Comprehensive technical guide to VLM evaluation and fine-tuning, covering key metrics (BLEU, METEOR, CIDEr, SPICE, BERTScore, CLIPScore, VQA Accuracy, ANLS) and core loss functions (cross-entropy, contrastive, focal, KL divergence, DPO). Includes mathematical formulations, step-by-step worked examples, and practical code snippets for implementation.

Our annual data-driven analysis of how enterprises are actually deploying computer vision in 2026 - covering the five dominant deployment patterns, sample ROI numbers by vertical, technology choices between YOLO26 and RF-DETR, edge vs cloud splits, and the no-code vs custom engineering debate.

Learn how to finetune NVIDIA's Cosmos-Reason2 vision-language model on Datature Vi to bring chain-of-thought reasoning to physical AI applications like warehouse automation, enabling robots to not just detect objects but reason about safety, spatial relationships, and physical interactions.