What challenges arise in ensuring scalability of Generative AI for multi-modal datasets

Question

Can i know What challenges arise in ensuring scalability of Generative AI for multi-modal datasets?

Answer 1

Scalability challenges in Generative AI for multi-modal datasets include handling large volumes of diverse data, managing computational complexity, and ensuring efficient training across different modalities (e.g., text, images, audio). 

Here is the code snippet showing how it is done:

In the above code, we are using the following key points:

• Multi-modal Dataset: Handles a dataset with both text and image data (e.g., COCO dataset).
• CLIP Model: Utilizes the CLIP model for processing and understanding multi-modal inputs.
• Batch Processing: Efficiently processes large datasets in batches for scalability.

Hence, ensuring scalability in multi-modal Generative AI requires efficient handling of complex data formats, model optimization, and batch processing to manage large datasets and minimize computational overhead.