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Google DeepMind releases new world model with ‘vast space’ to train robots and autonomous systems

August 6, 2025 by David Edwards

Google DeepMind has unveiled Genie 3, the latest version of its generative world model, describing it as a step forward in creating more intelligent and adaptable simulation environments – including those for robotics applications.

Although the company’s announcement focuses heavily on advancements in video prediction and general AI learning, Genie 3 has direct relevance for robotics developers who rely on high-fidelity, physics-aware simulation systems to train and test autonomous systems.

Described as a “world model,” Genie 3 can generate realistic interactive environments directly from a single image prompt and a short textual description, such as “driving down a highway at sunset” or “walking in a rainy city”.

These simulations unfold dynamically in video form and allow limited user interaction, providing an immersive, general-purpose training space for AI agents.

For robotics, this capability is crucial. Training robots in the real world is expensive, time-consuming, and sometimes dangerous. Simulation environments like those enabled by Genie allow developers to expose robots to diverse physical situations at scale, accelerating both development and safety testing.

While DeepMind’s blog post only briefly mentions robotics, the underlying technology appears aligned with broader industry trends, where “embodied AI” systems learn by interacting with virtual worlds before being deployed in real ones.

According to DeepMind, Genie 3 – which Google describes as a “vast space to train agents like robots and autonomous systems” – significantly improves on its predecessors in terms of generality and realism.

The system has been trained on 200,000 hours of Internet videos and is capable of simulating a wide range of environments with consistent physics and camera control – two essential features for robot training.

The platform is also designed to be controllable through reinforcement learning, a technique widely used in robotics. DeepMind previously demonstrated the use of similar world models in simulated robotic motor control tasks, as detailed in a related blog post titled From motor control to embodied intelligence.

With other tech giants – including Nvidia and Meta – also investing in virtual training environments for robotics, Google’s Genie 3 adds competitive pressure and innovation to this fast-moving space.

If Genie evolves into a robust robotics simulation platform, it could become an integral tool for the next generation of autonomous machines.

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Filed Under: Design, News Tagged With: deepmind, embodied ai, generative ai, google genie 3, reinforcement learning, robot training, robotics simulation, simulation environments, virtual robotics, world model ai

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