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https://www.youtube.com/watch?v=AgFScQq5yCc
This perception middleware for robots gives memory and spatial/compositional reasoning. Who wants to test run on their stack? https://coreworldmodel.com for the guide..

9jageek:

https://www.youtube.com/watch?v=AgFScQq5yCc
This perception middleware for robots gives memory and spatial/compositional reasoning. Who wants to test run on their stack? https://coreworldmodel.com for the guide..

Did you use python Yolo library for vision tracking or detection in real time

No I did not.. I will share a more current demo with you. We use dynamically generated bounding box grid layouts but using Yolov8 ir detectron is part of our plans for better supervision. Are you very active with robotics development? We should have a discussion.

Alphabyte3:
Did you use python Yolo library for vision tracking or detection in real time

Vibe code robotics code blocks and plugins using a automated code block LLMs. The platforms will have manual and automatic recommendations.

Reinforcement learning as a service RLaas in robotics. We need to improve on computing power to do this but offline and online services.

Agents, cronjobs, and moltbot will enhance robots' knowledge capacity, enabling improved learning and autonomy. This combo boosts AI capabilities.

But you know the danger because of data are mined by the robotics locally or on cloud storage. This would act as a brain of robots. No data security or privacy because every information about you your robots knows.

In the future we will have millions or billions of agentic robotics workers working together simultaneously.

Alphabyte3:
Reinforcement learning as a service RLaas in robotics. We need to improve on computing power to do this but offline and online services.

Robotics unsupervised learning uses algorithms to analyze raw data, finding hidden patterns or anomalies without predefined rules. It uncovers structures in unlabeled datasets. All robots developed is pre-trained to adapt it would be better in future doing tasks it isn't taught.


We need Nvidia,Unitree , Intel and Tesla to work on unsupervised learning rather than only supervised learning by increasing compute . This is a continuation of this idea

Collaboration agents in Ros I am waiting for and Openclaw latest version. I love Nvidia or Unitree to work on the project. Robotics reasoning need to move to the next version like 100 years automation/simulation doing tasks with higher priorities.

I read in the Stanford AI index report that, "Robots still fail at household tasks, performing just at 30% even though they excel at controlled environment evaluations (90%)."

Enter frontier robotics, advanced robots built to mitigate these failure points. One major important augmentation to achieve this is giving robots spatial memory. Remembering what they saw, where they saw it, its relationship to other objects, and when last they saw it.

https://medium.com/@boltzmind/why-household-robots-fail-and-how-persistent-object-memory-changes-the-game-fd1a6851f41b

9jageek:
I read in the Stanford AI index report that, "Robots still fail at household tasks, performing just at 30% even though they excel at controlled environment evaluations (90%)."

Enter frontier robotics, advanced robots built to mitigate these failure points. One major important augmentation to achieve this is giving robots spatial memory. Remembering what they saw, where they saw it, its relationship to other objects, and when last they saw it.

https://medium.com/@boltzmind/why-household-robots-fail-and-how-persistent-object-memory-changes-the-game-fd1a6851f41b

Localized geo spatial memory is still research Google and Nvidia should do a collaboration.
This “robotics eye network” stack lets machines see, understand, and share the world. MultiSet AI provides cm-level VPS localization for indoor/outdoor fleet coordination, with SDKs for integration. Google ARCore Geospatial API adds ∼1m global positioning via Street View/satellite data. Niantic Spatial Platform offers crowdsourced 3D maps for shared AR anchors. Together: See via camera, Know via geo-data, Share maps, Act with navigation/AR. Uses: markerless warehouse bots, precise drones.

Nvidia just fixed an issue about robotics simulation and task in real time by increasing the frame rates (FPS). Isaac Lab reaching over 150,000 frames per second (FPS) for reinforcement learning (RL) tasks as of early 2026. For real-time physical deployment, Jetson modules support high-speed perception (60-120+ FPS) and low-latency processing, critical for AI-driven, physical robotics.

Unitree achieved physical AI by using lower FPS and a Commonly support up FPS for RGB, with depth maps often operating to support real-time SLAM (Simultaneous Localization and Mapping) using perception System 3D or 4D LiDAR (e.g., Livox-MID360) and depth camera (e.g., Intel RealSense D435i) for full-environment scanning.

Building robots is costly, requiring expensive components like custom chips, lithography machines, massive circuit boards, or simpler Arduino/Raspberry Pi sensors, plus plastic and metal 3D printers.

Assembly demands expertise to avoid damaging parts. After building, marketing becomes the hardest challenge. Success depends on budget, technical skill, and your ability to sell the finished robot.

nvidia omniverse ,YOLO, OpenCV, MoveIt2,ROS2, Openclaw ,KCF algorithms, Nvidia Jetson Orin Nano and MediaPipe integrated by good mapping system delivering visual perception for advanced applications like autonomous driving, face recognition and tracking.

In technology you have to add more constraints to make it more useful and better. Improving on robotics from teleoperated to semi are the goals.

