicates specifically 3D gaming cards. Nvidia's "super graphics cards" appear to be announced in January. In addition, you can remember that last year at CES the company announced the mobile RTX 40 Laptop and the desktop RTX 4070 Ti. As numerous leaks indicate , at least three models await us: RTX 4070 Super, RTX 4070 Ti Super and RTX 4080 Super. Whether there will be an RTX 4060 Super and RTX 4090 Super (or Ti) later is still unknown.

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But the situation is not yet completely clear The other day, the Remedy studio published the system requirements for the game Alan Wake 2, which turned out to be quite high, and even the minimum ones included DLSS or FSR activation. However, it turned out that the presence of Radeon RX 6600 or GeForce RTX 2060 video cards in the minimum requirements is not just an indicator of some level of performance. The bottom line is that the game may not run at all on older adapters.  [caption id="attachment_73068" align="alignnone" width="780"] GeForce GTX 1080 Ti[/caption] So the GeForce GTX 1080 Ti can be thrown away? One of the project developers stated that the game was created using Mesh Shaders, which are simply not supported by video cards older than the Radeon RX 6000 and GeForce RTX 20. That is, the conditional RX 5700 XT, which is close in performance to the RX 6600 XT, perhaps will not be able to handle the game properly. It's the same story with the GTX 10, and even more so with even older adapters.  Interestingly, even the developers are not sure that the game will not work properly on old video cards, which is strange. However, after some time the specified message was deleted, and the same studio employee wrote that she was persuading her colleagues to make an official statement explaining the situation. 

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The company is developing its own Ascend AI chips US measures to limit the export of advanced chips with artificial intelligence (AI) technologies to China could open up huge opportunities for Huawei for import substitution in the domestic market, as reported by Reuters. While Nvidia has historically been the leading AI chip supplier in China with a market share exceeding 90%, Chinese firms including Huawei are developing their versions of Nvidia's best-selling chips, such as the A100 and H100. Huawei's Ascend AI chips are comparable to Nvidia's in terms of processing power, according to analysts and some artificial intelligence companies such as China's iFlytek. [caption id="attachment_72981" align="aligncenter" width="600"] Nvidia[/caption] US ban on supplies of Nvidia accelerators opens up huge opportunities for Huawei Jiang Yifan, chief market analyst at brokerage Guotai Junan Securities, said another key limiting factor for Chinese firms is the dependence of most projects on Nvidia's chips and software ecosystem, but that could change with U.S. restrictions. “This US move, in my opinion, actually gives Huawei Ascend processors a huge gift,” Jiang said in a post on the social network Weibo. Many cutting-edge AI projects are being built using CUDA, a popular programming architecture pioneered by Nvidia, which in turn has led to the creation of a huge global ecosystem capable of training highly complex AI models such as OpenAI's GPT-4. Huawei's version is called CANN, and analysts say it is much more limited in terms of the artificial intelligence models it can train. Woz Ahmed, a former chip design executive turned consultant, said that for Huawei to win Chinese customers from Nvidia, it needs to replicate the ecosystem that Nvidia has created, including supporting customers in migrating their data and models to Huawei's platform. Woz Ahmed believes that Huawei could take 5 to 10 years to achieve this.