A multimodal AI can process and generate multiple data types: text, images, audio, video. Models like GPT-4V, Gemini, and Claude 3 are multimodal.
What is Multimodal AI?
Multimodal AI is an artificial intelligence system capable of understanding and generating multiple content types (modalities): text, images, audio, video, and sometimes code or structured data.
Multimodal AI Examples
- GPT-4V (Vision): Image analysis + text generation
- Gemini: Text, images, audio, video natively
- Claude 3: Image and document analysis
- DALL-E 3: Image generation from text
Multimodal Capabilities
| Modality | Input | Output |
|---|---|---|
| Text | ✅ All | ✅ All |
| Image | ✅ GPT-4V, Gemini, Claude 3 | ✅ DALL-E, Midjourney |
| Audio | ✅ Whisper, Gemini | ✅ ElevenLabs |
| Video | ✅ Gemini | ✅ Sora, Runway |
Impact on visibility
Multimodal AI changes the visibility game:
- Optimized images: Alt text, captions, context
- Transcribed videos: Subtitles, descriptions
- Infographics: Text extracted and indexed
- PDFs and documents: Content analyzed directly
Optimizing for Multimodal AI
- Add descriptive alt text to all images
- Transcribe audio and video content
- Use high-quality images with context
- Create infographics with readable text