Pretty human-like hand Beijing-based SynapX will unveil its tendon-driven... OctoH-Hand at WRC. Human-scale in size, the hand uses a hybrid architecture combining fully tendon-driven actuation with direct-drive motors in the forearm. It integrates 28 independently controllable actuators and 23 active DoF, along with tactile sensors embedded in the palm. Interestingly…SynapX is building more than just a dexterous hand. It has also developed a World model(SYNWorld), and a data collection system(OctoSense), creating a loop from data collection to world understanding and policy generation, and finally to real-world execution and feedback. Another physical AI bridge for humanoid robots.show more

.Xynova is one of the top rising players in... China’s dexterous hand and humanoid robot components space, based in Hangzhou • They develop not only the hands but also all core components (linear actuators, motors, etc) and algorithms fully in-house • They use a hybrid drive system, combining tendon-driven and direct-drive methods • One of the most exciting features is wrist control and finger abduction/adduction, delivering much more natural hand and arm dexterity • They prevent the hand from overheating by placing one of the actuators in the arm (below the palm) • Hands are equipped with tactile sensors and lidars, with 23 DoF (human hands have ~27 DoF) The overall design is deeply inspired by real human hand and arm muscle movements, impressive biomimicry approach The Humanoid Hub and I interviewed their tech lead so stay tuned for more technical details!show more

Elon Musk has repeatedly highlighted the hand (and forearm)... as one of the toughest engineering challenges for Tesla’s Optimus Robot. A new Patent (for presumably Optimus 3) shows Tesla is using human anatomy to recreate a tendon-driven robotic hand and forearm assembly that closely mimics a human system. Basically, Tesla is replacing human muscles with actuators and tendons with cables to replicate human dexterity. The Tesla Engineering team is on another level. Optimus Gen 3 reveal is going to be incredible.show more

Super excited to visit WUJI TECH who's pushing the... frontier with their advanced dexterous robotic hand Most traditional robotic hands still rely on tendons/cables, but Wuji Hand uses direct-drive actuators embedded right in the fingers with worm gears. This solves the usual tendon problems by delivering smoother, more precise, and reliable motion with way less sim-to-real gap It also has high dexterity with 20 active degrees of freedom and the weight/size feel almost exactly like an adult human hand Got to test the newly launched Wuji Hand 2 today and was super fascinated! (watch how I handle the hand in the first video😂)show more

Tactile interaction in the wild can unlock fine-grained manipulation!... 🌿🤖✋ We built a portable handheld tactile gripper that enables large-scale visuo-tactile data collection in real-world settings. By pretraining on this data, we bridge vision and touch—allowing robots to: ✅ Perform robust in-hand reorientation ✅ Control contact and force with precision 🔗 Project page: (1/6)show more

TESLA’S NEXT-GEN OPTIMUS V3 HAND IS GETTING CLOSE TO... HUMAN-LEVEL Tesla engineers just shared new details on the Optimus V3 hand — and the progress is striking. They’re now saying that as they move into Gen-3 and mass production, the hand is getting very close to human functionality and form factor. One engineer described it clearly: “It won’t even look like a robot. It will look like a human in a superhero suit. It will be something revolutionary.” This level of dexterity and human-like design is a critical milestone. The hand is one of the hardest parts of building a truly useful humanoid robot — and Tesla is iterating extremely fast.show more

Pi Ventures Joins Hack VC To Back AI Robotics... Startup On Base Axis Robotics (Axis Robotics) has raised a $12 million seed round led by Hack VC, with participation from Pi Network (Pi Network) Ventures, Nomad Capital, 10K Ventures, and other angel investors. The company is building a data engine for Physical AI that combines simulation, real world data capture, and human feedback to generate scalable robotics datasets. Axis said the funding will accelerate development of its global human in the loop data engine. Base (Base APAC) congratulated the team, calling Axis one of the leading scalable Physical AI and robotics platforms building on the network.show more

