Pre-training datasets significantly affect the cultural relevance of Generative AI by determining the cultural context and bias embedded in the model. Here are the key points you can consider:
- Cultural Bias: Datasets from specific cultures may introduce biases and limit the AI's ability to generate culturally diverse content.
- Data Diversity: A diverse pre-training dataset with representation from multiple cultures enables the model to generate more culturally relevant and inclusive outputs.
- Contextual Understanding: Training on culturally relevant data helps the model understand specific nuances, customs, and expressions.
Here is the code snippet you can refer to:

In the above code, we have the following to consider:
- Cultural Representation: Ensure pre-training data reflects diverse cultures to avoid biases.
- Fine-Tuning: Fine-tune the model on culturally specific data to improve relevance for targeted regions or communities.
Hence, By curating a diverse and inclusive pre-training dataset, you can enhance the cultural relevance of generative AI models.