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Google DeepMind releases Gemini Robotics 2, which combines several different AI models into a single system to control a range of robots, including humanoids

The latest version of Google DeepMind's AI model includes a significant jump into “physical AGI.”  But plopping AI into the real world comes with risks.

Wired Will Knight

Context & Ripple Effects

Google DeepMind’s robotics work has moved from separate Gemini 2.0-based Robotics and Robotics-ER models toward progressively more capable task execution. The intermediate 1.5 release added multi-step robot task capabilities, while ER 1.6 focused on stronger spatial and physical reasoning.

The new unified system also follows efforts to make the stack deployable across hardware: Google released an on-device robotics model and SDK, and Boston Dynamics began integrating Gemini Robotics into Atlas. Combining models into one controller makes that progression consequential for humanoid and other robot platforms.

First-order effects

  • Robot builders and deployment teams gain a single Gemini Robotics 2 system intended to control a range of machines, rather than assembling separate model capabilities themselves.
  • The shift puts more emphasis on validating real-world behavior and operational safeguards, because the system is being positioned for physical environments where errors have direct consequences.

Second-order effects

  • Robot manufacturers and systems integrators using Gemini-based stacks can evaluate a more unified software layer across different form factors; the earlier Atlas integration is a concrete indication of where such model advances can be tested.
  • Competing robotics-AI providers face pressure to match not only task performance but also the integration path from perception and reasoning to robot control, increasing the value of hardware-software partnerships.

Third-order effects

  • If unified foundation-model controllers prove reusable across robot types, robotics competition could shift toward deployment data, safety validation, and integration expertise rather than narrowly tailored control models alone.
  • As AI systems take on broader physical agency, operational governance is likely to become a product requirement alongside capability claims, especially for deployments beyond controlled demonstrations.

The trend: Gemini Robotics 2 is part of the broader physical-AI push to turn general-purpose models into reusable control layers for real-world machines.

Discussion

  • @googledeepmind @googledeepmind on x
    To be genuinely useful in our homes and workplaces, robots need finesse. …
  • @officiallogank Logan Kilpatrick on x
    Introducing Gemini Robotics ER 2, our latest robotics embodied reasoning model based on Gemini. So much progress from our last ER model (and baseline Gemini 3.6 Flash). Very excited to see more robots do useful things with this model! [image]
  • @dynamicwebpaige @dynamicwebpaige on x
    🤖✨ Gemini Robotics ER 2 gives you the spatial and reasoning capabilities of massive frontier models (like Opus 5 and GPT 5.6 Sol), but with the sub-second latency and cost efficiency required to actually run continuous video feeds on physical robots in the real world. So excited …
  • @apptronik @apptronik on x
    Huge congrats to the @GoogleDeepMind team on launching Gemini Robotics 2! Watching Apollo 2 use advanced reasoning to navigate whole-body tasks and fine-tuned dexterity is a massive leap forward. See it for yourself! 👇 #apptronik #robotics #AI #humanoids
  • @newsfromgoogle @newsfromgoogle on x
    Meet Gemini Robotics 2: our next-generation physical AI from @GoogleDeepMind that gives robots the ability to think, reason, act, and even work together.
  • @googleai @googleai on x
    For decades, we've dreamed of robots that can seamlessly step into our world and lend a hand. …
  • @thehumanoidhub @thehumanoidhub on x
    Google DeepMind just introduced Gemini Robotics 2. It's a single VLA that unlocks physical dexterity across different end effectors, hands or grippers, from one model checkpoint. Apptronik's Apollo 2 humanoid, with the 22-DoF SharpaWave hand, ties knots and seals a ziplock bag [v…
  • @googledeepmind @googledeepmind on x
    Three new models power this breakthrough: 1️⃣ Gemini Robotics 2: A vision-language-action model controlling humanoids from feet to fingertips 2️⃣ Gemini Robotics ER 2: Capable of real-world video understanding and complex, multi-step planning 3️⃣ On-Device 2: Runs locally and ada…
  • @googledeepmind @googledeepmind on x
    Gemini Robotics 2 moves physical AI beyond tabletop tasks, enabling intelligent whole-body control for humanoids. Watch @Apptronik's Apollo 2 process a single prompt to reach, bend, and pick up a watering can ↓ [video]
  • @googledeepmind @googledeepmind on x
    One brain. For any robot. 🤖 We're launching Gemini Robotics 2: our next-generation physical AI bringing full body intelligence to humanoids, advanced dexterity, multi-robot teamwork and more.
  • @google @google on x
    Introducing Gemini Robotics 2: the next era of truly adaptable robots from @GoogleDeepMind 🤖 Powered by three new models, it brings whole-body control, fine dexterity, and teamwork to complex tasks — making robots more helpful in the real world. [video]
  • Karl Weinmeister Karl Weinmeister on linkedin
    Most robotics AI models suffer from the “stop-and-think” problem.  —  They take a static picture, pause to reason, execute an action, and repeat. …
  • Jérémy Plassmann Jérémy Plassmann on linkedin
    Very excited about our latest Gemini Robotics 2 release!  So proud of this team and what we've built together!
  • @demishassabis Demis Hassabis on x
    Gemini Robotics 2 is here, with our new suite of models, robots can now reason through every movement to manage tasks that weren't possible before, like tying delicate knots - and even team up to solve complex workflows. Huge congrats to the robotics team on this great milestone!
  • r/Bard r on reddit
    Introducing Gemini Robotics ER 2