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More than six years ago, Nvidia launched its image enhancement and scaling technology – deep learning sampling or DLSS. The latest implementation of DLSS 4, announced at CES earlier this month, promises to be exponentially more advanced than the GeForce 20 Series. But have you ever pondered how we got here? It turns out that a supercomputer was involved in the entire process from the beginning. Bryan Catanzaro’s, Nvidia VP of applied research deep learning, stated this while discussing the technology at the consumer electronics show. DLSS is the result of a six-year process of continuous learning. Catanzaro said that a supercomputer powered by thousands of the newest GPUs at Nvidia runs 24/7, 365. Its sole focus is on improving DLSS. Catanzaro explained that the training process is largely based on analyzing failures. When a DLSS fails, it appears as ghosting, flickering or blurriness within a game. Nvidia attempts to determine the cause of such failures.
Analyzing errors helps Nvidia figure out how to improve their training data. The model is then retrained on the newer data, and gets tested across hundreds of games. Rinse, repeat. “So, that’s the process,” Catanzaro concluded.
Nvidia announced DLSS 4 alongside its new RTX Blackwell GPUs at CES. The graphics specialist claimed that its $549 RTX5070 delivers performance similar to a 4090 when using DLSS 4. This is a claim that many are eager to test.
Nvidia benchmarks show that the RTX is 30 percent faster without DLSS than the 4090. The 5080 is also said to be 15% faster than the 4008, and the 5070 up to 20% faster than the 4007 These are Nvidia benchmark numbers. We will have to wait for real-world, non-biased figures closer to the launch.