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A Hugging Face social post reposted a message from NVIDIA Robotics promoting the idea of running open-source vision-language models on edge devices. The post asks whether developers want to “bring open-source vision language models to the edge” and references a forthcoming resource (“Check out our @ …”), but the linked content or full details are not included in the available text. Key players mentioned are Hugging Face and NVIDIA Robotics, and the topic centers on deploying multimodal AI (visio
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A Hugging Face social post reposted a message from NVIDIA Robotics promoting the idea of running open-source vision-language models on edge devices. The post asks whether developers want to “bring open-source vision language models to the edge” and references a forthcoming resource (“Check out our @ …”), but the linked content or full details are not included in the available text. Key players mentioned are Hugging Face and NVIDIA Robotics, and the topic centers on deploying multimodal AI (vision-language models) outside the cloud, on local hardware. With only the title fragment available, no specific model names, hardware platforms, performance claims, dates, or product announcements can be confirmed.
Hugging Face announced that BEDLAM2.0 image and depth data are now available on its platform, according to a repost of a message from Michael J. Black. Based on the title alone, the update indicates that the BEDLAM2.0 dataset includes both RGB images and depth information and has been published for access or download through Hugging Face’s dataset hosting and distribution tools. The release matters because making multimodal computer-vision data easier to find and retrieve can support research and development in areas such as 3D perception, depth estimation, and human or scene understanding. No additional details—such as licensing terms, dataset size, benchmarks, or release date—were provided in the available text.