Embeddings are numerical vectors that capture semantic meaning, enabling similarity search, clustering, and retrieval workflows.

Related AI terms: CLIP and Textual Inversion.

A Vector Database is optimized for indexing and querying high-dimensional vectors, commonly used for RAG and semantic search.

Grounding is the practice of constraining generation with verifiable sources so outputs are accurate, attributable, and context-specific.

Fine-tuning is supervised model adaptation on curated examples so behavior aligns more closely with domain-specific tasks.

Related AI terms: DreamBooth and Subject-Driven Generation.

Multimodal AI combines understanding and generation across different modalities, enabling richer interfaces and cross-media reasoning.

ControlNet augments diffusion generation with explicit structural conditions such as edges, depth, or pose. It improves control in Diffusion Model systems and often uses cues from Image Segmentation.