@berryxia: Folks, 3D asset generation is truly taking off. A team led by Assistant Professor Elliott Wu (former Stanford, Oxford background) at the University of Cambridge just released Articraft — a true agentic coding system. It doesn't just generate static 3D models, it...

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The team of Assistant Professor Elliott Wu from the University of Cambridge released Articraft — an agentic coding system that can automatically generate interactive 3D assets with parts, joints, and realistic motion, and open-sourced the Articraft-10K dataset, significantly lowering the asset threshold for robot training and physical AI.

Folks, 3D asset generation is truly taking off. A team led by Assistant Professor Elliott Wu (former Stanford, Oxford background) at the University of Cambridge just released Articraft — a true agentic coding system. It doesn’t just generate static 3D models; it allows an AI agent to write its own code, execute it, receive physical verification feedback, and iterate continuously, ultimately outputting interactive 3D assets with parts, joints, and realistic motion that can be directly thrown into robot simulation and physical AI scenarios. Previously, creating a high-quality articulated asset could take days or even weeks; now the agent runs fully automatically, and the entire process is incredibly efficient. They also open-sourced the Articraft-10K dataset: over 10,000 articulated 3D objects across 250 categories, all interactive and simulation-ready, pushing the asset threshold for large-scale robot training and physical-world AI to new lows. The "data hunger" problem of physical AI and robot simulation has been largely eliminated by this agentic pipeline. Project page here: https://articraft3d.github.io Full code and dataset are also open-sourced on GitHub. If you are working on robotics, simulation, physical AI, or 3D content generation, this open-source release is worth trying right away. PS: Not yet tested; review to follow!
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Cached at: 05/16/26, 09:17 AM

Brothers, 3D asset generation is about to take off completely.

Elliott Wu, Assistant Professor at Cambridge (formerly Stanford, Oxford), and his team just released Articraft — a truly agentic coding system.

It doesn’t just generate static 3D models. Instead, it lets an AI agent write its own code, execute it, receive physics validation feedback, iterate, and ultimately output interactive 3D assets with parts, joints, and realistic motion — ready to plug directly into robot simulations and physical AI scenarios.

Previously, creating a high-quality articulated asset took days or even weeks. Now the agent handles everything automatically, and the whole process is ridiculously efficient.

They also open-sourced the Articraft-10K dataset: over 10,000 articulated 3D objects across 250 categories, all interactive and simulation-ready. This drastically lowers the asset barrier for large-scale robot training and physical world AI.

The “data hunger” problem in physical AI and robot simulation has been largely addressed by this agentic pipeline.

Project page: https://articraft3d.github.io
Full code and dataset are open-sourced on GitHub as well.

If you work on robotics, simulation, physical AI, or 3D content generation, this open-source release is worth trying immediately.

PS: Not tested yet — review coming later!

Elliott / Shangzhe Wu (@elliottszwu): Check out Ariticraft 🦾 - a highly efficient agentic system that generates articulated 3D assets fully automatically at scale!

🚀

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