AI Glossaryfundamentals

Multimodal AI

AI models that can process and generate multiple types of data: text, images, audio, video, and code.

How It Works

Modern AI models are increasingly multimodal. GPT-5.2 handles text, images, and audio. Gemini 3.0 processes text, images, audio, and video. Claude Opus 4.6 handles text and images. Multimodal capabilities enable: analyzing screenshots for bugs, transcribing and summarizing meetings, generating images from descriptions, and understanding video content. Building multimodal apps requires handling different input/output formats and choosing the right model for each modality.

Common Use Cases

  • 1Image analysis and generation
  • 2Video understanding
  • 3Voice assistants
  • 4Document OCR and analysis

Related Terms

Large Language Model (LLM)

A neural network trained on massive text datasets that can generate, understand, and reason about human language.

Computer Vision

The field of AI that enables machines to interpret and understand visual information from images and video.

Text-to-Speech (TTS)

AI technology that converts written text into natural-sounding spoken audio, enabling voice interfaces and audio content generation.

Need help implementing Multimodal AI?

AI 4U Labs builds production AI apps in 2-4 weeks. We use Multimodal AI in real products every day.

Let's Talk