KEENON Robotics launches KOM 2.0 - World's First Service Industry VLA Model Exciting breakthrough in embodied AI! KEENON's KOM 2.0 combines vision, language, and action in one unified model: 🧠 K-Mind System - Multimodal perception and intelligent task planning 🤖 K-Act System - Precise motion execution from real-robot training 🔄 K-Infinity Learning - Trained on hundreds of millions of real-world service interactions Watch how the robot seamlessly makes sandwiches and pours drinks - perceiving, understanding, and acting autonomously in real-time with millisecond-level precision. A game-changer for commercial service robotics! #VLA #AI #Robotics #EmbodiedIntelligence #ServiceAutomation

Extremely exciting research on embodied reasoning models capable of breaking down complex tasks into detailed plans of smaller and manageable steps to achieving the tasks! Cannot wait to see all the amazing applications across industries that embodied AI and robotics can enable and empower! #robotics #embodied #ai #artificialintelligence #machinelearning #ml #dl #deeplearning #reasoning #tasks #plan #amazing #applications #industry #research #cool #exciting

I used to file humanoid robots under 'interesting, but maybe in 2040.' Then I saw Figure 03. My timeline just collapsed. This isn't another clunky robot. It's dexterous. It has a sense of touch. You can talk to it, and it understands and acts. The hardware is impressive, but that’s not the revolution. The real game-changer is its AI brain, 'Helix,' which learns by watching human video. This is a fundamental shift. We're moving from programmed machines to learning systems in a physical body. No, they won't be taking over offices next year. But for leaders, ignoring this is a strategic error. The question is no longer *if* they will integrate into our workforce, but *how* we will prepare our operations for them. My take: The first applications will be in logistics and facilities, handling the repetitive tasks that burn out our human teams. As a leader, what's one mundane, physical task in your operation you'd delegate to a robot first? #FutureOfWork #Robotics #AIInnovation I'm tracking these developments closely. Get my weekly AI insights here: https://lnkd.in/eTkwR66W

🧠 𝗧𝗵𝗲 𝗙𝘂𝘁𝘂𝗿𝗲 𝗶𝘀 𝗡𝗼𝘄: 𝗙𝗹𝗶𝗽𝗽𝗶𝗻𝗴 𝘁𝗵𝗲 𝗦𝗰𝗿𝗶𝗽𝘁 𝗼𝗻 𝗥𝗼𝗯𝗼𝘁𝗶𝗰𝘀 🤖 We just witnessed a moment that will be studied for years: the FIRST full-size humanoid robot to execute a ground flip powered by deep reinforcement learning (DRL)! 🤯 This isn't just a party trick; it's a monumental leap in dynamic, real-world robotic dexterity. 📊 𝗣𝗿𝗲𝗰𝗶𝘀𝗶𝗼𝗻 & 𝗣𝗼𝘄𝗲𝗿: 𝗕𝘆 𝘁𝗵𝗲 𝗡𝘂𝗺𝗯𝗲𝗿𝘀 📈 This achievement wasn't a fluke; it was engineered precision. The robot, weighing in at over 65 kg, used 38 separate actuators to manage the force and balance for the rotation. ✨ The Reinforcement Learning Model: Trained in simulation for the equivalent of over 5,000 hours (that's over 208 full days!), the DRL algorithm learned to execute the perfect parabolic arc and landing compensation entirely on its own. 💡 𝗪𝗵𝘆 𝗧𝗵𝗶𝘀 𝗠𝗮𝘁𝘁𝗲𝗿𝘀: 𝗔 𝗦𝗵𝗮𝗿𝗽 𝗜𝗻𝘀𝗶𝗴𝗵𝘁 🚀 For decades, getting a bipedal robot to simply walk was a monumental challenge. A flip, however, requires the robot to embrace instability and control unpredictable momentum—the very definition of real-world interaction. This breakthrough unlocks a future where humanoids can navigate complex, uneven terrain, recover from stumbles, and eventually, perform intricate tasks in disaster relief or manufacturing that were previously impossible. Think of it: a robot that instinctively knows how to correct a near-fall in an industrial setting, saving millions in potential damage. 🎥 𝗦𝗲𝗲 𝘁𝗵𝗲 𝗨𝗻𝗯𝗲𝗹𝗶𝗲𝘃𝗮𝗯𝗹𝗲 𝗠𝗼𝘃𝗲 🔗 Click to see the footage. Prepare to be amazed by the fluidity and control. This is the power of DRL realized in physical form. Is this level of autonomous, athletic capability in robots inspiring, or does it spark a deeper conversation about the roles we reserve for human ingenuity? #Robotics #AI #DeepReinforcementLearning #HumanoidRobot #FutureOfWork #TechInnovation

