Hugging Face Blog
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3 hours ago
DharmaOCR, a Portuguese-language optical character recognition model, outperformed newer competitors Mistral OCR4 and Unlimited-OCR on a Brazilian Portuguese benchmark through domain-specific training rather than architectural superiority. DharmaOCR scored 0.925 on the Portuguese benchmark while Mistral OCR4 scored 0.798 and Unlimited-OCR scored 0.7587. The specialized model's advantage persists because concentrating all parameters on a single language outperforms distributing them across multiple languages, even as general OCR architectures improve.
Meta AI Blog
Meta released SAM 3.1, an updated version of its Segment Anything Model that processes video object tracking more efficiently through a technique called object multiplexing. The model doubles processing speed from 16 to 32 frames per second on a single H100 GPU by tracking up to 16 objects in a single forward pass instead of processing each object separately. This enables real-time object tracking in complex videos while reducing GPU resource requirements, making the technology feasible on smaller hardware.
Meta AI Blog
Alta Daily, a fashion app launched in 2025, uses Meta's Segment Anything Model to digitize users' wardrobes and recommend outfit combinations from photos. The app has processed more than 20 million images using SAM, reducing costs compared to external segmentation APIs that charged several cents per image. Users can now photograph their clothes and receive personalized outfit recommendations displayed on their digital avatar while tracking daily wear to avoid repetition.
Meta AI Blog
Meta and the World Resources Institute released Canopy Height Maps v2, an open-source model that uses satellite imagery to measure forest structure globally for conservation and land management. The model's accuracy metric (R²) improved from 0.53 to 0.86, and it was built using Meta's DINOv3 vision model trained on 493 million satellite images. Governments and organizations in the UK, EU, and US cities are already using the maps to monitor forests, track tree-planting commitments, and plan urban cooling interventions.
