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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 #4286 · 03/02/2025, 01:00 PM

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CZ Proposes New Token Unlock Model 🔵 CZ proposes a tokenomics model linking unlocks to price growth and time, reducing market impact. 😏 Initial 10% sold for development. 😏 Unlock every 6 months, contingent on 2x price increase maintained for 30 days. 😏 Max 5% unlock each time. ❓ Market implications include lack of sell pressure from mass unlocks and encouraging long-term projects. 🔴 Critics argue it could disadvantage small teams reliant on token price. Could this model reshape token economies? Read more: Link #CZ#Tokenomics#Crypto#Blockchain#Ethereum#MarketTrends#Investing#DeFi#Finance#Startups#Innovation#LongTerm#SmartContracts#PriceGrowth#Unlocks#Community#PricingModel#InvestmentStrategies#ElonMusk#HongKong