Definition
Multimodal AI
Multimodal AI can process or generate more than one type of data, such as text, images, audio, video or code.
Short definition
Multimodal AI works across multiple data types. A model might read text and images together, answer questions about a chart, describe a video frame or generate an image from written instructions.
How it works
Multimodal systems combine representations from different modalities. The model needs a way to align image patches, audio segments or video frames with language so it can reason across them.
Example
A user can upload a screenshot of an analytics dashboard and ask the model to explain the trend, identify anomalies and suggest follow-up questions. The system uses both visual understanding and language generation.
Why it matters
Many real-world tasks are not text-only. Multimodal AI is important for design, accessibility, robotics, document processing, education and visual analysis. It also raises new safety questions because images and videos can be manipulated or misunderstood.