[danielbln]

I mean, there is a somewhat unique value proposition of a multimodal framework like this meta transfirmer. Its goal isn't necessarily to beat expert models in their own game, but to provide a unified framework for processing diverse modalities of data.

I think it aims to leverage the cross-modal relationships and unified learning, which might not be possible with expert models designed for only a single modality.

Even if it performs slightly worse on some tasks, the ability to handle multiple modalities within a single framework is an pretty sweet advantage in scenarios where data from various sources need to be processed simultaneously, and patterns across modalities need to be captured somehow.

A general-purpose model could also be a more cost-effective solution in some cases, ensemble experts are difficult to scale and parallelize.