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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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Crypto M - Crypto News

@CryptoM · Post #65047 · 04/10/2026, 04:10 PM

🚀 Whop Introduces Treasury Yield Product Following Tether Investment Whop has launched its Treasury yield product on March 25, following a significant investment from Tether in February, which valued the company at $1.6 billion. According to NS3.AI, the product was introduced after Tether's $200 million investment. Steven Schwartz noted that 3% of users engaged with the beta version within a week, despite the absence of a marketing campaign. The product channels funds through a Veda vault on Plasma into Aave lending markets, offering an annual percentage yield (APY) of up to 6%. The investment from Tether will enable Whop to integrate on-platform USDT wallets and payment options. #Whop#Tether#TreasuryYield#Investment#Crypto#APY#Aave#USDT#Fintech#Blockchain#AAVE