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Source channel @githubtrending · Post #15365 · Dec 24

#jupyter_notebook DINOv3 offers powerful self-supervised vision models from Meta AI, like ViT up to 7B parameters and ConvNeXt, pretrained on 1.7B web or satellite images. Load them easily via PyTorch Hub, Hugging Face Transformers (v4.56+), or timm (v1.0.20+), with code examples for features, depth, detection, and segmentation. You benefit by using these top-performing, dense features without fine-tuning or labels—saving time and compute for tasks like classification, object detection, and zero-shot analysis on your images. https://github.com/facebookresearch/dinov3

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AI & Law

@ai_and_law · Post #763 · 02/12/2026, 08:04 AM

🇪🇺📖ETSI Publishes Baseline AI Security Standards for Europe The European Telecommunications Standards Institute (ETSI) has released baseline cybersecurity standards for organizations implementing AI systems in Europe. The document sets out AI security expectations across the full lifecycle of AI tools, including design, deployment, and operational use. The standards were developed using guidance from the UK National Cyber Security Centre and the Department for Science, Innovation and Technology. They are intended to serve as a common security reference point for AI adoption, establishing minimum expectations for safeguarding AI systems against cyber risks. #AIRegulation#AIGovernance#Cybersecurity#AIStandards#ETSI#TechLaw