We watch cartoons and movies of giant robots now Unitree GDO1 Lands bringing it to reality. For years, the idea of humans piloting towering, bipedal mechas was purely the stuff of sci-fi blockbusters like Pacific Rim. But the boundary between sci-fi imagination and real-world engineering is rapidly blurring in China. Unitree isn't slowing down.

Source: Global times

Robotics dual IP camera protocol with good internal and external access based permissions. one camera will work as vision while the others will see multiple things using advanced Visual Positioning System (VPS) mapping the environment via AI IP protocols and using advanced predictive models.

Alphabyte3:
Robotics unsupervised learning uses algorithms to analyze raw data, finding hidden patterns or anomalies without predefined rules. It uncovers structures in unlabeled datasets. All robots developed is pre-trained to adapt it would be better in future doing tasks it isn't taught.


We need Nvidia,Unitree , Intel and Tesla to work on unsupervised learning rather than only supervised learning by increasing compute . This is a continuation of this idea

New job title robotics data analyst training of thousands or millions of simulation but AI and humans based. Auto simulation and preprocessed simulation by AI and humans verifications systems. Analyzed sensor, telemetry, and behavior data from large-scale simulations to identify model failures and guide retraining of robotics AI. Built preprocessing pipelines that blended AI-generated labels with human annotations, reducing simulation-to-reality gap and speeding model iteration.

when this is done robots can be able to adapt and learn following it access to locally simulated data offline and cloud or online simulation data . It would follow a long queued process. Many nations are already developing this robotics data analyst are paid well .

A new section of robotics on different domain like AUV ,UAVs and UGVs. my question for those what are the uses case note that the motion sensor and actuator are slightly different imagine them running on Openclaw brain systems .

Guess our data is used to train these AI Models

darkwebnews:
Guess our data is used to train these AI Models

OpenAI , Google, Anthropic and others AI wants to know everything about everyone on the planet not just data . AGI is a threat to privacy.

We are talking about using advanced AI gyroscope sensors and models in robotics for precision with a guide model.

Unitree and Nvidia needs to build the Space multipurpose drone for SpaceX 🌐. Space drones on Mars with 3d printed carbon fiber will be like 5m it can perform tasks like repairs , building or creating and mapping .


The drone will have an inbuilt model to connect different tools like welding tools , mechanical engineering tools and electrical tools . Project like this needs robotics data analyst in different engineering field .

Physical AI demands a new standard of safety. NVIDIA Halos brings the full-stack platform proven in autonomous vehicles to the next generation of humanoids and industrial robots.

Nvidia and Unitree are making robotics more knowledge accessible. As a robotics engineer or company with ideas you can offer contributions in Opensource it will boost your portfolio both giants are making robotic engineering easier to learn for both beginners and expert level.


https://github.com/NVIDIA/halos-outside-in-safety

robotics spatial intelligence + Physical AI = Full embodiment intelligence

The claims that somehow by just scaling up LLMs, we're going to reach super human intelligence, that is simply not going to happen by Yann LeCun . Robotics is not a smart as an insect but will find a way to bridge the gap and prove Yann LeCun wrong. He hasn't even seen Openclaw controlling robots autonomously via voice commands. The problem is that it is difficult to code intuition in robot everything are simulation with our current level of technology. Jepa might solve some problems I doubt it will give robots intuition.

Alphabyte3:
The claims that somehow by just scaling up LLMs, we're going to reach super human intelligence, that is simply not going to happen by Yann LeCun . Robotics is not a smart as an insect but will find a way to bridge the gap and prove Yann LeCun wrong. He hasn't even seen Openclaw controlling robots autonomously via voice commands. The problem is that it is difficult to code intuition in robot everything are simulation with our current level of technology. Jepa might solve some problems I doubt it will give robots intuition.

AGI still very far.

Suicideboy:
AGI still very far.

It is not the just software that are the problem but hardware now so with current tech it is difficult to achieve it and releasing it too early is a problem of national security. Humans won't need to work and spend more time reading and solving problems related to their region. To achieve AGI we need fresh ideas from researchers all over the world. AI already solved the discrepancies in top talented programmers.

Robotics need a unified system which will be updated monthly or yearly to accelerate towards AGI . In China and some countries robots are replacing humans to maximize profits and Carryout difficult missions.


Big tech are already thinking of launching space Datacenter and others in different new places. Small step are needed to create something tangible .

Wuji tech just solve a major problem in robotics it is Unintree might want to update their Humanoid robotic hand. China leading powerhouse of robotics not the US .



https://github.com/wuji-technology

Multi-agent ESP 32 controller is what engineers need to build it will consume all human data and skill set. Including gestures recognition in performing tasks autonomously . Embedded system engineers need to switch fully to robotics to build larger components and toolkits with enough power with minimal consumption. IoT is the beginning of the journey .


We should spend more money on human well-being than AI or robots . Humans first robots last . Stop treating humans like machines.