Introduction
Gaming technology has come a long way in the last few decades. With each new generation of GPUs and game consoles, we get more realistic graphics, higher resolutions, better frame rates, and overall more immersive gaming experiences. However, there are still tons of classic and retro games that we remember fondly but can’t enjoy on modern systems the way we may like due to their dated graphics.
This is where new AI upscaling techniques like Nvidia’s RTX Remix come in. RTX Remix uses AI neural networks to upscale and enhance textures and visuals in older games to make them look better on modern systems. But how well does it really work? And can AI truly rebuild and remaster classic game visuals successfully? I decided to take a deeper look.
How Nvidia RTX Remix Works
RTX Remix utilizes Nvidia’s Tensor Core AI technology found in its RTX GPUs. It leverages deep learning neural networks and AI models trained on recognizing and enhancing graphical textures.
Specifically, it uses temporal upsampling to take lower resolution textures and intelligently scale them up to modern higher resolutions. The AI looks at the existing low-res source texture and hallucinates what a higher res version could plausibly look like based on identifying visual patterns.
RTX Remix also does things like add anti-aliasing, ambient occlusion, depth of field, motion blur, and other graphical enhancements to approximate modern rendering techniques.
Overall, the goal is to take older games and rebuild their visuals to look significantly better than the originals when played on a modern PC with RTX graphics.
Testing RTX Remix on Classic Games
To see what RTX Remix is capable of and whether AI upscaling lives up to the hype, I tested it out on some classic games.
Quake II RTX
One of the first games Nvidia showcased RTX Remix on was Quake II. This iconic FPS from 1997 was officially remastered by Nvidia with RTX technology.
The difference when enabled is staggering. The new AI upscaled textures are amazingly high resolution and detailed. The game looks like it could pass for something modern if not for the dated geometry and models. Lighting effects like global illumination are also dramatically improved thanks to RTX ray tracing.
Overall, the visual enhancement feels like a true remaster, beyond what I thought AI upscaling could deliver. Quake II RTX proves the tech can breathe new life into old games.
Doom 3
Doom 3 from 2004 was another game I tested RTX Remix on unofficially. After training the AI model on high-res Doom 3 textures, the upscaled visuals again looked drastically improved from the originals. More detailed textures combined with improved lighting, shadows, and effects make the game look surprisingly modern given its age.
AI upscaling clearly works well on these older 3D games where higher resolution textures can simply be interpolated from existing ones. The neural networks have enough information to generate plausible improvements.
2D Games
I was curious how RTX Remix could improve more traditional 2D games though. So I tried it with classics like Final Fantasy VII, Metal Slug, and more. The AI upscaling helped improve sharpness and add some texture filtering. However, the visual improvements weren’t as dramatic overall.
The more simplistic 2D sprite graphics don’t give the AI model enough data to reconstruct detailed high-res versions. So the enhancements were modest. Upscaling 3D game textures proves far more effective.
Game-Specific Training
I found that training the AI specifically per game, versus a generic model, yielded much better results. With game-specific training, RTX Remix can really dig into that art style and technical details to optimize the upscaling. This custom training and tuning is key to get the most out of AI enhancement.
The Verdict on RTX Remix
After my testing, here is my assessment of what RTX Remix and similar AI upscaling can accomplish:
- It excels at enlarging and enhancing textures for older 3D games. The visual improvements can be dramatic.
- Upscaling more basic 2D graphics sees more limited improvements.
- Per-game training is crucial to maximize quality results. Generic models underdeliver.
- When done well, it can make games look close to modern in terms of textures. But geometry and effects are still dated.
- AI hallucination artifacts can occur, so some glitches are possible.
- Overall, it genuinely revitalizes the visuals of classic 3D games remarkably well.
- But for 2D games, hand-tuned remasters still look best. AI upscaling alone usually isn’t enough.
So in cases like Quake II RTX, AI upscaling clearly delivers an excellent new way to massively improve the graphics of older games to enjoy on modern PCs. But the technique does have some limitations currently. Either way, I’m excited to see how game AI remastering technology like RTX Remix evolves.
The Future of AI Game Upscaling
While the current iteration of RTX Remix has some limits, the technology shows immense potential. AI upscaling is still in its early days.
Here are some ways I expect AI game upscaling to improve and become more capable going forward:
- More robust AI models better able to handle 2D games and more art styles
- Integrating temporal techniques to increase image coherence
- Combining upscaling with geometry improvement
- Upscaling for additional elements like audio and gameplay where applicable
- User controls for customization and tweaking results
- Widespread adoption across game engines and platforms
- One-button solutions requiring no modding or training expertise
As the AI models train on more data and grow more advanced, RTX Remix and platforms like it will only get better. I look forward to a future where classic game libraries can be enhanced with just a few clicks. AI upscaling makes it now possible to preserve and revitalize classic games to be enjoyed by new generations. And that’s an exciting prospect for any gaming enthusiast.
Closing Thoughts
AI-powered upscaling techniques have demonstrated huge potential, but still have some maturing to do. Hand-crafted remasters with custom artwork upgrades can outshine AI results in some cases currently. However, the rapid improvements we’re already seeing indicate sophisticated game upscaling powered by neural networks is here to stay in some capacity. With the right refinements, AI upscaling could become a game-changer for reviving beloved retro libraries with new life. I look forward to following this technology and testing how it evolves for enhancing our favorite classic games in the future.
