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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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@emagzinewspars · Post #9460 · 11/03/2025, 03:27 AM

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#The_Bloomberg🇺🇸📕[PDF]⬇️ #November2025 #Monthly_Magazines For learning, for free(dom). @backupofmagazines This issue pits #GavinNewsom against a shifting #USPolitics map while probing the supposed #AIBubble, from frothy valuations to real-world productivity. A climate-forensics read asks whether #CloudSeeding worsened Dubai’s deadly storm—at the nexus of #ExtremeWeather and #ClimateChange. The geo-economics file tracks India’s wobbling investments, China’s expanding #Ports, and weaponized #SupplyChains. For investors, the issue weighs #ETFs, #401k tweaks, #BigTech concentration risk, and hedges in #Europe and #Gold. Lifestyle detours sample Utah powder and the dive-bar revival. It’s a brisk tour of power, money, and culture in a volatile world. #Markets#Investing#Energy#MiddleEast#Africa#Healthcare#Birkenstocks