Here in Multimodal data scenarios, like involve image, audio, vedio case, i am thinking whether users will store these kinds of multimodal data into deeplake, or just storage directly in disk like S3?

Hoping have a disscuss for this to enhance understanding in multimodal data scenarios.

Possible Usages of Multimodal data

Before consider how Multimodal data will be stored, here we should consider how will these kinds of data will be used later, here i thought may exist this kinds of usage:

• Convert images, text, audio, etc., into embedding vectors to facilitate downstream retrieval and analysis. Here may store embedding vectors into deeplake.
• Tagging images and videos.
• feed image or video to model, here include read image or frame of video and convert to normalized Tensor and as input for model.

How will or should Multimodal data be stored ?

Currently, here in mind, it seems save metadata and path of Multimodal data is more common, like following table data:

• Thus here i want to know is there some case that user will tends to store Multimodal data like image or video into deeplake directly instead of remote disk like S3?

Hoping you share you ideas and insight @activesoull @artgish @zaaram @tatevikh @khustup @dgaloop