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Multimodal learning
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<p>Multimodal learning is a type of <a href="/facts/Deep_learning/JLuwD3ea">deep learning</a> that integrates and processes multiple types of data, referred to as <a href="/facts/Modality_(human%25E2%2580%2593computer_interaction)/KzL4uqMm">modalities</a>, such as text, audio, images, or video. This integration allows for a more holistic understanding of complex data, improving model performance in tasks like visual question answering, cross-modal retrieval, text-to-image generation, aesthetic ranking, and image captioning. </p><p>Large multimodal models, such as <a href="/facts/Google_Gemini/Kwfa4rMW">Google Gemini</a> and <a href="/facts/GPT-4o/6WnEYHRa">GPT-4o</a>, have become increasingly popular since 2023, enabling increased versatility and a broader understanding of real-world phenomena. </p>