New robot hands just dropped! But it seems to... be missing a couple fingers. Tacta Systems Tacta Systems is a Palo Alto robotics startup that just came out of stealth, and raised with $75M and a dexterity platform, TactaBot, aimed at high-value manufacturing. TactaBot has three parts: - the Tacta Hand -> a human-scale robotic hand with 15 independently actuated joints, proprietary "Fluidic Tendon" actuation, pitched as reliable for millions of factory cycles. - the Tacta Sensor -> a tiny tactile sensor reading force from 250 Pa to 700,000 Pa, sampling at 400 Hz, resolving temperature to 0.1 °C. - Skill Capture -> a data system built around the Tacta Glove. It contains the same sensor embedded in a glove that factory workers wear. Sounds similar to what mimic is doing! Except with 3 fingers instead of 5. Tacta's vision sees 3 fingers as more than enough to complete all tasks, and less complex to simulate than 5. My opinion: Tacta is very strong at semiconductor/MEMS, their moat lies in their ability to manufacture their touch sensor as large as a grain of sand, not the hand or the model. One caveat though: there is no detail nor explanation of how the 5 finger data acquisition glove maps to the 3 finger hand -> I would love to learn more about it! This is where the interesting part of the tech is imho. If this does not work, then nothing does. Still, I have to admit it looks very cool, slick, and minimal, I love it:show more

TESLA HALTED MODEL S AND MODEL X PRODUCTION TO... BUILD AN ARMY OF OPTIMUS ROBOTS The Fremont assembly line was torn down in 46 days. In its place, Tesla is building a line for humanoid production, aiming for a million units a year A humanoid robot is a body shaped like a human. Physical AI is the intelligence that controls that body Walking and making coffee is often just imitation learning from a scripted routine. But once the environment shifts, the learned trick stops working Language models had the entire internet to train on. Robotics has nothing close to that scale of data, which is why one giant brain hasn't worked for anyone yet The industry is moving toward modularity instead - separate models for vision, movement, and planning, each improved on its own The real question is no longer whether a robot can move impressively. It's whether it can pull its sensors into one picture of the world and adapt to whatever wasn't scripted for itshow more

Physical AI is taking humanoid robots beyond scripts and... into the real world. 🌍 Join Spencer Huang at #NVIDIAGTC Taipei for a technical look at end-to-end workflows for building general-purpose humanoid robots, from data collection all the way to deployment on hardware. 📅Thursday, June 4, 2026 | 10:30 AM CST 📍TICC Add to calendar:show more

In the future, it might just be humanoid robots... doing the refueling!🤖⛽️ Sinopec plans to introduce humanoid robot workers across its gas stations. They will handle tasks like fueling, picking up items, restocking, and inspections,working alongside human staff, especially during peak holiday periods in China to ease service pressure. With more than 30,000 gas stations across the country (most of them equipped with convenience stores), this implies a deployment of at least 30,000 humanoid robots. The robot is a wheeled humanoid developed by Beijing-based company FIVEAGES.show more

From seeing → to understanding → to following →... now to finding. In the last update, our robot learned how to recognize and follow people SR Agentic now evolves from human-following → to goal-driven object search. Give it a task like: → “find the white bottle on the table ” It will: • break down the instruction via LLM task planning • scan the environment in real-time • localize the object in 3D space • navigate and approach autonomously Step by step, capability by capability — from perception → to tracking → to task execution in the physical world. This is how real-world agentic robotics is builtshow more

🦿Xpeng showed a humanoid robot called IRON whose movement... looked so human that the team literally cut it open on stage to prove it is a machine. IRON uses a bionic body with a flexible spine, synthetic muscles, and soft skin so joints and torso can twist smoothly like a person. The system has 82 degrees of freedom in total with 22 in each hand for fine finger control. Compute runs on 3 custom AI chips rated at 2,250 TOPS (Tera Operations Per Second), which is far above typical laptop neural accelerators, so it can handle vision and motion planning on the robot. The AI stack focuses on turning camera input directly into body movement without routing through text, which reduces lag and makes the gait look natural. Xpeng staged the cut-open demo at AI Day in Guangzhou this week, addressing rumors that a performer was inside by exposing internal actuators, wiring, and cooling. Company materials also mention a large physical-world model and a multi-brain control setup for dialogue, perception, and locomotion, hinting at a path from stage demos to service work. Production is targeted for 2026, so near-term tasks will be limited, but the hardware shows a serious step toward human-scale manipulation.show more

