Instruction: Discuss strategies for optimizing multimodal AI models to run efficiently on edge devices with limited computing resources.
Context: This question evaluates the candidate's expertise in deploying AI models on edge devices, including techniques for model compression, quantization, and efficient data handling across different modalities.
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The way I'd think about it is this: On edge devices, I would aggressively simplify the multimodal pipeline. That may mean smaller encoders, compressed representations, selective activation of expensive modalities, and splitting some work between the device and the cloud...