SAM 3 is Meta’s next-generation segmentation model that shifts from geometric, prompt-based segmentation to concept-level understanding through Promptable Concept Segmentation, enabling open-vocabulary instance detection via text or visual exemplars.

This article provides a comprehensive guide to fine-tuning PaliGemma - Google's new Visual Language Model (VLM) - for tasks such as image captioning, object detection, and segmentation, addressing specific challenges and potential solutions for optimizing performance and ensuring reliable outputs.