The big one. 19×39 blocks ~1,800 m² of continuous 3D environment. Left: reconstructed mesh.
Right: fully textured render. It proves you can scale world generation infinitely without collapse or drift.
@godofprompt
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Breakthrough in Infinite 3D World Generation Using AI
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WorldGrow Uses Generative AI to Create Coherent Synthetic Environments
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9×9 block layouts, hundreds of rooms, all generated by the model itself.
No manual stitching, no rendering errors. Every corridor connects naturally. WorldGrow makes synthetic worlds that feel lived in. -
WorldGrow Outperforms Generative Models in Continuous Indoor Scene Synthesis
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Here’s where it flexes against SynCity, BlockFusion, DiffInDScene, and TRELLIS. Only WorldGrow generates high-res, continuous indoor scenes with perfect texture alignment. Figure 5 literally shows you the other methods fall apart at the seams.
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WorldGrow improves 3D modeling via occlusion-aware feature aggregation
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Standard 3D models fail near occlusions and boundaries. WorldGrow fixes this with occlusion-aware feature aggregation and a retrained decoder removing color bleeding and floating geometry. Figure 3 visually compares the “vanilla” vs “scene-friendly” SLAT. The difference is
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Technical Overview of WorldGrow’s Generative AI Pipeline
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WorldGrow’s pipeline works like a growing brain: – Scene-friendly SLAT encodes 3D context
– 3D block inpainting ensures spatial continuity
– Coarse-to-fine refinement keeps global layout + fine detail Each module adds realism while keeping the world endless. -
WorldGrow: A New AI System for Infinite 3D Environment Generation
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Holy shit… this might be the first AI that can literally grow worlds 😳
— God of Prompt (@godofprompt) 28 octobre 2025
It’s called WorldGrow a new system from Huawei & SJTU that generates infinite 3D environments block by block.
No loops. No stitching. Just a single seed expanding into a seamless, photorealistic world.
→… pic.twitter.com/tiGKRncJWGHoly shit… this might be the first AI that can literally grow worlds It’s called WorldGrow a new system from Huawei & SJTU that generates infinite 3D environments block by block. No loops. No stitching. Just a single seed expanding into a seamless, photorealistic world. →
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Using AI Agents and Knowledge Graphs for Customer Intelligence
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The design behind Enterpret is genius.
— God of Prompt (@godofprompt) 27 octobre 2025
→ Real-time Knowledge Graph
→ Adaptive Taxonomy that evolves as feedback changes
→ Agent alerts that close the loop automatically
It’s not just analytics.
It’s Customer Intelligence in motion. pic.twitter.com/H88QdCLjvMThe design behind Enterpret is genius. → Real-time Knowledge Graph
→ Adaptive Taxonomy that evolves as feedback changes
→ Agent alerts that close the loop automatically It’s not just analytics. It’s Customer Intelligence in motion. -
Using AI to analyze enterprise customer feedback patterns
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Here’s what it looks like in action 👇
— God of Prompt (@godofprompt) 27 octobre 2025
Ask:
“Why are enterprise users churning in Q3?”
Enterpret instantly surfaces every pattern, complaint & correlation.
You don’t analyze feedback anymore you converse with it. pic.twitter.com/oQ9ZdTMUpSHere’s what it looks like in action Ask: “Why are enterprise users churning in Q3?” Enterpret instantly surfaces every pattern, complaint & correlation. You don’t analyze feedback anymore you converse with it.
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Enterpret uses AI to automate customer feedback analysis and alerting
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Let’s say your app keeps crashing after login. Enterpret spots 500 complaints about it across: – Support tickets
– App store reviews
– Slack messages
– Reddit threads Then it automatically alerts your PMs with context. -
AI Agents for Real-Time Feedback and Insight Automation
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Here’s what happens behind the scenes:
— God of Prompt (@godofprompt) 27 octobre 2025
1. Captures every conversation in real time
2. Builds a Knowledge Graph that links feedback → features → users
3. Uses Adaptive Taxonomy to group insights dynamically
4. Deploys AI Agents to detect bugs or churn signals instantly pic.twitter.com/sg8JsQRELMHere’s what happens behind the scenes: 1. Captures every conversation in real time
2. Builds a Knowledge Graph that links feedback → features → users
3. Uses Adaptive Taxonomy to group insights dynamically
4. Deploys AI Agents to detect bugs or churn signals instantly