Why Contrastive Learning Is the Core Foundation of Visual Language Models
The article explains how contrastive learning replaces fixed‑category visual training with a relationship‑based approach, detailing the dual‑encoder architecture, cosine similarity loss, batch scaling, temperature control, zero‑shot capabilities, scalability from web data, and the method's strengths and limitations in modern multimodal AI.
