I had an idea a long time ago that would allow us to make “soft AGI” by making models into “nodes” that would have an input and output representations and routing them to achieve the task needed.

Basically a “marketplace” of models that would have the metadata to be easily searchable and standardized types/representations that would allow them to link seamlessly. We could then build a system that would get a text query and phone sensors as input and would determine input-output representations for the query. The system would then find a route (ideally using the most cost-efficient path, nodes being rated with a compute cost) to achieve the task.

Is Google trying to make this with MediaPipe?

I think once it is ou of beta they will open a repository for our “Calculators” (as they call nodes) to make this happen. They could maybe provide cheap or free execution on Google Cloud but use the data passing through as training material. The thing is we could make models more modular and reuse pretrained nodes already on the system. It would make training really fast as most of the model is already pretrained and avoid overfitting because the nodes are used for other tasks as well.

What do you think of it?