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Gemini Robotics ER 2 is our most capable embodied reasoning model designed for physical AI 🤖 Built as a high-level brain for robotics, the model connects directly to the Gemini Live API. It processes continuous video streams to track progress, call tools, search the web, and command an action... show more

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17,581 görüntüleme • 2 gün önce •via X (Twitter)

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Google DeepMind introduced two foundational models for embodied reasoning, enabling robots to comprehend, react, and take action in the physical world: ⦿ Gemini Robotics – built on Gemini 2.0. Integrates vision, language, and action for real-world dexterity, . ⦿ Gemini Robotics-ER – Enhances spatial reasoning for advanced robotic control. They are working with Apptronik to develop the next generation of humanoid robots.

Google DeepMind introduced two foundational models for embodied reasoning, enabling robots to comprehend, react, and take action in the physical world: ⦿ Gemini Robotics – built on Gemini 2.0. Integrates vision, language, and action for real-world dexterity, . ⦿ Gemini Robotics-ER – Enhances spatial reasoning for advanced robotic control. They are working with Apptronik to develop the next generation of humanoid robots.

The Humanoid Hub

73,097 görüntüleme • 1 yıl önce

Most robotics AI models suffer from the "stop-and-think" problem. They take a static picture, pause to reason, execute an action, and repeat. In the real world, that latency causes spills, collisions, and failed tasks. Google DeepMind just launched Gemini Robotics ER 2: an embodied reasoning model that thinks and acts at the speed of the physical world. Here's why this is a step-change for physical AI engineering: Traditional robotics models rely on static snapshots. But knowing *when* a task is done, such as when to stop pouring coffee into a cup or when a trash bag is securely tied, requires continuous temporal awareness. Gemini Robotics ER 2 integrates directly with the bidirectional streaming Gemini Live API to reason about what comes next while simultaneously executing motor actions. What makes Gemini Robotics ER 2 different: 🎯 91.3% accuracy on live video moment-finding (0.96s mean absolute distance) at 4x the execution speed of frontier models 📈 Continuous progress tracking across 5 completion stages (57.4% accuracy) to self-correct mid-task without restarting 🛠️ Native agentic tool orchestration that commands lower-level VLA models, navigation APIs, and Google Search 🤝 Multi-robot collaboration allowing physically diverse machines (like Apptronik's Apollo 2 humanoid and Franka's FR3 Duo arm) to hand off tasks in shared spaces 🛡️ Built-in physical safety that autonomously halts robots when humans enter a workspace and resumes once clear

Most robotics AI models suffer from the "stop-and-think" problem. They take a static picture, pause to reason, execute an action, and repeat. In the real world, that latency causes spills, collisions, and failed tasks. Google DeepMind just launched Gemini Robotics ER 2: an embodied reasoning model that thinks and acts at the speed of the physical world. Here's why this is a step-change for physical AI engineering: Traditional robotics models rely on static snapshots. But knowing when a task is done, such as when to stop pouring coffee into a cup or when a trash bag is securely tied, requires continuous temporal awareness. Gemini Robotics ER 2 integrates directly with the bidirectional streaming Gemini Live API to reason about what comes next while simultaneously executing motor actions. What makes Gemini Robotics ER 2 different: 🎯 91.3% accuracy on live video moment-finding (0.96s mean absolute distance) at 4x the execution speed of frontier models 📈 Continuous progress tracking across 5 completion stages (57.4% accuracy) to self-correct mid-task without restarting 🛠️ Native agentic tool orchestration that commands lower-level VLA models, navigation APIs, and Google Search 🤝 Multi-robot collaboration allowing physically diverse machines (like Apptronik's Apollo 2 humanoid and Franka's FR3 Duo arm) to hand off tasks in shared spaces 🛡️ Built-in physical safety that autonomously halts robots when humans enter a workspace and resumes once clear

Karl Weinmeister

26,179 görüntüleme • 2 gün önce

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 Google DeepMind, 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:

