Google's New AI Robots Learn to Think and Adapt Like Humans
DeepMind's Gemini Robotics models enable robots to plan multi-step tasks, search the web, and teach themselves new skills.
Google DeepMind has unveiled two groundbreaking AI models—Gemini Robotics 1.5 and Gemini Robotics-ER 1.5—that significantly enhance robots' ability to reason, plan, and adapt autonomously. These models represent a shift from single-task robots to those capable of multi-step problem-solving, marking a major milestone toward Artificial General Intelligence (AGI) in the physical world.
Key Advancements
- Generalization: Robots can now apply knowledge to new scenarios, overcoming a longstanding hurdle in robotics. For example, they can sort laundry by color, pack suitcases based on weather forecasts, or check local recycling rules—tasks requiring contextual awareness.
- Online Integration: The robots can access Google Search for real-time information, such as recycling guidelines in San Francisco, and execute tasks accordingly.
- Collaborative Learning: Skills learned by one robot can be transferred to others, accelerating adaptability.
Performance and Limitations
In tests, the robots demonstrated a 20-40% success rate in executing complex tasks—a notable improvement, though far from perfect. For instance:
- They visually identified objects, cross-referenced them with online recycling rules, and disposed of them correctly.
- They employed chain-of-thought reasoning, breaking tasks into logical steps (e.g., "whites go in one bin, colors in another").
Technical Breakdown
The two models work in tandem:
- Gemini Robotics-ER 1.5: Acts as the "brain," planning tasks and retrieving information via search (e.g., weather forecasts). It’s a Vision-Language Model (VLM).
- Gemini Robotics 1.5: Handles physical execution, converting instructions into movements. It’s a Vision-Language-Action (VLA) model.
Google CEO Sundar Pichai touted the models as "the next big step toward general-purpose robots."
Industry Context
Google’s approach contrasts with competitors:
- Tesla: Focused on mass-producing factory robots.
- Boston Dynamics: Prioritizes physical agility (e.g., backflipping Atlas).
Meanwhile, China leads in industrial robotics, with 1.8 million operational robots in 2023 (International Federation of Robotics).
Availability
- Gemini Robotics-ER 1.5: Now accessible via Gemini API.
- Gemini Robotics 1.5: Limited to select partners.
This development underscores the accelerating global race toward intelligent, adaptive robotics.
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About the Author

Dr. Emily Wang
AI Product Strategy Expert
Former Google AI Product Manager with 10 years of experience in AI product development and strategy formulation. Led multiple successful AI products from 0 to 1 development process, now provides product strategy consulting for AI startups while writing AI product analysis articles for various tech media outlets.