Definition
Embeddings convert discrete data (words, sentences, images) into continuous vector representations in a high-dimensional space.
Key Properties: - Similar items have similar vectors - Enable mathematical operations on meaning - Typically 384-4096 dimensions
- **Types:**
- Word embeddings: Word2Vec, GloVe
- Sentence embeddings: SBERT, Ada-002
- Image embeddings: CLIP, ResNet features
- Code embeddings: CodeBERT
Applications: - Semantic search - Recommendation systems - Clustering and classification - RAG systems
Popular Models: - OpenAI text-embedding-ada-002 - Cohere embed - Voyage AI - BGE, E5
Examples
Converting "king" and "queen" to vectors where their difference equals the "male-female" direction.
Related Terms
A technique combining information retrieval with text generation to improve accuracy.
Database optimized for storing and searching high-dimensional vector embeddings.
Search that understands meaning and intent, not just keyword matching.
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