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Virtual Community provides an online pipeline that automatically generates 3D scenes from real geospatial data, performing comprehensive cleaning and enhancement of both geometry and texture — including mesh simplification, texture refinement, object placement, and automatic annotation. 3/n

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Chuang Gan

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20,795 Aufrufe • vor 1 Jahr •via X (Twitter)

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This guy built a visual scanner that reads 468 points on his face and 42 points on his hands from a regular webcam and turns them into a cloud of thousands of particles right between his palms. Inside, MediaPipe and TouchDesigner are linked: the first captures hands and face from the webcam with high accuracy, the second turns those coordinates into a live plane and feeds it into a POP system that instantly generates a swarm of particles in the shape of a head. No studio, no render farmer, no VR headset. Just a laptop, a webcam, and 1 TouchDesigner session. And traditional VJ studios keep teams of 5 people on a setup with lighting, custom hardware, and commercial plugins, while his expenses are only a TouchDesigner subscription and a regular USB camera. One laptop runs MediaPipe and TouchDesigner simultaneously, holds the camera stream at 60 FPS without drops, and in parallel processes 468 face points + 21 points on each hand. The camera captures frame after frame, MediaPipe in real time sends TouchDesigner the finger coordinates and face geometry, and the POP operator inside the engine translates those numbers into thousands of particle points with colors from bright pink to gold. This setup immediately defines the role of the tool and the limits of its autonomy. It knows where the fingertips are at every moment of the frame. It knows how to read the face geometry at any angle to the camera. It knows how to draw a swarm of particles between them with the right color and contour. → MediaPipe pulls 468 points from the face and 21 points from each hand, 60 times per second → TouchDesigner receives those coordinates, builds a virtual rectangle between the fingertips, and feeds it into the POP system → POP generates thousands of particle points in the shape of a head, coloring them in a gradient from bright pink to gold → The HUD layer adds green corners and a blue neon frame, styling the image like an AR interface → All layers assemble into 1 real-time frame that projects back onto the video in the camera window → The final image is recorded to a file or broadcast to a projector for a live installation And only when the guy spreads his hands wider does the plane between the palms stretch; brings them together, it narrows. Otherwise the system runs on its own. And when he moves from his home room to a concert hall, the same laptop with the same webcam launches the same TouchDesigner session in just 5 minutes, without reconfiguration, without a new team, and without a single line of new code. In his work setup there is no studio of his own and no team for assembly. On the desk sits a laptop with a webcam, on top run MediaPipe and TouchDesigner with POP operators, and the same setup through a USB camera moves to any concert without a new configuration. Out of everything I have seen this year, this is the cleanest Creative Coding setup on 1 laptop: 0 render farms, 0 studio lighting, and between them 3 libraries, thousands of particle points, and 1 webcam.

