Counter-Strike's Dust II runs purely within a neural network on an RTX 3090 — performance is disappointing at only 10 FPS

In a move showing yet further progress in the field of generative AI being capable of simulating existing (copyrighted) games, the "DIAMOND" Diffusion for World Modeling model has now been showcased simulating Counter-Strike: Global Offensive, trained and played off a single RTX 3090 (at 10 FPS). One of the people working on the project, Eloi Alonso, posted footage of this CS:GO "world model" being run in a thread on Twitter, including plenty of disclosure on the involved glitches, of which there are many.

Ever wanted to play Counter-Strike in a neural network?These videos show people playing (with keyboard & mouse) in 💎 DIAMOND's diffusion world model, trained to simulate the game Counter-Strike: Global Offensive.💻 Download and play it yourself → https://t.co/vLmGsPlaJp🧵 pic.twitter.com/8MsXbOppQKOctober 11, 2024

While a responsible enthusiast should be critical of the implications posed by AI technology implemented in this way, it's undoubtedly an impressive technical achievement on the part of Eloi Alonso and the rest of the people who worked on the "DIAMOND" diffusion model to effectively "port" CS:GO to AI by training a single GPU with enough Dust II Deathmatch footage to "teach" the diffusion model the game. The glitches are all fascinating in their way, too, showing us some of the logistical shortcomings of generative AI technology that is still ultimately guessing correct player/game behavior, not running it within a game engine.

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