At Computex 2024, Nvidia’s Jensen Huang discussed the future of Deep Learning Super Sampling (DLSS). He mentioned that AI will be used to generate textures, objects, and non-playable characters (NPCs) exclusively through DLSS. This approach will improve gaming performance on RTX GPUs by shifting work to the tensor cores, freeing up resources, and increasing frame rates.
Nvidia is working on a new texture compression technology that uses AI neural networks to significantly improve texture quality while maintaining similar video memory demands as modern games. This technology, capable of compressing textures up to a ratio of 16x, will enhance the fidelity of in-game objects, which are essentially textures in 3D space.
Huang also discussed Nvidia’s plans to use DLSS to generate in-game assets from scratch, going beyond the current DLSS 3 frame-generating technology. This innovation will require DLSS to be informed about where assets should be placed in the game world, but the assets themselves will be generated entirely by AI.
Additionally, Huang mentioned the potential for DLSS to generate NPCs in video games. He gave an example of a scenario where four out of six characters are created by AI. This concept ties back to Nvidia ACE, an in-game LLM demonstrated in 2023, designed to bring NPCs to life with unique dialogue and responses, benefiting from user interaction.
Nvidia envisions a future where PC gaming is entirely rendered through AI, replacing traditional 3D graphics rendering. The company sees the generation of in-game assets as a step towards this AI-driven future, where DLSS will play a crucial role in enhancing gaming experiences.
Overall, Nvidia’s plans for DLSS involve utilizing AI to generate textures, objects, and NPCs in video games, improving gaming performance on RTX GPUs. This innovative approach, coupled with new texture compression technology, showcases the company’s commitment to pushing the boundaries of AI technology in the gaming industry.
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