Google DeepMind has introduced its Gemini Robotics project, which features two new models that enable robots to "think" before acting by integrating generative AI capabilities. The Gemini Robotics 1.5 model generates robot actions using visual and text data, while the Gemini Robotics-ER 1.5 model employs simulated reasoning to make decisions about complex tasks, enhancing the versatility of AI-powered robots. This advancement aims to overcome the limitations of traditional robots that require extensive training for specific tasks.

Google DeepMind is advancing robotics by enabling robots to learn and improve autonomously through competitive play, using table tennis as a testbed. By having robots play against each other and incorporating vision language models for coaching, they aim to overcome the limitations of traditional programming and machine learning approaches that require extensive human input. This research seeks to create machines capable of continuous self-improvement and skill acquisition in dynamic environments.

Google DeepMind has introduced a cloud-free on-device VLA model for robotics, enhancing the autonomy and reliability of physical robots. This innovation allows robots to quickly adapt to their environments without relying on cloud processing, marking a significant advancement in generative AI applications in robotics.