Google DeepMind has identified video games as a significant testing ground for artificial intelligence (AI) research. The company aims to expand AI research that can be applied to the real world by combining AI agents that understand language commands and respond to user actions within complex 3D environments.
Alexandre Mufarech, director of Google DeepMind, presented a session titled "How Google DeepMind Advances AI Research Through Video Games" at the Nexon Developer Conference 2026 (NDC) held on June 17 in Seongnam, South Korea.
Mufarech stated, "Games provide a minimal model for learning more complex dynamics," emphasizing that they are a core foundation of DeepMind's research program. He explained that Google DeepMind has expanded AI reasoning, planning, and adaptability through game-based research, building on the legacy of projects like AlphaGo, AlphaZero, and AlphaStar, which validated AI's planning capabilities.
Currently, DeepMind is focusing on the AI agent SIMA and the world model Genie. SIMA is an embodied AI agent that understands natural language commands from users in a 3D environment. It operates without relying on internal game data or separate application programming interfaces (APIs), recognizing only the pixels on the user's screen and manipulating characters through keyboard and mouse inputs.
Mufarech emphasized that SIMA is not designed to excel at specific games but aims to function as a general agent across various environments. He noted, "The core goal of SIMA research is to generalize to environments it has never encountered before," stating that a complex and rich set of games serves as the foundation for this research.
The world model Genie generates the environment in which the agent operates, simulating the dynamics of the environment to respond to user actions. DeepMind introduced Genie1 in February 2024, showcasing a short interactive environment based on a 2D platform game. Subsequently, Genie2 expanded into a 3D fantasy world. Last year, Genie3 was unveiled, supporting 24 frames per second generation, real-time interactions, and rendering up to 720p.
Genie3 features world consistency and "promptable world events," allowing the model to remember changes made by users and insert new events as prompts even after generation has begun. Mufarech described this as similar to scripted events in video games.
DeepMind is creating a cyclical research structure by combining SIMA and Genie, allowing AI agents to act in generated virtual worlds and using the outcomes to improve the models.
However, Mufarech drew a line against the notion that AI could replace game creators. He stated, "Creating a realistic 3D world does not make it a game; games require story, gameplay, tension, and the creator's vision." He explained that AI could serve as a tool to express visions in new ways rather than replacing creators.
Collaboration with the gaming industry is also emphasized. DeepMind trains AI agents based on the consent of game developers and is currently collaborating with the developers of the large-scale multiplayer online game EVE Online. Mufarech noted that EVE Online's persistent world and player-driven economy provide a suitable environment for researching long-term planning, memory, and multiplayer interactions.
Mufarech concluded, "We must explore what AI research can do for games and confirm through repeated experiments whether we can create new player experiences and game experiences that were impossible without AI."
* This article has been translated by AI.
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