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Google just announced Gemini Robotics 2, extending its physical AI models beyond tabletop manipulation. A robot tying a trash bag sounds routine, but might be a bigger breakthrough than it seems:

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The Rundown AI

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19,341 görüntüleme • 2 ay önce •via X (Twitter)

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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 ↓
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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 ↓

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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
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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

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Boston Dynamics and Google DeepMind announced a partnership to integrate Gemini Robotics AI models with the new electric Atlas humanoid robots. Got to say hi to Carolina Parada before the presentation
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Boston Dynamics and Google DeepMind announced a partnership to integrate Gemini Robotics AI models with the new electric Atlas humanoid robots. Got to say hi to Carolina Parada before the presentation

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Watching someone easily bypass ChatGPT's safety rules on this Unitree G1 robot to fire a BB gun at its operator is definitely cause for alarm. It might be about time we dust off Isaac Asimov's Three Laws of Robotics/physical AI👇
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Watching someone easily bypass ChatGPT's safety rules on this Unitree G1 robot to fire a BB gun at its operator is definitely cause for alarm. It might be about time we dust off Isaac Asimov's Three Laws of Robotics/physical AI👇

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Sundar Pichai on the robotics opportunity: ⦿ He's impressed by recent humanoid progress - so much so that he sometimes has to look closely to tell if a robot video is real or fake. ⦿ Google initially moved too early into the application layer, but now sees the combination of AI and robotics as the “sweet spot.” ⦿ He believes we’re 2–3 years away from a “magical moment” in robotics. ⦿ Google is working on playing a role similar to Android in robotics - one of its internal bets is already focused on supporting robotics manufacturers. ⦿ Gemini robotics models will work very well - how to productize them is still an open question at the company.
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Sundar Pichai on the robotics opportunity: ⦿ He's impressed by recent humanoid progress - so much so that he sometimes has to look closely to tell if a robot video is real or fake. ⦿ Google initially moved too early into the application layer, but now sees the combination of AI and robotics as the “sweet spot.” ⦿ He believes we’re 2–3 years away from a “magical moment” in robotics. ⦿ Google is working on playing a role similar to Android in robotics - one of its internal bets is already focused on supporting robotics manufacturers. ⦿ Gemini robotics models will work very well - how to productize them is still an open question at the company.

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Google just made an incredible AI video breakthrough with its latest diffusion model, Lumiere. 2024 is going to be a massive year for AI video, mark my words. Here's what separates Lumiere from other AI video models:
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Google just made an incredible AI video breakthrough with its latest diffusion model, Lumiere. 2024 is going to be a massive year for AI video, mark my words. Here's what separates Lumiere from other AI video models:

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My conversation with Kanishka Rao, who went from working on particle physics at CERN to driving robotics at Google DeepMind. We get into the Gemini Robotics 2 release, trending training recipes in the industry, physical AGI, world models, and more. 1:00 Intro 1:47 Does AI's pace feel crazy? 4:04 From particle physics PHD to robotics 6:03 Speech recognition's deep learning moment 8:43 Whole-body humanoid control 10:47 The trash-bag tying demo 13:07 The robotics data pyramid 14:13 Transferring skills across robots 16:30 How does Motion Transfer work 16:56 Why a separate reasoning model 19:02 Can distillation work in robotics? 20:02 The ASIMOV safety benchmark 22:47 VLAs vs world models 25:10 The missing tactile sensing piece 27:48 How far to physical AGI? 30:07 Fundamental breakthrough needed? 31:53 World models for evaluation 33:45 Will the model layer commoditize? 35:11 Humanoid as a form factor
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My conversation with Kanishka Rao, who went from working on particle physics at CERN to driving robotics at Google DeepMind. We get into the Gemini Robotics 2 release, trending training recipes in the industry, physical AGI, world models, and more. 1:00 Intro 1:47 Does AI's pace feel crazy? 4:04 From particle physics PHD to robotics 6:03 Speech recognition's deep learning moment 8:43 Whole-body humanoid control 10:47 The trash-bag tying demo 13:07 The robotics data pyramid 14:13 Transferring skills across robots 16:30 How does Motion Transfer work 16:56 Why a separate reasoning model 19:02 Can distillation work in robotics? 20:02 The ASIMOV safety benchmark 22:47 VLAs vs world models 25:10 The missing tactile sensing piece 27:48 How far to physical AGI? 30:07 Fundamental breakthrough needed? 31:53 World models for evaluation 33:45 Will the model layer commoditize? 35:11 Humanoid as a form factor

