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🧵 2. GameNGen trains in two phases: an RL-agent plays the game, and a diffusion model generates frames. The focus is on human-like gameplay data generation.

🧵 3. GameNGen is trained on 128 TPU-v5es and runs at 20FPS on a single TPUv5. Human raters find it hard to distinguish between the AI-generated game and a real game.

🧵 4. The project hints at a future where everything will be represented and simulated by AI systems, marking a significant step towards a universe embedded in AI.

🧵 5. Google's GameNGen showcases the potential for AI to revolutionize game development by learning to play and generate game data for endless possibilities.