Multimodal/multimedia transformers models have lots of juice left in them. - The output can be much better with better input (multiple text blocks, images, vid

Multimodal/multimedia transformers models have lots of juice left in them. - The output can be much better with better input (multiple text blocks, images, video, sound and such). - The collective training dataset is much better with labeled/associated video, audio, static images and text. - I suspect previous models can be used to augment human datasets without too much risk of "AI inbreeding." For example, imagine asking an LLM to reword a text page, or a image model generate a variant of an image. Now picture this in a multimedia dataset, with (for instance) a model more accurately labeling video, or producing image variations with associated audio/text as inputs.