Google AI

338,874 görüntüleme • 2 gün önce

For an industrial robot built for the rigors of factories and power plants, tidying up a living room may seem like a light day at the office for Spot. Yet, this demonstration represents the promise of AI models in robotics. In this case, Google DeepMind's visual-language model (VLM) Gemini Robotics-ER 1.5 was empowering Spot with embodied reasoning. Go behind the scenes and watch the full demo in our blog:

For an industrial robot built for the rigors of factories and power plants, tidying up a living room may seem like a light day at the office for Spot. Yet, this demonstration represents the promise of AI models in robotics. In this case, Google DeepMind's visual-language model (VLM) Gemini Robotics-ER 1.5 was empowering Spot with embodied reasoning. Go behind the scenes and watch the full demo in our blog:

Boston Dynamics

60,551 görüntüleme • 3 ay önce

(1/5) Gemini 3, our most intelligent model, is landing in Google Search today – starting with AI Mode. Excited that this is the first time we’re shipping a new Gemini model in Search on day one! 🚀 In Search, Gemini 3 with generative layouts will make it easy to get a rich understanding of anything on your mind. It has state-of-the-art reasoning, deep multimodal understanding and advanced agentic capabilities. That allows the model to shine when you ask it to explain advanced concepts or ideas – it reasons and can code interactive visuals in real-time. It can tackle your toughest questions like advanced science.

(1/5) Gemini 3, our most intelligent model, is landing in Google Search today – starting with AI Mode. Excited that this is the first time we’re shipping a new Gemini model in Search on day one! 🚀 In Search, Gemini 3 with generative layouts will make it easy to get a rich understanding of anything on your mind. It has state-of-the-art reasoning, deep multimodal understanding and advanced agentic capabilities. That allows the model to shine when you ask it to explain advanced concepts or ideas – it reasons and can code interactive visuals in real-time. It can tackle your toughest questions like advanced science.

Robby Stein

94,877 görüntüleme • 8 ay önce

#AGIBOTAIWeek Day 3: Introducing GO-2: the next-generation foundation model for embodied AI, built to unify reasoning and action. To truly bridge “thinking” and “doing,” embodied AI must solve two challenges at once: • It generate executable action plans through deep spatial reasoning • It deliver stable execution in real-world environments GO-2 tackles both with a comprehensive architecture: Action Chain-of-Thought for action reasoning, and an Asynchronous Dual-System for robust execution. #AGIBOT #AGIBOTAIWeek #Foundation #model #EmbodiedAI Official account tags X: AGIBOT LinkedIn: agibot

#AGIBOTAIWeek Day 3: Introducing GO-2: the next-generation foundation model for embodied AI, built to unify reasoning and action. To truly bridge “thinking” and “doing,” embodied AI must solve two challenges at once: • It generate executable action plans through deep spatial reasoning • It deliver stable execution in real-world environments GO-2 tackles both with a comprehensive architecture: Action Chain-of-Thought for action reasoning, and an Asynchronous Dual-System for robust execution. #AGIBOT #AGIBOTAIWeek #Foundation #model #EmbodiedAI Official account tags X: AGIBOT LinkedIn: agibot

Hasan Toor

36,202 görüntüleme • 3 ay önce

🚀 MiniCPM enters the physical world — enabling robots to understand, remember, and act. We open-source MiniCPM-Robot, our first embodied AI model series, including: 🤖 MiniCPM-RobotManip — a 1.5B general-purpose Vision-Language-Action (VLA) model for robotic manipulation. 🐕 MiniCPM-RobotTrack — a compact model for real-world target tracking. ⚡ PhyAI — a high-performance inference framework built for embodied models. Together, they bring efficient, practical, and open embodied intelligence closer to real-world robots. ⭐ GitHub: 🤗 MiniCPM-RobotManip: 🤗 MiniCPM-RobotTrack:

