Core Viewpoint - Google DeepMind has launched the Gemini Robotics On-Device model, which allows robots to operate with a local "offline brain," enhancing their capabilities and reducing reliance on cloud computing [2][4]. Group 1: Model Capabilities - The Gemini Robotics On-Device model can run offline while maintaining strong operational capabilities, allowing robots to follow instructions and perform tasks requiring precision [3][4]. - This model supports deployment on various robotic platforms, from humanoid robots to industrial dual-arm robots, with significantly reduced response latency [4]. - The On-Device version outperforms previous local models in handling out-of-distribution tasks and complex multi-step instructions [8]. Group 2: Adaptability and Training - The model's adaptability is a key strength, enabling it to quickly adjust to new tasks with minimal training data, requiring only 50 to 100 demonstration samples for new tasks [11][12]. - The model has been successfully transferred to different robotic platforms, demonstrating its versatility in executing both general instruction-following tasks and industrial-level operations [13][14]. Group 3: Developer Support - Google has released the Gemini Robotics SDK to facilitate developer access to this technology, allowing for easy evaluation of the model's performance in various tasks and environments [15]. - The SDK includes a MuJoCo physics simulator for testing ideas in a simulated environment before deploying them on real robots, thereby reducing development costs and risks [15][16].