Blaze

38,242 Aufrufe • vor 3 Monaten

A Letter to Our Community: The Road Ahead for Robotics To our Community and Partners, As we step into 2026, our mission at Axis is clearer than ever: Constructing the definitive End-to-End Scaling Layer for Robotics. Our goal is to accelerate the transfer of diverse human intelligence into Robotics General Intelligence (RGI). By owning the critical path of intelligence creation, we are turning the physical limitations of robotics into a scalable, software-driven future. Here is our strategic outlook and roadmap for the year ahead. The Core Thesis: Simulation is the Only Way Out The path to RGI is currently blocked by Data Scarcity, Generalization Fragility, and Hardware Fragmentation. At Axis, we believe Simulation is the only way out. Our Simulation Data Platform and Data Augmentation Engine transform raw data into "Synthetic Gold". Backed by academic milestones like Roboverse, Skill Blending, and GraspVLA, we have proven that pure simulation can achieve the generalization required for the real world. We don’t just collect data; we architect it. The Engine: Why Crypto? We believe RGI should come from all, not a few. Crypto is not just a feature; it is the primitive that powers our entire ecosystem flywheel: - Incentive Mechanism: Democratizing contribution and rewarding the trainers and developers. - Assetization: Turning proprietary data and refined models into liquid, ownable assets. - Verifiable Workflow: We are opening the "Black Box" of AI. By bringing total transparency to the Task Generation → Data Collection → Model Training pipeline, we ensure every byte of intelligence is verifiable, traceable, and secure. 2026 Strategic Deliverables This year, we are committed to delivering three foundational pillars: - The World's Largest Training Dataset for Robots: A robot training set—diverse, high-quality interaction data at an unprecedented scale. - A Robotics Foundation Model: A universal robotic brain trained on our pure simulation and synthetic data, capable of robust cross-embodiment transfer and open-world adaptability. - Evolvable Robot Hardware: Robots deployed with Axis models that autonomously evolve through continuous interaction, turning every deployment into a self-improving node within our RGI network. The Ultimate Vision We are building more than models; we are architecting the Distributed Machine Economy. A future where every dataset, model, and robotic embodiment is a verifiable asset in a global, autonomous network. Thank you for building the future of intelligence with us✌️📷
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A Letter to Our Community: The Road Ahead for Robotics To our Community and Partners, As we step into 2026, our mission at Axis is clearer than ever: Constructing the definitive End-to-End Scaling Layer for Robotics. Our goal is to accelerate the transfer of diverse human intelligence into Robotics General Intelligence (RGI). By owning the critical path of intelligence creation, we are turning the physical limitations of robotics into a scalable, software-driven future. Here is our strategic outlook and roadmap for the year ahead. The Core Thesis: Simulation is the Only Way Out The path to RGI is currently blocked by Data Scarcity, Generalization Fragility, and Hardware Fragmentation. At Axis, we believe Simulation is the only way out. Our Simulation Data Platform and Data Augmentation Engine transform raw data into "Synthetic Gold". Backed by academic milestones like Roboverse, Skill Blending, and GraspVLA, we have proven that pure simulation can achieve the generalization required for the real world. We don’t just collect data; we architect it. The Engine: Why Crypto? We believe RGI should come from all, not a few. Crypto is not just a feature; it is the primitive that powers our entire ecosystem flywheel: - Incentive Mechanism: Democratizing contribution and rewarding the trainers and developers. - Assetization: Turning proprietary data and refined models into liquid, ownable assets. - Verifiable Workflow: We are opening the "Black Box" of AI. By bringing total transparency to the Task Generation → Data Collection → Model Training pipeline, we ensure every byte of intelligence is verifiable, traceable, and secure. 2026 Strategic Deliverables This year, we are committed to delivering three foundational pillars: - The World's Largest Training Dataset for Robots: A robot training set—diverse, high-quality interaction data at an unprecedented scale. - A Robotics Foundation Model: A universal robotic brain trained on our pure simulation and synthetic data, capable of robust cross-embodiment transfer and open-world adaptability. - Evolvable Robot Hardware: Robots deployed with Axis models that autonomously evolve through continuous interaction, turning every deployment into a self-improving node within our RGI network. The Ultimate Vision We are building more than models; we are architecting the Distributed Machine Economy. A future where every dataset, model, and robotic embodiment is a verifiable asset in a global, autonomous network. Thank you for building the future of intelligence with us✌️📷

Axis Robotics

27,858 Aufrufe • vor 7 Monaten

honestly no surprise why Silicon Valley is so obsessed with Matic robots right now > basically a Roomba on steroids > vacuums first, then mops > uses five cameras to build a live 3D map of your home > recognizes rugs, wires, furniture, pets, and people, then changes how it cleans > point at a mess and say “hey Matic, clean this” and it does > an NVIDIA Jetson inside the robot handles all the vision, mapping, and navigation > raw footage is discarded in real time and your 3D map never leaves the device btw that last privacy part is extremely underrated IMO my biggest fear with robotics is putting moving cameras and microphones inside our most private spaces without knowing where the data goes. > this week, camera components on Royal Navy drones were caught phoning home to China > Chinese Unitree robot dogs were found with a backdoor that let anyone with the key remotely control them and watch through their cameras > Roombas sent images from inside homes to overseas labelers, including a woman on the toilet and a child your home is your most sacred private space. if you're gonna buy a robot that can physically record, map, and move through it, make sure it's secure!
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honestly no surprise why Silicon Valley is so obsessed with Matic robots right now > basically a Roomba on steroids > vacuums first, then mops > uses five cameras to build a live 3D map of your home > recognizes rugs, wires, furniture, pets, and people, then changes how it cleans > point at a mess and say “hey Matic, clean this” and it does > an NVIDIA Jetson inside the robot handles all the vision, mapping, and navigation > raw footage is discarded in real time and your 3D map never leaves the device btw that last privacy part is extremely underrated IMO my biggest fear with robotics is putting moving cameras and microphones inside our most private spaces without knowing where the data goes. > this week, camera components on Royal Navy drones were caught phoning home to China > Chinese Unitree robot dogs were found with a backdoor that let anyone with the key remotely control them and watch through their cameras > Roombas sent images from inside homes to overseas labelers, including a woman on the toilet and a child your home is your most sacred private space. if you're gonna buy a robot that can physically record, map, and move through it, make sure it's secure!

