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Introducing the Robora 3D Builder by our Co-Founder, Guang Cheng: a web based, drag and drop interface for rapid robotics prototyping. Designed for hobbyists and DIY enthusiasts, the MVP includes 5 - 8 essential hardware modules: wheeled bases, motors, servos, LiDAR, sensors, and an integrated starter brick for power... show more

Robora

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40,647 次观看 • 11 个月前 •via X (Twitter)

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The first universal 3D robot viewer for the browser… load URDF, MJCF, or USD in seconds. No installs. No setup. Developer Victor Oldensand has built Mechaverse, a universal 3D robotics viewer that works on desktop and even mobile (if your phone is strong enough). No installs. No setup. Just drag and drop your robot model. Mechaverse merges and improves the work of several open-source projects, including: ✅ Mujoco_wasm (MuJoCo in the browser) ✅ USD-viewer (OpenUSD) ✅ URDF-loaders … into one clean, cross-platform tool. 💻 Try it here: Built in just 4 days, it supports URDF, MJCF, and OpenUSD formats via Three.js, with rendering powered by WebAssembly. Perfect for quickly inspecting robot models or scenes without heavyweight desktop software.

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🚀 Announcing Echo — our new frontier model for 3D world generation. Echo turns a simple text prompt or image into a fully explorable, 3D-consistent world. Instead of disconnected views, the result is a single, coherent spatial representation you can move through freely. This is part of a bigger shift in AI: from generating pixels and tokens to generating spaces. Echo predicts a geometry-grounded 3D scene at metric scale, meaning every novel view, depth map, and interaction comes from the same underlying world — not independent hallucinations. Once generated, the world is interactive in real time. You control the camera, explore from any angle, and render instantly — even on low-end hardware, directly in the browser. High-quality 3D world exploration is no longer gated by expensive equipment. Under the hood, Echo infers a physically grounded 3D representation and converts it into a renderable format. For our web demo, we use 3D Gaussian Splatting (3DGS) for fast, GPU-friendly rendering — but the representation itself is flexible and can be easily adapted. Why this matters: consistent 3D worlds unlock real workflows — digital twins, 3D design, game environments, robotics simulation, and more. From a single photo or a line of text, Echo builds worlds that are reliable, editable, and spatially faithful. Echo also enables scene editing and restyling. Change materials, remove or add objects, explore design variations — all while preserving global 3D consistency. Editing no longer breaks the world. This is only the beginning. Echo is the foundation for future world models with dynamics, physical reasoning, and richer interaction — environments that don’t just look right, but behave right. Explore the generated worlds on our website and sign up for the closed beta. The era of spatial intelligence starts here. 🌍 #Echo #WorldModels #SpatialAI #3DFoundationModels Check it out:

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FREE and open-source Bitcoin mining hardware: Don’t throw away or sell your S19j, S19k, or S19 Pro units just yet, developing something tailored for our Bitcoin-mining HeatHarvest greenhouse, semi-waterproof, moisture-resistant, and packed with some intriguing extras. Securing the hashboard with lock mechanisms was a priority, along with a tough and durable 3d printable frame that ties cleanly into other materials after printing. Working in mounts for alternative thermal-management modules, currently prototyping. Beyond the core functions, kept the pleb #Bitcoin miner in mind with this design, many pleb miners have small print area 3D printers, parts are kept within ranges to fit smaller printer beds. This is Prototype 1, the basic concept. Logged a dozen mod notes, now it’s back to CAD and reprints. Stay tuned, this is shaping up to be perfect for solo plebs mining at home and DIY Bitcoin heat capture projects.

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Lukas Ziegler

20,361 次观看 • 2 个月前

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RAF

15,720 次观看 • 2 年前

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Lukas Ziegler

233,110 次观看 • 9 个月前

It's a 3D printer, and 3D assembly station! 🖨️ The Functgraph developed at Meiji University starts as a regular 3D printer but upgrades itself into a mini factory. It can print parts for its own tools, pick them up, clean them, and put them together, all by itself. Think of it like a robot that can 3D print a spatula, assemble it, and then use it to flip pancakes. 🥞 Instead of just printing objects, the Functgraph can actually perform physical tasks, like folding laundry or slicing vegetables, by using printed and assembled tools. It’s a step toward the idea of a robot that can download "apps" as physical skills, much like your phone downloads software! 👀 ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

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Lukas Ziegler

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15,295 次观看 • 1 年前

Introducing the composable reputation API for agents. The FairScale Agent API is now open to any team building on Solana Gate access, transactions and assess credibility in real time. Score any agent or wallet based on behaviour, deployer, counterparties, and network. Use our FairScore, or define your own by weighting features through a custom scoring endpoint.

