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tagged with all of: multimodal + robotics
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Gemini Robotics 1.5 introduces advanced AI models that enable robots to perceive, plan, and execute complex tasks in the physical world. The models enhance a robot's ability to reason, learn across different embodiments, and interact naturally, marking a significant step towards achieving artificial general intelligence (AGI) in robotics. Developers can access these capabilities through the Gemini API in Google AI Studio.
Google DeepMind has unveiled the Gemini Robotics models, which enhance robots' capabilities to perform complex tasks through natural language understanding and dexterity. These multimodal models allow robots to adapt to various environments and instructions, paving the way for future applications in everyday life and industry. Carolina Parada emphasizes the potential of embodied AI to transform how robots assist with daily tasks.
Gemini models 2.5 Pro and Flash are revolutionizing robotics with advanced coding, reasoning, and multimodal capabilities, enhancing robots' spatial understanding. Developers can utilize these models and the Live API for applications such as semantic scene understanding, spatial reasoning, and interactive robotics, enabling robots to execute complex tasks through voice commands and code generation. The article highlights practical examples and the potential of Gemini's embodied reasoning model in various robotics applications.
Vision Language Models (VLMs) have evolved significantly over the past year, showcasing advancements in any-to-any architectures, reasoning capabilities, and the emergence of multimodal agents. New trends include smaller yet powerful models, innovative alignment techniques, and the introduction of Vision-Language-Action models that enhance robotic interactions. The article highlights key developments and model recommendations in the rapidly growing field of VLMs.