Embeddings
Embeddings are dense vector representations of text, images, or other data in a high-dimensional space. Similar content maps to nearby vectors, enabling semantic search and similarity calculations.
Why it exists
- •LLMs don't know your private data
- •LLMs hallucinate confidently
- •Embeddings bridges AI + real knowledge
Used in
What is Embeddings?
Embeddings are like a secret code that turns words and ideas into numbers. Similar things get similar numbers, so the computer can understand what's related!
👶 For Beginners
Embeddings are like a secret code that turns words and ideas into numbers. Similar things get similar numbers, so the computer can understand what's related!
👨💻 For Developers
Embeddings are dense vector representations of text, images, or other data in a high-dimensional space. Similar content maps to nearby vectors, enabling semantic search and similarity calculations.
🚀 For Founders
Embeddings enable semantic search, recommendation systems, and AI that understands meaning beyond keywords. Essential for building intelligent search and discovery features.