Playing FULLY AI-Generated CS:GO on a Single RTX 3090!
Entertainment
Introduction
I wasn't planning on making a video today, but I stumbled upon something so exciting that I felt compelled to share it immediately. It's 4:45 AM and I believe this discovery holds significant future implications. What you're about to see may remind you of CS:GO because, in a unique way, this experience is heavily inspired by it.
This technology is being generated locally using just a single NVIDIA RTX 390 TI graphics card. Essentially, a model has been trained on gameplay imagery along with corresponding actions. When I move forward in the game, the model predicts what I should be seeing based on its training. While the performance can be a little unpredictable—sometimes even wonky—it's an early demonstration of what this technology can achieve on consumer-grade hardware.
As I navigate through the game, the visuals are impressive; the car model looks particularly good, and even the gun animation showcases muzzle flash and recoil. These aspects seem to be some of the most consistently generated features due to the repetitive nature of shooting in CS:GO, which offers the model a robust dataset to learn from. However, there are times when things appear to get out of sync, which can happen due to the limited data set the model has been trained on.
I believe the future implications of this technology are vast. Google’s research lab recently demonstrated similar technology using Doom, and now, here I am experiencing it just a month or two later in a game as celebrated as CS:GO.
For those interested in trying this out themselves, I want to share how I set everything up on my machine. I am using Ubuntu 20.04, and my setup includes the NVIDIA 390 TI card.
After navigating to the GitHub repository for this project, I found it relatively simple to follow the installation steps—unlike many repositories that can be tedious to work with.
Once I cloned the repository, I created a new Conda environment and installed the required packages using Python 3.10. Everything installed smoothly with no dependency issues. The default configuration is optimized for CUDA GPU, which means it's perfect for an NVIDIA card like mine.
Upon launching the game, I used a size multiplier flag, which allowed for a larger display than the default setting. After a short loading time, I could start maneuvering my character. The graphics showcased various elements like weapon recoil very effectively, although there were moments where the model would struggle with complex orientations or rapidly moving the camera.
After experimenting with the controls, I was delighted to see the visuals maintaining a dreamlike quality, achieving a unique blend of realism and abstraction. The technology feels like it draws parallels to human cognition, making one consider the possibilities of AI-generated worlds.
As I wrapped up, I observed the performance—around 3GB of video memory usage—but I couldn’t monitor metrics while in-game. This experience is not just a novel demonstration of AI capability but also a glimpse into the realm of digital creation that may redefine gaming as we know it.
Kudos to the developers behind this project for making this accessible. Given that it combines aspects of AI and gaming into a fascinating opportunity, I expect that interest in this technology will grow rapidly.
Keywords
AI, CS:GO, NVIDIA RTX 390 TI, gameplay, machine learning, video game, GitHub repository, CUDA, installation, digital creation.
FAQ
Q: What hardware do I need to run this AI-generated CS:GO?
A: You'll need at least an NVIDIA RTX 390 TI graphics card and a compatible operating system like Ubuntu.
Q: Can I play on platforms other than Windows?
A: Yes, this project is designed to work on Linux-based systems; it has been specifically tested on Ubuntu.
Q: How do I install the AI-generated CS:GO on my machine?
A: The installation involves cloning the GitHub repository, setting up a Conda environment, and installing the required dependencies as listed in the documentation.
Q: Does the performance of the AI change based on hardware?
A: Yes, performance may vary based on the specifications of your hardware, especially GPU capabilities. The model runs best with a CUDA-enabled NVIDIA GPU.
Q: Is the AI-generated gameplay stable?
A: While the technology is impressive, stability can sometimes fluctuate, especially in areas with limited training data. The visuals may appear wonky or abstract in certain situations.