Google DeepMind has unveiled two innovative AI models—Gemini Robotics and Gemini Robotics-ER—marking a significant advancement in integrating artificial intelligence into the physical world. Building upon the Gemini 2.0 platform, these models extend beyond digital problem-solving to enable robots to perform real-world tasks. Gemini Robotics combines vision, language, and action capabilities, allowing robots to interpret and execute complex instructions, while Gemini Robotics-ER enhances spatial understanding, facilitating precise interactions with physical environments. These developments aim to bridge the gap between AI's cognitive abilities and practical, embodied applications. ?

Gemini Robotics is designed to be general, interactive, and dexterous. Its generality allows it to adapt to novel situations and handle tasks it wasn't explicitly trained for, demonstrating flexibility across various environments. The model's interactivity enables it to understand and respond to natural language commands, adjusting its actions in real-time based on changes in its surroundings. In terms of dexterity, Gemini Robotics can perform intricate tasks requiring fine motor skills, such as folding origami or packing items, showcasing a level of manipulation previously challenging for robotic systems. ?

Gemini Robotics-ER focuses on embodied reasoning, enhancing a robot's ability to comprehend and navigate physical spaces. It improves upon Gemini 2.0 by offering advanced spatial reasoning, object detection, and trajectory planning. This model can infer appropriate grasping techniques and safe movement paths, enabling robots to interact more naturally and safely with their environment. By integrating perception, planning, and action, Gemini Robotics-ER allows for more autonomous and context-aware robotic behavior. ?

To ensure safety and ethical deployment, DeepMind has implemented a comprehensive approach to AI and robotics development. This includes interfacing Gemini Robotics-ER with low-level safety controllers to prevent collisions and ensure stability. Additionally, DeepMind has introduced the ASIMOV dataset, inspired by Isaac Asimov's Three Laws of Robotics, to evaluate and improve the semantic safety of robotic actions. Collaborations with experts and adherence to a Responsibility and Safety Council further underscore DeepMind's commitment to responsible AI advancement.

?DeepMind is collaborating with companies like Apptronik, Agile Robots, Agility Robotics, Boston Dynamics, and Enchanted Tools to test and refine these models across various robotic platforms. These partnerships aim to develop versatile robots capable of assisting in diverse settings, from industrial environments to everyday human interactions. By integrating advanced AI models with physical embodiments, DeepMind envisions a future where robots are more helpful, adaptable, and aligned with human needs. ?