Definition
Contrastive Language-Image Pre-training (CLIP) is a dual-encoder architecture that maps images and text into a shared latent vector space, enabling semantic cross-modal retrieval. In RAG pipelines, it facilitates Multi-modal RAG by allowing agents to retrieve visual data using natural language queries, though it trades off fine-grained spatial reasoning for broad semantic alignment.
An embedding model for vision-language alignment, not a tool for cropping or 'clipping' video files.
"A Universal Rosetta Stone that maps a photo of a mountain and the written word 'altitude' to the exact same coordinate on a high-dimensional map."
- Multi-modal RAG(Application Context)
- Vector Embedding(Prerequisite)
- Contrastive Learning(Underlying Mechanism)
- Zero-shot Learning(Capability)
Conceptual Overview
Contrastive Language-Image Pre-training (CLIP) is a dual-encoder architecture that maps images and text into a shared latent vector space, enabling semantic cross-modal retrieval. In RAG pipelines, it facilitates Multi-modal RAG by allowing agents to retrieve visual data using natural language queries, though it trades off fine-grained spatial reasoning for broad semantic alignment.
Disambiguation
An embedding model for vision-language alignment, not a tool for cropping or 'clipping' video files.
Visual Analog
A Universal Rosetta Stone that maps a photo of a mountain and the written word 'altitude' to the exact same coordinate on a high-dimensional map.