Multimodal
AI systems that can process and generate multiple types of content—text, images, audio, and video.
Definition
Multimodal AI can understand and generate multiple types of media within a single system. Rather than separate models for text, images, and audio, multimodal models process these formats together, understanding relationships between them.
This enables AI to analyze images and discuss them, generate images from text descriptions, or transcribe and summarize audio content.
Why It Matters
Real-world information comes in many formats. Multimodal AI can handle the full spectrum—analyzing a product photo while reading its description, or understanding a video presentation with slides and speech.
Multimodal capabilities dramatically expand what AI can assist with, from creative projects to complex analysis.
Examples in Practice
A multimodal model analyzes a room photo and suggests furniture arrangements in both text descriptions and generated images.
Customer support uses multimodal AI to understand product issue photos and generate illustrated repair instructions.
A marketing team uploads campaign mockups for multimodal analysis of visual design, copy effectiveness, and brand consistency.