Yes, handling data redundancy in AI-generated marketing content requires deduplication techniques, diversity-promoting loss functions, and contrastive learning. Here is the code snippet you can refer to:

In the above code, we are using the following key points:
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Uses sentence embeddings to identify semantically redundant content. 
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Computes cosine similarity scores to detect duplicates. 
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Filters out repetitive marketing text while ensuring diversity. 
Hence, AI-generated marketing content remains diverse and engaging by applying deduplication and semantic filtering techniques.