Glossary
What is Multimodal AI?
AI that processes text, images, audio, and video together.
What is multimodal AI?
Multimodal AI can process and generate multiple types of data—text, images, audio, and video—in a unified model. Examples include GPT-5, Gemini, Claude 4, and Llama 4, which can understand images and generate text about them.
Multimodal Capabilities
- Vision: Understand and describe images
- Audio: Transcribe and understand speech
- Video: Analyze video content
- Generation: Create images, audio from text
Multimodal Models (2025)
- GPT-5: Text, image, audio input/output
- Gemini 3: Native multimodal with video
- Claude 4: Vision and document understanding
- Llama 4: Native text, image, video, audio
Monitoring Multimodal AI
Unique challenges for multimodal monitoring:
- Visual hallucinations—describing things not in images
- Object misidentification
- Inappropriate image descriptions
- Cross-modal consistency
Do multimodal models need different monitoring?
Yes. Multimodal models can hallucinate about image content, misidentify objects, or generate inappropriate descriptions. Monitor both text outputs and visual understanding accuracy.
Monitor multimodal AI outputs
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