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Source channel @githubtrending · Post #15062 · Aug 15

#python#mllm#point_clouds#scene_understanding#spatial_intelligence SpatialLM is a powerful 3D language model that turns complex 3D point cloud data from videos, RGBD images, or LiDAR into clear, structured 3D scene layouts showing walls, doors, windows, and objects with labels. It works without needing special equipment and can detect user-specified object categories. This helps you understand and analyze indoor spaces better, useful for robotics, navigation, and 3D design. You can run it on your data, visualize results, and even customize detection tasks easily, making 3D scene understanding more accessible and flexible for many applications. https://github.com/manycore-research/SpatialLM

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The Digi Doodles

@Digi_doodles · Post #622 · 08/01/2025, 10:02 AM

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WeTransfer’s AI Terms: Are Artists Losing Control?🃏 July 28, 2025 · The Art Newspaper A quiet shift with loud consequences. 👂 WeTransfer has updated its terms of service to allow the use of uploaded files for AI training — sparking concern among digital artists and creatives. While the platform claims “anonymized and aggregated” data use, critics warn this could jeopardize intellectual property. What’s at stake: — Artists may unknowingly feed generative AI tools — Lack of opt-out or clear consent for creative works — Questions around ownership, credit & ethics Another wake-up call in the ongoing conversation around AI, authorship, and data rights📖 #AIArt#DigitalRights#WeTransfer#ArtAndTech#DataEthics

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