Instruction: Explain techniques to handle the scenario where one or more modalities are missing during inference in a multimodal AI system.
Context: This question probes the candidate's ability to design robust multimodal AI systems that can still function effectively even when some modalities are unavailable, emphasizing redundancy and fault tolerance.
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The way I'd think about it is this: I mitigate modality dropout by training the system to survive partial input availability instead of assuming every modality is always present. That usually means modality dropout during training, robust fusion...