Transformers Enable Multimodal Models

Transformers can combine text, images, and other modalities for integrated reasoning.

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🤯 Did You Know (click to read)

CLIP can associate unseen images and text without task-specific training for each new concept.

Models like CLIP and VisualBERT encode both visual and textual data using attention layers. By learning cross-modal relationships, these models perform tasks such as image captioning, visual question answering, and cross-modal retrieval efficiently.

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💥 Impact (click to read)

Multimodal Transformers expand AI capabilities, allowing richer human-computer interaction and understanding of combined sensory data.

Researchers can develop applications integrating vision and language, enabling improved accessibility, education, and creative tools.

Source

Radford et al., 2021 - CLIP

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