🤖 𝐓𝐡𝐞 𝐅𝐮𝐭𝐮𝐫𝐞 𝐨𝐟 𝐑𝐨𝐛𝐨𝐭𝐢𝐜𝐬 𝐉𝐮𝐬𝐭 𝐆𝐨𝐭 𝐚 𝐁𝐫𝐚𝐢𝐧. Meet 𝑯𝒆𝒍𝒊𝒙 — a generalist 𝑽𝒊𝒔𝒊𝒐𝒏-𝑳𝒂𝒏𝒈𝒖𝒂𝒈𝒆-𝑨𝒄𝒕𝒊𝒐𝒏 (𝑽𝑳𝑨) 𝒎𝒐𝒅𝒆𝒍 designed to think, see, and act like a human. Developed by Figure AI, Helix unifies perception, language understanding, and learned control — finally bridging the gap between AI reasoning and real-world robotics. 💡 𝑾𝒉𝒚 𝒊𝒕 𝒎𝒂𝒕𝒕𝒆𝒓𝒔: 1. Robots can now understand instructions, not just follow them. 2. They can see and adapt to their environment in real time. 3. They can learn new tasks without retraining. This is more than a robotics upgrade — it’s a step toward general-purpose intelligence that moves, thinks, and collaborates. 🚀 Watch how Helix is changing the future of robotics. #AI #Robotics #Helix #ArtificialIntelligence #VisionLanguageAction #FutureTech #Automation #MachineLearning #FigureAI 📖 Read the full report here: https://vist.ly/4aztk

🚀 Is this how we finally get robots to master the real world? One of the biggest hurdles in robotics has always been the "sim-to-real" gap. Training a robot in the real world is incredibly slow, expensive, and risky (imagine a robot learning to use your fine china!). Virtual simulations are safer, but often too simple or unrealistic for a robot to transfer its learned skills to our messy, unpredictable homes. That's why I was so fascinated by this new tool from MIT CSAIL, called Steerable Scene Generation. It's a genuine game-changer. In a nutshell, it uses a powerful combination of generative AI (a steered diffusion model) and the same strategic search technique that powered AlphaGo (Monte Carlo Tree Search) to build incredibly realistic and physically accurate 3D worlds. But here's the magic ✨: The AI doesn't just create random scenes. It "steers" the creation process to build logical, everyday environments. It knows that forks and plates go on a table, not through it. This allows a robot to practice complex tasks, like setting a table or stacking dishes, endlessly in a safe, scalable virtual world. This is more than just a cool simulation. It's a potential solution to the data bottleneck that has held back the development of general-purpose robots. By making training faster, cheaper, and far more realistic, we're taking a massive leap toward robots that can finally navigate and interact with our world safely and effectively. To me, this feels like a foundational piece of the puzzle falling into place. We're not just building robots; we're building intelligent, dynamic worlds to teach them. What's the first task you'd want a household robot to learn? I'd love to hear your thoughts! Credits: MIT CSAIL Nicholas Ezra Pfaff #AI #Robotics #Innovation #MIT #CSAIL #MachineLearning #GenerativeAI #FutureOfTech #ArtificialIntelligence

Google DeepMind has unveiled Gemini Robotics, a next-generation AI model capable of teaching robots to perform complex physical tasks with logic, adaptability, and perception. Gemini combines advanced language reasoning with real-world data, allowing robots to understand context, interact with objects, and make intelligent decisions in dynamic environments. From healthcare to logistics, this innovation could transform how robots operate, turning static automation into adaptive, human-like intelligence. The line between digital and physical intelligence is rapidly disappearing, and Gemini is leading the charge. Follow MediaBlizz for daily insights on AI advancements, robotics, and the future of smart automation. #Mediablizz #DeepMind #GeminiRobotics #AI #ArtificialIntelligence #MachineLearning #Innovation #Automation #TechNews #RoboticsResearch

Google DeepMind’s new AI enables robots to share skills and solve complex jobs, from laundry to recycling, by learning online and reasoning together.