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Video games have emerged as powerful training grounds for AI agents playing video games, accelerating breakthroughs in autonomous behavior.
At the annual Game Developers Conference, Google DeepMind introduced its Scalable Instructable Multiworld Agents (SIMA). These agents mastered nine distinct 3D game worlds, such as No Man’s Sky and Goat Simulator, using natural-language instructions. Crucially, skills learned in several games transferred successfully to unfamiliar game environments.
The research also demonstrates how gaming-trained AI can provide real-world robots with more adaptable intelligence. SIMA’s success echoes advances in virtual-to-physical robotics, such as OpenAI’s Dactyl and Google’s RoboCat. Robots can learn manipulation and navigation skills in simulated environments before being deployed to perform real-world tasks.
Experts believe this progress signals movement toward Artificial General Intelligence (AGI). Multi-game transfer learning enables agents to generalize across unknown challenges: a core component of human-like cognition.
Researchers note that games’ structured, tool-rich environments mirror real-world problem-solving, making them ideal practice arenas.
The implications span robotics, industrial automation, and consumer AI. Companies like NVIDIA and Meta are expanding simulation platforms in robotics, while startups like Figure are building humanoid robots accelerated by video-game-trained models.
Bernard Marr, a tech futurist, predicts AI agents playing video games will trigger major workplace and creativity transformations.
