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Concepts →Multimodal AI
AI systems that process or generate more than one type of data, such as text, images, audio, or video.
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Multimodal AI combines multiple data modalities in one model or system. A multimodal system may understand an image and answer a text question, generate an image from text, reason over audio, or combine several input types in one workflow.
How it works
Architectures vary. Some systems map different modalities into shared representations, while others use specialized encoders connected to a language model or a unified generative architecture. Alignment between modalities is a central training challenge.
Why it matters
Multimodal systems broaden the range of real-world tasks AI can handle, but they also expand evaluation and safety requirements because failures can arise from interactions between modalities rather than text alone.
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