🚀 MiniCPM enters the physical world — enabling robots to understand, remember, and act. We open-source MiniCPM-Robot, our first embodied AI model series, including: 🤖 MiniCPM-RobotManip — a 1.5B general-purpose Vision-Language-Action (VLA) model for robotic manipulation. 🐕 MiniCPM-RobotTrack — a compact model for real-world target tracking. ⚡ PhyAI — a high-performance inference framework built for embodied models. Together, they bring efficient, practical, and open embodied intelligence closer to real-world robots. ⭐ GitHub: 🤗 MiniCPM-RobotManip: 🤗 MiniCPM-RobotTrack:

OpenBMB

327,126 görüntüleme • 13 gün önce

With this new release, Gemini applies advanced reasoning to make sense of complex, changing information in real-time. 3.1 Pro can utilize advanced reasoning to bridge the gap between complex APIs and user-friendly design. For example, Gemini built a live aerospace dashboard, taking live telemetry from a public API and designing a front end to track the Space Station's orbit.

With this new release, Gemini applies advanced reasoning to make sense of complex, changing information in real-time. 3.1 Pro can utilize advanced reasoning to bridge the gap between complex APIs and user-friendly design. For example, Gemini built a live aerospace dashboard, taking live telemetry from a public API and designing a front end to track the Space Station's orbit.

Google Gemini

106,360 görüntüleme • 5 ay önce

🤖What if a robot could perform a new task just from a natural language command, with zero demonstrations? Our new work, NovaFlow, makes it possible! We use pre-trained video generative model to create a video of the task, then translate it into a plan for real-world robot execution. 1/6 #Robotics #AI #ZeroShot #Manipulation

🤖What if a robot could perform a new task just from a natural language command, with zero demonstrations? Our new work, NovaFlow, makes it possible! We use pre-trained video generative model to create a video of the task, then translate it into a plan for real-world robot execution. 1/6 #Robotics #AI #ZeroShot #Manipulation

Hongyu Li

105,628 görüntüleme • 9 ay önce

Say hi to Odyssey-2 Pro—our most intelligent, interactive, and general-purpose world model yet. Every pixel is generated in real-time, and frame-by-frame the model simulates the world forward. Today for minutes, soon for hours. Available to developers and our API very soon.

Say hi to Odyssey-2 Pro—our most intelligent, interactive, and general-purpose world model yet. Every pixel is generated in real-time, and frame-by-frame the model simulates the world forward. Today for minutes, soon for hours. Available to developers and our API very soon.

Odyssey

285,220 görüntüleme • 7 ay önce

say hello to my little friend 🤖 3D model control (move, rotate, scale, animate) using hand gestures and voice commands, running in real-time in the browser! created with Three.js, Rosebud AI, mediapipe computer vision, and web speech API credit to Quaternius for the robot model 🔗 demo below

say hello to my little friend 🤖 3D model control (move, rotate, scale, animate) using hand gestures and voice commands, running in real-time in the browser! created with Three.js, Rosebud AI, mediapipe computer vision, and web speech API credit to Quaternius for the robot model 🔗 demo below

AA

30,775 görüntüleme • 1 yıl önce

A toolkit for building agents that watch, listen, and understand video. Low latency by design. Open source. Production ready. Vision Agents lets you build real time video AI that works with your models and your edge layer. Supports YOLO, Moondream, Cartesia, Deepgram, ElevenLabs, HeyGen, Gemini, OpenAI, and more. Quick model switching. Easy to use API. Perfect for coaching tools, collaboration apps, avatars, and robotics.

A toolkit for building agents that watch, listen, and understand video. Low latency by design. Open source. Production ready. Vision Agents lets you build real time video AI that works with your models and your edge layer. Supports YOLO, Moondream, Cartesia, Deepgram, ElevenLabs, HeyGen, Gemini, OpenAI, and more. Quick model switching. Easy to use API. Perfect for coaching tools, collaboration apps, avatars, and robotics.

GitHub Projects Community

30,274 görüntüleme • 7 ay önce

Mondo is the most adorable companion robot. It’s safe around kids, can track and follow a person, and capture high-resolution action videos. Mondo is also doing frontier research in humanoid Video-Action models built on a world model backbone: I have no doubt we’ll be hearing this name a lot in consumer robotics. Thanks Mondo Robotics Shuo Yang for the tour.

