The words you're looking for are: "transfer learning".

Currently, dedicated robotics datasets are pathetic - in both the raw size and domain diversity - compared to what we have for generative AIs in domains like text, sound, video or images. So adding any more data helps a lot.

If you trained a robot to fully strip down a specific e-scooter model - whether for repair, remanufacturing or recycling - that training data would then help with any similar tasks. As well as a variety of seemingly unrelated tasks that also require manual dexterity, manipulation and spatial reasoning.

Those "9999 specializations" all overlap in obvious and subtle ways - and they feed little bits of skills and adaptations to each other. Which is why a lot of the robotic companies are itching to start pushing the units out there as soon as they are able to perform some useful tasks. They want that real world training data.