Ole Lehmann

45,092 Aufrufe • vor 9 Tagen

Proud to announce my role as an official Ambassador for Atlas Ora. Excited to contribute to a decentralized travel platform that is bringing the short-term rental economy fully on-chain. Atlas Ora is building an open network where hosts and guests connect directly without intermediaries taking a cut. Each booking runs through smart contracts, with payments handled transparently on-chain. No hidden fees, no delayed payouts only verified listings and secure transactions that both sides can trust. The model gives ownership back to the community. Hosts keep more of what they earn, guests pay a fair rate, and reputation is built through verifiable on-chain data rather than centralized reviews. Beyond short-term rentals, the platform opens possibilities for tokenized incentives, loyalty programs, and real economic participation in the travel ecosystem. Atlas represents a shift from platform-owned markets to user-owned networks where value flows directly between people. Proud to stand behind a project that turns travel into an open, transparent, and self-governing economy. $AORA
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Proud to announce my role as an official Ambassador for Atlas Ora. Excited to contribute to a decentralized travel platform that is bringing the short-term rental economy fully on-chain. Atlas Ora is building an open network where hosts and guests connect directly without intermediaries taking a cut. Each booking runs through smart contracts, with payments handled transparently on-chain. No hidden fees, no delayed payouts only verified listings and secure transactions that both sides can trust. The model gives ownership back to the community. Hosts keep more of what they earn, guests pay a fair rate, and reputation is built through verifiable on-chain data rather than centralized reviews. Beyond short-term rentals, the platform opens possibilities for tokenized incentives, loyalty programs, and real economic participation in the travel ecosystem. Atlas represents a shift from platform-owned markets to user-owned networks where value flows directly between people. Proud to stand behind a project that turns travel into an open, transparent, and self-governing economy. $AORA

Jade🃏

14,584 Aufrufe • vor 10 Monaten

This looks like a regular IT server room. But it is actually the main avionics compartment of an Airbus A350, a rare view into what sits at the very front of the aircraft, directly beneath the cockpit floor. Inside are 22 purpose built computing modules made by Thales, each costing more than $100,000+ They host multiple aircraft systems, processing everything from flight controls and landing gear to hydraulics, fuel, electrical systems and flight warnings. All of them are connected through a dual redundants AFDX network, with 14 switches and 29 remote data concentrators distributed throughout the aircraft. Keeping this computing architecture running requires an estimated 50-60+ kW of electrical power. The electricity keeping all of this computing hardware alive is generated in real time from the aircraft's two engines. Each engine mechanically drives two generators through its accessory gearbox, giving the A350 four generators capable of producing up to 100 kVA each. That electricity then flows through the aircraft's power network, where transformers and rectifiers convert it into the different AC and 28 V DC supplies the avionics need. And if those generators fail, the aircraft has layers of backup power, including the APU and, in an extreme emergency, a ram air turbine that deploys automatically if all systems fail. The A350 has two independent avionics cooling circuits, heat extraction fans and backup airflow paths to keep the computers within their operating limits. So the next time you hear the word autopilot, remember what it really takes to make an Airbus A350 fly itself, An entire architecture of computers, networks, redundant power and cooling, hidden beneath the floor where no passenger ever sees it. Source, maintenancemode
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This looks like a regular IT server room. But it is actually the main avionics compartment of an Airbus A350, a rare view into what sits at the very front of the aircraft, directly beneath the cockpit floor. Inside are 22 purpose built computing modules made by Thales, each costing more than $100,000+ They host multiple aircraft systems, processing everything from flight controls and landing gear to hydraulics, fuel, electrical systems and flight warnings. All of them are connected through a dual redundants AFDX network, with 14 switches and 29 remote data concentrators distributed throughout the aircraft. Keeping this computing architecture running requires an estimated 50-60+ kW of electrical power. The electricity keeping all of this computing hardware alive is generated in real time from the aircraft's two engines. Each engine mechanically drives two generators through its accessory gearbox, giving the A350 four generators capable of producing up to 100 kVA each. That electricity then flows through the aircraft's power network, where transformers and rectifiers convert it into the different AC and 28 V DC supplies the avionics need. And if those generators fail, the aircraft has layers of backup power, including the APU and, in an extreme emergency, a ram air turbine that deploys automatically if all systems fail. The A350 has two independent avionics cooling circuits, heat extraction fans and backup airflow paths to keep the computers within their operating limits. So the next time you hear the word autopilot, remember what it really takes to make an Airbus A350 fly itself, An entire architecture of computers, networks, redundant power and cooling, hidden beneath the floor where no passenger ever sees it. Source, maintenancemode

Ammanichanda

66,313 Aufrufe • vor 4 Tagen