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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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Venture Village Wall 🦄

@venturevillagewall · Post #4339 · 03/08/2025, 01:00 PM

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Top 5 Insights from Trendoscope Lab 1️⃣ a16z's new report reveals top B2C AI apps by traffic differ from revenue leaders like photo and video editors. Read more 2️⃣ Google launches AI Mode with Gemini, initially for Google One subscribers, enhancing AI SEO relevance. Details here 3️⃣ Short drama apps surge with 221% annual growth in downloads, affecting traditional streamers like Netflix and Disney+ that declined by 35%. Insight found here 4️⃣ Google and Meta enable developers to access cameras on XR devices, easing previous privacy restrictions. More info and here 5️⃣ Google enhances Android widget visibility with new filters and dedicated pages. Learn more #AI#Google#Tech#Streaming#XR#Investments#B2C#Apps#VideoEditing#Photos#Dramas#SEO#Privacy#Android#Widgets#Investing#VC#a16z#Trends#Innovation

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