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🇺🇲The apple-to-apple comparison for iOS26 vs. iOS27 is anything but apples to apples. iOS27 brings a major AI upgrade but with a Google twist… Apple developed those models in collaboration with Google and its Gemini models. People keep pointing out that iOS27 is running Gemini under the hood. Writer: Marie
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🇺🇲The apple-to-apple comparison for iOS26 vs. iOS27 is anything but apples to apples. iOS27 brings a major AI upgrade but with a Google twist… Apple developed those models in collaboration with Google and its Gemini models. People keep pointing out that iOS27 is running Gemini under the hood. Writer: Marie

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1/7 Physical AI has a data problem. More compute alone won’t teach a robot how to move, grasp, react, or recover from mistakes. LLMs had the entire internet to learn from. Robots need something different: huge amounts of real action data. That’s where Axis Robotics gets interesting. $AXIS is building a data engine for Physical AI, turning robot training into something people can contribute to directly through a browser. The loop is straightforward: Generate → Collect → Process → Deploy → Correct → Repeat. What looks simple on the surface could become something much bigger underneath: a scalable way to produce the training data robots need to become genuinely useful in the physical world. The real unlock for Physical AI might not be another bigger model. It might be better data.
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1/7 Physical AI has a data problem. More compute alone won’t teach a robot how to move, grasp, react, or recover from mistakes. LLMs had the entire internet to learn from. Robots need something different: huge amounts of real action data. That’s where Axis Robotics gets interesting. $AXIS is building a data engine for Physical AI, turning robot training into something people can contribute to directly through a browser. The loop is straightforward: Generate → Collect → Process → Deploy → Correct → Repeat. What looks simple on the surface could become something much bigger underneath: a scalable way to produce the training data robots need to become genuinely useful in the physical world. The real unlock for Physical AI might not be another bigger model. It might be better data.

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Gemini Robotics 2 by Google DeepMind uses sim-only post-training on a mixed-data base model to handle automotive kitting. Contact-rich tasks like these have long been considered one of the hardest challenges in Sim2Real. Gemini Robotics 2 shows simulation can work even here. General robot intelligence needs much more data than real-robot collection alone can provide. Simulation has proven to be an effective way to fill that gap.
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Gemini Robotics 2 by Google DeepMind uses sim-only post-training on a mixed-data base model to handle automotive kitting. Contact-rich tasks like these have long been considered one of the hardest challenges in Sim2Real. Gemini Robotics 2 shows simulation can work even here. General robot intelligence needs much more data than real-robot collection alone can provide. Simulation has proven to be an effective way to fill that gap.

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We teamed up with Boston Dynamics to power their robot Spot with Gemini Robotics embodied reasoning models. This means it can better understand its surroundings, identify objects and follow simple commands - like tidying up a room.

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We’ve just stepped into the future. Our AI, CERE, no longer just talks… It walks, moves, and interacts with you in real time! Cere Thanks to our integration with Robot TEMI, CERE is now embodied as a physical being: Meet Robot CERE! And with its GenAI integration, it can now talk to you on the spot. We’ve brought artificial intelligence into the physical world. Unveiled today at the expo — Tomorrow, it might be in your home, your office, or even on the street. Get ready: Technology is no longer just code — Cerebrum Tech #CERE #RobotCERE #ArtificialIntelligence #Robotics #CerebrumTech #AI #FutureTech

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So cool! Can you even tell this is a robot horse? 🤖🐎 DEEP Robotics has built a robot horse, seemingly a special Year of the Horse limited edition based on their M20 Pro. The bionic details on this machine are incredible, especially those lifelike hooves. It looks like a living creature rather than just another quadruped robot. It is amazing to see a quad robot move so smoothly while having such a realistic animal appearance. Source: DEEP Robotics #Robot #Quadruped #Robotics #AI #EmbodiedAI #PhysicalAI #DEEPRobotics #Bionics #TechDesign

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California startup announces breakthrough in general-purpose robotics with π0.5 AI — a vision-language-action model. Everything the robot sees, it sees for the first time. The robot has not been trained to recognize its surroundings. We are getting there! Only a few more years until we finally have household robots. A dream is coming true!

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Announcing Axol: a dual-arm robot designed for teams working with physical AI. Made in America. Axol is for builders who believe robots should work, in the real world, not just staged environments, and that the future of physical AI should be open, not closed. #robotics #automation #ai #hardware

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Google Chief Scientist, Jeff Dean "AI now generates 25% of Google's integrated code" Google has already trained a Gemini model on its internal codebase to help developers this doesn’t cover everything, but it improves AI-assisted coding by integrating code into its parameters
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Google Chief Scientist, Jeff Dean "AI now generates 25% of Google's integrated code" Google has already trained a Gemini model on its internal codebase to help developers this doesn’t cover everything, but it improves AI-assisted coding by integrating code into its parameters

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