Introducing the composable reputation API for agents. The FairScale Agent API is now open to any team building on Solana Gate access, transactions and assess credibility in real time. Score any agent or wallet based on behaviour, deployer, counterparties, and network. Use our FairScore, or define your own by weighting features through a custom scoring endpoint.

FairScale

16,896 次观看 • 4 个月前

Robora x Lemorele We are excited to announce the integration of the Robora P300 (R) model. An exclusive model developed in partnership with Lemorele, features a custom Robora-exclusive SKU and hardware configuration designed to support high-performance, wireless video streaming for AI training and perception. We will integrate this specialized unit into our VLA Module. The Robora P300 (R) enables seamless, real-time capture of high-definition HDMI video from external cameras, allowing users to wirelessly feed visual data directly into the VLA training pipeline. This enhances capabilities such as multi-view learning, remote annotation, and real-world AI fine-tuning, all without requiring tethered camera setups. While the full Robora robotics platform is still in development, users will be able to use the Robora P300 (R) hardware with their existing iOS or Android devices, enabling them to begin collecting and streaming visual data for VLA from mobile platforms. As part of our commitment to the Robora community, we will be offering exclusive giveaways of the Robora P300 (R) hardware to token holders, giving early supporters the opportunity to contribute directly to Robora’s growing AI training ecosystem and to gain early access to the tools that power the future of robotics and intelligent vision.

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Robora

19,276 次观看 • 10 个月前

Clerk Billing update! 🎉 The team has been hard at work building the foundations of the most compelling user billing product for SaaS companies. No need to integrate with any payment provider, or watch for web hooks, or write payment code. It all just works out of the box. And comes with User Entitlements BUILT-IN! Check it out 🎥 If you're interested in early access, DM me and I'll toss you on the early access list 🤝 Also, if you're interested in building with me, I'm hiring for senior product, senior design and senior engineering roles! DM me with a link to your LinkedIn/portfolio/github 👍

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Drew Wilson

53,985 次观看 • 1 年前

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Alex Barashkov

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Runway

80,385 次观看 • 8 个月前

Blended-NeRF: Zero-Shot Object Generation and Blending in Existing Neural Radiance Fields paper page: Editing a local region or a specific object in a 3D scene represented by a NeRF is challenging, mainly due to the implicit nature of the scene representation. Consistently blending a new realistic object into the scene adds an additional level of difficulty. We present Blended-NeRF, a robust and flexible framework for editing a specific region of interest in an existing NeRF scene, based on text prompts or image patches, along with a 3D ROI box. Our method leverages a pretrained language-image model to steer the synthesis towards a user-provided text prompt or image patch, along with a 3D MLP model initialized on an existing NeRF scene to generate the object and blend it into a specified region in the original scene. We allow local editing by localizing a 3D ROI box in the input scene, and seamlessly blend the content synthesized inside the ROI with the existing scene using a novel volumetric blending technique. To obtain natural looking and view-consistent results, we leverage existing and new geometric priors and 3D augmentations for improving the visual fidelity of the final result. We test our framework both qualitatively and quantitatively on a variety of real 3D scenes and text prompts, demonstrating realistic multi-view consistent results with much flexibility and diversity compared to the baselines. Finally, we show the applicability of our framework for several 3D editing applications, including adding new objects to a scene, removing/replacing/altering existing objects, and texture conversion.

Blended-NeRF: Zero-Shot Object Generation and Blending in Existing Neural Radiance Fields paper page: Editing a local region or a specific object in a 3D scene represented by a NeRF is challenging, mainly due to the implicit nature of the scene representation. Consistently blending a new realistic object into the scene adds an additional level of difficulty. We present Blended-NeRF, a robust and flexible framework for editing a specific region of interest in an existing NeRF scene, based on text prompts or image patches, along with a 3D ROI box. Our method leverages a pretrained language-image model to steer the synthesis towards a user-provided text prompt or image patch, along with a 3D MLP model initialized on an existing NeRF scene to generate the object and blend it into a specified region in the original scene. We allow local editing by localizing a 3D ROI box in the input scene, and seamlessly blend the content synthesized inside the ROI with the existing scene using a novel volumetric blending technique. To obtain natural looking and view-consistent results, we leverage existing and new geometric priors and 3D augmentations for improving the visual fidelity of the final result. We test our framework both qualitatively and quantitatively on a variety of real 3D scenes and text prompts, demonstrating realistic multi-view consistent results with much flexibility and diversity compared to the baselines. Finally, we show the applicability of our framework for several 3D editing applications, including adding new objects to a scene, removing/replacing/altering existing objects, and texture conversion.

AK

62,768 次观看 • 3 年前