Figure is aiming to develop the world’s largest and... most diverse real-world humanoid pretraining dataset. For this purpose, they’re partnering with Brookfield, a global asset manager overseeing $1 trillion in assets, including 100,000 residential units, 500M square feet of commercial office space, and 160M square feet of logistics space. The data collected from this collaboration will be used to train Figure’s Helix AI model, enabling humanoids to perform tasks autonomously in real-world environments designed for humans. In addition to data collection, the partnership will explore support for next-generation GPU data centers, real estate for robotic training environments, and commercial use cases across Brookfield’s global footprint.show more

🚀 My New Book is Here: Data Strategy (3rd... Edition) 🚀 I’m thrilled to share the release of my latest bestselling book, Data Strategy: How to Use Data and Artificial Intelligence to Transform Your Business. Every business today needs data to survive - but simply having data is not enough. What matters is how you use it. A well-designed data strategy is the key to unlocking value, driving insights, and giving your organisation the competitive edge it needs to thrive in the digital economy. From small organisations to global enterprises, I’ve seen first-hand how a data-driven approach can transform operations, improve decision-making, and unlock entirely new opportunities. That’s why I’ve poured my experience into this book — to help leaders and teams build strategies that don’t just talk about data, but actually deliver measurable impact. 🔍 In this third edition, I’ve expanded the book to reflect the latest developments in data and AI, including: ✅ Generative AI and its role in shaping business innovation. ✅ Synthetic data and how it can accelerate AI adoption. ✅ The potential of quantum computing and what it means for the future of data. ✅ Expanded guidance on cybersecurity, regulations, and ethics in a data-driven world. This isn’t just a theoretical framework - it’s a practical guide to collecting, managing, and using data effectively in order to drive growth, innovation, and long-term success. Whether you’re leading a start-up or a multinational, Data Strategy will equip you with the tools you need to stay ahead in a rapidly evolving landscape. 📖 Pre-order your copy today: 👉 Amazon - 👉 Kogan Page - I can’t wait to hear how this book helps you craft your own data-driven strategy and transform your business for the future.show more

I am posting after a Long Time on Twitter,... but its to announce a big change. I have started and we are Collecting Egocentric Data at Scale from India, Covering 300 + Commercial Locations 1500 + Households This is the network and base we have built in just past 2 months, as the Robotics companies, VLMs and World Models increase their requirements on Real World Data collection, Human Loops will be keep scaling out capacity. We are on track to collect 1M Hours of Egocentric in the coming 6 months for our clients exclusively. We are maintaining 95% Quality standards across industrial data and running a End - End Operational Management complying all Indian Laws and compensating our partners/operators. (From Environment sourcing, to hardware, Legal contracts, deployment, training, collection, processing) Check our Samples: - Commercial Videos -- Household Videos --- Multimodel ---- Egocentric + Live Audio Narration Links : On the Journey to become #1 India Physical AI Data Partner. We are also building our capacity as annotation and labelling partner for data companies to become end-end partner for companies. A big change from the world of crypto and web3 but physical AI and data space is where i want to build my next venture #Egocentric #EgocentricIndia #PhysicalAI #Robotics #India #AIdata #data #Multimodeldata #worldmodels #VLMs #Humanloops #Egocentridata #Multimodeldatashow more

There's one detail about this robot that nobody mentions... until you touch it This is Moya from DroidUp Moya runs on the Walker 3 skeleton with tendon driven lattice muscles, hitting 92% walking accuracy versus real human movement. Watch the gait, it barely stutters Now the part that gets skipped. Active thermal regulation keeps its skin at 32 to 36°C, the same range as an actual person. Built for healthcare and hospitality, where a cold robotic hand gives everything away in one handshakeshow more

