Embeddings and similarity

Many AI systems represent information as vectors. Embeddings capture meaning numerically, allowing programs to compare, retrieve, and rank items by similarity.

• Representing data as vectors — Encoding text or data as numeric vectors.
• Computing similarity — Measuring distance or closeness between vectors.
• Retrieval and ranking — Selecting and ordering items by similarity score.