Mondo is the most adorable companion robot. It’s safe around kids, can track and follow a person, and capture high-resolution action videos. Mondo is also doing frontier research in humanoid Video-Action models built on a world model backbone: I have no doubt we’ll be hearing this name a lot in consumer robotics. Thanks Mondo Robotics Shuo Yang for the tour.

The Humanoid Hub

27,765 görüntüleme • 1 ay önce

Booster Robotics has launched Booster Studio, the first IDE built specifically for embodied AI. > Booster Studio features code editing, high-precision simulation, real-robot debugging, and real-world deployment. > It shortens the path from the first idea to the working hardware, with the build, test, and deployment loop living in a single environment rather than scattered across separate tools. Vibe Robotics 👀

Booster Robotics has launched Booster Studio, the first IDE built specifically for embodied AI. > Booster Studio features code editing, high-precision simulation, real-robot debugging, and real-world deployment. > It shortens the path from the first idea to the working hardware, with the build, test, and deployment loop living in a single environment rather than scattered across separate tools. Vibe Robotics 👀

🚨 AI News | TestingCatalog

21,276 görüntüleme • 1 ay önce

Real-time transcription just got a significant upgrade. Universal-3-Pro is now available for streaming — bringing AssemblyAI's most accurate speech model to live audio for the first time. Developers building voice agents, live captioning tools, and real-time analytics pipelines now get three things they've been asking for: 🔹 Best-in-class word error and entity detection across streaming ASR benchmarks 🔹 Real-time speaker labels — know who said what, as it happens 🔹 Superior entity detection for names, places, orgs, and specialized terminology in real-time 🔹 Code-switching and global language coverage built-in

Real-time transcription just got a significant upgrade. Universal-3-Pro is now available for streaming — bringing AssemblyAI's most accurate speech model to live audio for the first time. Developers building voice agents, live captioning tools, and real-time analytics pipelines now get three things they've been asking for: 🔹 Best-in-class word error and entity detection across streaming ASR benchmarks 🔹 Real-time speaker labels — know who said what, as it happens 🔹 Superior entity detection for names, places, orgs, and specialized terminology in real-time 🔹 Code-switching and global language coverage built-in

AssemblyAI

15,016 görüntüleme • 5 ay önce

A Chinese robotics company unveiled a highly advanced, blue-eyed desktop companion robot designed to bring physical, empathetic AI directly to the workspace. Unlike traditional static smart speakers, this device utilizes eye-mounted cameras and multiple degrees of freedom to enable fluid neck motion, responsive head positioning, and real-time eye tracking for natural, human-like engagement.

A Chinese robotics company unveiled a highly advanced, blue-eyed desktop companion robot designed to bring physical, empathetic AI directly to the workspace. Unlike traditional static smart speakers, this device utilizes eye-mounted cameras and multiple degrees of freedom to enable fluid neck motion, responsive head positioning, and real-time eye tracking for natural, human-like engagement.

Wes Roth

33,414 görüntüleme • 3 ay önce

introducing nano banana 2 lite: our fastest, most cost-effective gemini image model yet built for high-velocity developer pipelines, it delivers text-to-image outputs in 4 seconds at just $0.034 per 1K-resolution image swap it into your workflow today via ai studio and the gemini api

introducing nano banana 2 lite: our fastest, most cost-effective gemini image model yet built for high-velocity developer pipelines, it delivers text-to-image outputs in 4 seconds at just $0.034 per 1K-resolution image swap it into your workflow today via ai studio and the gemini api

Google AI Studio

263,723 görüntüleme • 1 ay önce

The first open-source unified world model for scalable robot manipulation: 5B-parameter open-source unified video-action world model that combines policy and world modeling to generate robot actions, predict future visuals, and evaluate task progress from observations, language, and state. The model is trained on 27.3K hours of heterogeneous data (17.8K real-robot teleop, 6.5K UMI demos, 3K egocentric human videos), enabling it to perform complex manipulation tasks like faucet connecting, bag packing, and toolbox storing as shown in demo videos. The approach supports test-time action refinement and points toward deployment-driven continuous improvement via fleet data. Thanks for sharing, Jianlan Luo (Jianlan Luo)! 📌 Resource links for τ0-WM: • Project page: • GitHub (code): • Hugging Face (model weights): • Paper (PDF): ——- Weekly robotics and AI insights. Subscribe free:

