Combining real-time interactivity, task understanding, and full-body action prediction on a humanoid is so, so hard. Here's an example where we bring all of these together in Gemini Robotics 2 🤖🧠

Excited to share Gemini Robotics 2! 6 months ago, I wrapped up my PhD at Stanford to join GDMR full-time. Since then, I’ve learned so much from the team, while working on video understanding for our ER agent and improving the robustness & instruction-following of our action models. Still lots of work ahead, but excited about our progress towards a general robot brain! ✨

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!

For decades, we’ve dreamed of robots that can seamlessly step into our world and lend a hand. Today, we take a major stride toward making that dream a reality: Introducing Gemini Robotics 2 from @GoogleDeepMind, the intelligence layer powering the next generation of truly adaptable robots. This major advance unlocks intelligent whole-body control, advanced dexterity, and even multi-robot collaboration 🤯. Ok but... how does a robot actually "think"? Real-world tasks take time and planning. To manage that complexity, our new embodied reasoning model, Gemini Robotics ER 2, acts as the robot’s high-level brain, enhancing the robot’s capabilities to: — Observe the environment — Reason about the actions needed to complete the task — Coordinate with the vision-language-action model to carry out actions — Track progress until the job is done This setup allows robots to execute complex multi-step workflows, self-correct if a step fails, and adapt to completely novel situations. Learn more about Gemini Robotics ER 2 (and our two other brand new models) here: goo.gle/4x4E8q6

New work led by @riadoshi21 on training a single VLA policy for multi-robot collaboration Excited about all the new kinds of tasks this can unlock, when robots can coordinate and work together!

We’re rolling out an upgrade designed to help robots reason about the physical world. 🤖 Gemini Robotics-ER 1.6 has significantly better visual and spatial understanding in order to plan and complete more useful tasks. Here’s why this is important 🧵

And it's even better in-person! Got to see Memo live a few weeks ago and it's such a great design :) Love the gloves, seems to enable a scalable path to high quality data. Huge congrats to the team, especially @tonyzzhao so impressed by your resilience over the past 2 years!

🚨 We’re thrilled to announce our ICCV 2025 Workshop: MMRAgI – Multi-Modal Reasoning for Agentic Intelligence! 🚨 🌐 Homepage: agent-intelligence.github.io… 📥 Submit: openreview.net/group?id=thec… 🗓️ Submission Deadline (Proceeding Track): June 24th 2025 23:59 AoE 🗓️ Submission Deadline (Non-Proceeding Track): July 24th 2025 23:59 AoE AI Agents are evolving fast — but true intelligence needs reasoning across modalities. Vision, language, audio… it’s time to unify them. From digital and virtual agents to wearable and physical embodiments, agentic intelligence is reshaping how AI interacts with the world. As agents increasingly engage in 3D perception and geo-centric reasoning, bridging modalities with spatial understanding is more critical than ever. 💡 Join us to explore the frontiers of multi-modal agents: • Reasoning with MFM-powered agents • Applications in OS copilots, Scientific Agents, Digital Agents, Virtual Agents, Wearable Agetns and Embodied Agents! • Challenges in alignment, evaluation, efficiency, and robustness 📝 Call for Papers is now OPEN! 📅 Workshop: Oct 19–20 2025 Whether you work on models, methods, or applications — we want to hear from you! #ICCV2025 #MMRAgI #MultimodalAI #AIagents #LLM #MFM #EmbodiedAI #3DVision

How can robots problem solve in novel environments? We combine high-level reasoning with VLMs with low-level controllers to allow test-time problem solving. Paper & code: anniesch.github.io/vlm-pc/