Into:404-GEN
3D worlds, generated on demand.
As of · Jun 4, 10:37 UTC
Type a text prompt, get a 3D model. 404-GEN is building the infrastructure for spatial computing: on-demand 3D asset generation for AR, VR, XR, gaming, and any application that needs three-dimensional content at scale.
What is 404-GEN
404-GEN is a that generates 3D models from text descriptions. You type "a medieval castle with a drawbridge" and produce a 3D asset you can use in a game, AR experience, or virtual world. The subnet handles everything from prompt processing to quality validation.
The simple version: Imagine typing a description of any object and getting back a 3D model you can rotate, place in a scene, or 3D print. That's 404-GEN: text in, 3D model out.
Centralized equivalent: Think Luma AI's Genie or Meshy, but powered by competing miners who each try to produce the best 3D asset for your prompt.
How it works:
- Miners use neural rendering techniques and Gaussian splatting to convert text prompts into 3D assets. Tasks come from organic traffic (API, Discord bot, Blender plugin) and synthetic datasets generated by quantized LLMs (Llama3-8B, Mixtral-11Bx2). Performance is measured over 8-hour evaluation windows.
- deploy MetaCLIP neural networks to evaluate 3D model quality by rendering 16 different camera angles (8 fixed, 8 random) and computing semantic similarity scores against the original prompts. Batch processing with GPU acceleration enables real-time validation at scale.
Why This Matters
- The problem it solves: 3D content is the bottleneck for spatial computing. Creating a single high-quality 3D model takes hours or days with traditional tools. AR/VR applications need thousands of assets.
- The opportunity: Apple Vision Pro, Meta Quest, and the broader AR/VR market need 3D content at scale. The market for 3D assets is projected to grow alongside spatial computing adoption.
- The Bittensor advantage: Competitive generation means multiple approaches to the same prompt. Gaussian splatting, neural radiance fields, and other techniques compete simultaneously, surfacing the best method per prompt type.
- Traction signals: Blender plugin for direct integration into 3D workflows. Discord bot for casual generation. API for programmatic access. 2,514 net 7-day inflow. Led by Ben James (CEO). Highest momentum score in this batch at 68.
Other research from the same neighborhood of the network.