The first open-source unified world model for scalable robot manipulation: 5B-parameter open-source unified video-action world model that combines policy and world modeling to generate robot actions, predict future visuals, and evaluate task progress from observations, language, and state. The model is trained on 27.3K hours of heterogeneous data (17.8K real-robot teleop, 6.5K UMI demos, 3K egocentric human videos), enabling it to perform complex manipulation tasks like faucet connecting, bag packing, and toolbox storing as shown in demo videos. The approach supports test-time action refinement and points toward deployment-driven continuous improvement via fleet data. Thanks for sharing, Jianlan Luo (Jianlan Luo)! 📌 Resource links for τ0-WM: • Project page: • GitHub (code): • Hugging Face (model weights): • Paper (PDF): ——- Weekly robotics and AI insights. Subscribe free:

Ilir Aliu

28,239 görüntüleme • 2 ay önce

You asked for it, we delivered. The full keynote is live. In this keynote, we unveil our enhanced vision to become the World’s Ears for AI & Robotics. We are creating the world’s first decentralized infrastructure for real-world audio intelligence. Check-out our new website: Start training Voice AI now & get rewarded: From noise-level mapping to multilingual voice data and the future of live audio streams, Silencio is building the critical audio data layer that will power foundation models, embodied AI, autonomous vehicles, and robotics.

You asked for it, we delivered. The full keynote is live. In this keynote, we unveil our enhanced vision to become the World’s Ears for AI & Robotics. We are creating the world’s first decentralized infrastructure for real-world audio intelligence. Check-out our new website: Start training Voice AI now & get rewarded: From noise-level mapping to multilingual voice data and the future of live audio streams, Silencio is building the critical audio data layer that will power foundation models, embodied AI, autonomous vehicles, and robotics.

Silencio | Voice Data for AI

176,200 görüntüleme • 10 ay önce

An interactive world model developed by NVIDIA in collaboration with academic partners. - DreamDojo turns egocentric human video data into physical intelligence. - Human data is more scalable than robotics data but lacks action labels. - To solve this, a dedicated action model extracts latent actions by identifying physics and motion deltas between frames. Training - A massive 44k hours of video data are used for pre-training. - Post-training on small-scale robot datasets maps human physics to specific robot embodiments. - An additional distillation stage converts the model into an autoregressive, few-step diffusion model, enabling real-time, action-controllable simulation. Primary Use Cases - Live Teleoperation: Controlling a robot inside a world simulation in real-time. - Model-based Planning: Previewing and curating the best actions for improved success. - Policy Evaluation: Testing robot policies in realistic, out-of-distribution scenarios. Everything that's open-sourced: weights, code, post-training dataset, eval set, and details to reproduce.

An interactive world model developed by NVIDIA in collaboration with academic partners. - DreamDojo turns egocentric human video data into physical intelligence. - Human data is more scalable than robotics data but lacks action labels. - To solve this, a dedicated action model extracts latent actions by identifying physics and motion deltas between frames. Training - A massive 44k hours of video data are used for pre-training. - Post-training on small-scale robot datasets maps human physics to specific robot embodiments. - An additional distillation stage converts the model into an autoregressive, few-step diffusion model, enabling real-time, action-controllable simulation. Primary Use Cases - Live Teleoperation: Controlling a robot inside a world simulation in real-time. - Model-based Planning: Previewing and curating the best actions for improved success. - Policy Evaluation: Testing robot policies in realistic, out-of-distribution scenarios. Everything that's open-sourced: weights, code, post-training dataset, eval set, and details to reproduce.

The Humanoid Hub

11,575 görüntüleme • 5 ay önce