How Nvidia's DLSS 3 technology makes your PC games run better

This video was created by Nvidia. All opinions expressed in this video are our own. Nvidia has no say in the content, and just like you, you're watching the video for the first time here on the site.

Every PC gamer knows that a good video card is essential for an optimal gaming experience. You want a good picture and good performance when playing games. No matter how beautiful the game is, if you rush and fumble through the levels, it's over quickly. At least with Kevin and Kos. A good video card prevents this misery. The problem of many gamers is that powerful video cards are not cheap. Especially in a recession, you can only spend your euro once. Nvidia meets these people using DLSS AI technology. It ensures that even though you have a “less powerful” card, you can still enjoy optimal performance on your monitor.

What are the features of DLSS 3 technology in Nvidia RTX video cards?

DLSS stands for Deep Learning Super Sampling and is a form of artificial intelligence that increases the accuracy of your games using neural networks. This all sounds very technical, but honestly, this technology helps the video card deliver performance that it couldn't achieve on its own. DLSS continuously checks the images provided by your graphics card. It then compares the images with a database trained by so-called supercomputers. With this information, DLSS fills in missing details, giving you a sharper, sharper image, with no performance degradation. Isn't that nice?

What are we aiming for: graphical mode or performance mode?

In this video, computer professors Kevin and Kos talk about their experiences with technology like DLSS 3 and Ray Tracing. What are the benefits for them? Are there any disadvantages? Where is technology headed? One thing is for sure, with DLSS 3 you can also play great games on laptops costing around 800 euros. This is pure progress. Check this for example Asus, MSI in HP Laptops once. You will find information about all Nvidia video cards here.