GameNGen is a neural model-based game engine that enables real-time interaction with complex gaming environments, challenging traditional game development methods through AI-driven innovation.
The team trained a reinforcement learning agent playing Doom to create data for a generative AI model, allowing real-time simulation with conditions based on prior gameplay.
GameNGen's development signifies a potential shift in gaming, moving towards AI-generated content where games could be crafted from text descriptions instead of manual coding.
Researchers aim to enhance GameNGen's memory and its capability to manage complex scenarios, envisioning wider applications beyond just Doom for interactive software.
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