The 2nd World Humanoid Robot Games opened today in... Beijing, and a world record has already been set. The Lightning robot, developed by smartphone maker Honor, ran 100 meters in 9.32 seconds, beating Usain Bolt's human record of 9.58 seconds. A total of 2,056 humanoid robots from 666 teams are participating in the games, competing in various real-world tasks and athletic events, such as house cleaning, firefighting, soccer, running, boxing, and more. Comment from me: Artificial intelligence is the foundation of future technological and environmental development. Today, we can see that two global centers have emerged in terms of the number of data centers, AI infrastructure, and the integration of AI into industrial and humanoid robotics: the United States, along with Japan and South Korea, and China. Russia is not an independent center and is lagging far behind the leaders, having squandered all its potential in the war. Europe is currently following the US lead, but it is already developing its own AI structures and semiconductor strategy, changing regulations, and investing hundreds of billions in technological autonomy, and it could become the third global center.show more

The date is set. Introducing JioBlackRock Flexi Cap Fund... — India’s first active equity fund powered by Systematic Active Equity* (SAE). Systematic Active Equity is BlackRock’s proprietary investment approach that processes the signals into actionable investment opportunities. Where AI meets human expertise, and traditional + alternate data come together to uncover smarter investment opportunities. This isn’t just another Flexi Cap Fund. It’s a new way to invest — intelligent, agile, and built for scale. NFO period: 23 Sep – 7 Oct 2025. *A technology-driven** investment approach that combines human expertise with a data-driven model to build a portfolio. ** The systematic approach involves utilizing inputs from the Fund Managers and signal research scores shared by BlackRock Inc. Stay tuned. The future of investing just got sharper. #JioBlackRock #FlexiCapFund #NFOshow more

Something big is happening in robotics - and it’s... hiding in plain sight. This post is not about dancing robots but in the data that powers them. Open robotics datasets have exploded this year, turning the field into a more scalable and collaborative ecosystem. In just two years, Hugging Face datasets grew from 11k to over 600k - and robotics is by far the fastest-growing segment. We went from 1k robotics datasets in 2024 to 27k in 2025! For comparison, text generation, the second-largest category, has only around 5k datasets in 2025. That gap is massive. Open datasets are important because robotics lives and dies by real-world robot data - video, actions, sensors, failures. By making this data easy to upload, reuse, and benchmark, researchers, startups, and large players are now releasing real-robot datasets that would have stayed locked inside labs just a few years ago. Major contributors include NVIDIA, LeRobot initiative, and a rapidly growing maker community. This surge is also enabled by cheaper video storage, better tooling, and an open-source AI culture now spilling into the physical world. And it really matters: open robotics data dramatically lowers entry barriers, accelerates learning-by-doing, and speeds up progress toward generalist and humanoid robots. Robotics won’t scale through hardware alone - but to a large extent through shared data. Viz below from AI World - link to the story and more viz/filters in comment.show more

Trained on zero real-world data. Learned to walk, pick... up boxes, and follow multi-step instructions... in the REAL world. ( 📌 Paper below) Researchers from Amazon FAR, Berkeley, Stanford, and CMU scanned real rooms with an iPhone, rebuilt them as 3D Gaussian Splatting scenes, then generated 48,000 synthetic trajectories of a Unitree G1 walking, grasping, and placing objects inside those virtual replicas. They rendered the robot's first-person camera view from each run and paired it with the matching language instruction and motion data. That's the dataset every humanoid team needs and nobody has: synced egocentric video + language + kinematics, at scale. Instead of collecting it in the real world, they manufactured it. They trained a vision-language-kinematics policy on that synthetic data alone, then deployed it on the physical G1 across five task types: navigation to a named object, lifting boxes of three different sizes with no per-size tuning, chained multi-step tasks, robustness to mid-task layout changes and flickering lights, and multi-minute long-horizon runs. No real-world fine-tuning at any point. Real-world interaction data has been the hard limit on humanoid learning... slow, expensive, and small. If scanning a room once and synthesizing thousands of labeled interactions holds up as a general recipe, that limit moves. Data stops being the bottleneck robotics teams have to solve for. 📌 Paper: Project: ——- Weekly robotics and AI insights. Subscribe free:show more