AI engineering glossary · Generative media multimodal
What is multimodal embedding?
Multimodal embedding: A vector representation in which text, images, audio or other inputs are mapped into one shared space so that semantically related items are close regardless of modality. It enables cross-modal search and zero-shot classification.
Multimodal embedding: an example
The embedding of a photo of a tiger lies near the embedding of the text 'a tiger', but far from 'a teacup'.
Related terms
More Generative media multimodal terms
- Multimodal model
- Negative prompt
- Neural audio codec
- Neural radiance field
- Neural vocoder
- Noise schedule
- Normalizing flow
- Object hallucination
Where you learn it
Multimodal embedding is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.