
In this tutorial, we build an end-to-end 3D medical image segmentation pipeline using MONAI to segment the spleen on the Medical Segmentation Decathlon Task09 dataset. We work with volumetric CT scans, apply medical imaging transformations such as orientation alignment, voxel-spacing normalization, intensity windowing, foreground cropping, and patch-based sampling, and then train a 3D UNet model for binary organ segmentation. We also use mixed precision training, DiceCE loss, sliding-window inf
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Today, Mistral AI released OCR 4, its latest document-understanding model. This new release adds bounding boxes, block classification, and inline confidence scores alongside extracted text. It supports 170 languages across 10 language groups and runs in a single container for fully self-hosted deployments. OCR 4 also serves as an ingestion component for enterprise search, RAG, and domain-specific retrieval pipelines. TL;DR OCR 4 returns bounding boxes, typed-block labels, and per-word c

Datalab has released lift, a 9B open-weights vision model for structured extraction. You pass it a JSON schema, and it returns a JSON object that matches. The model reads PDFs and images directly, then decodes against your schema. This is Datalab’s first model built purely for extraction. The team already ships open-source OCR tools: chandra, marker, and surya. lift extends that work into schema-driven field extraction. lift scores 90.2% field accuracy on Datalab’s 225-documen

Mistral OCR 4 delivers enterprise document AI with 170-language support, bounding boxes, and self-hosted deployment.
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