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CLIP is a multimodal AI model developed by OpenAI that uses contrastive learning to create meaningful embeddings for both images and text. Trained on 400 million image-text pairs, it employs separate embedding models for text (Transformer-based) and images (ResNet or Vision Transformer) to learn representations where similar content is closer in embedding space. The model excels at zero-shot tasks like image classification and OCR for simple text, achieving performance comparable to supervised baselines. While CLIP struggles with abstract tasks like object counting, it offers versatile applications in similarity search, RAG systems, and multimodal understanding tasks.

CLIP Model Overview : Unlocking the Power of Multimodal AI