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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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AI & Law

@ai_and_law · Post #99 · 08/30/2023, 07:04 AM

Zoom Addresses EU Privacy Concerns and Updates Terms of Service Greetings! In response to discussions about potential EU privacy law implications, Zoom issues a statement and revises its Terms of Service. The focus? Ensuring customer data isn't utilized to train AI models. Zoom's statement and Terms affirm that user-generated content, including audio, video, chat, and more, isn't employed for training Zoom's or any third-party AI models. This step aims to dispel any concerns. Zoom initially shared its statement on August 7 and later updated it on August 11, aligned with the revised Terms. The shared stance now unequivocally states, "Zoom does not use any of your customer content to train AI models." Earlier, a Stack Diary article flagged changes to Zoom's March Terms, raising potential concerns about broad data utilization for AI model training. Zoom's quick response aims to address these concerns and reaffirm privacy commitments. #Zoom#PrivacyMatters#TermsOfService#AIModels#DataProtection#PrivacyLaw#TechUpdates