Design a Cross-lingual and Multimodal AI System for Global Content Understanding

Design an AI system capable of understanding and analyzing content across multiple languages and modalities (text, images, video, audio) for applications like global content moderation, cross-cultural marketing, and multilingual information retrieval. Focus on implementing cross-lingual representation learning, multimodal fusion techniques, and transfer learning for low-resource languages. Address challenges like aligning representations across languages and modalities, handling cultural nuances and context, scaling to hundreds of languages, and providing real-time analysis for large volumes of global content.

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