We saw this happen with Stable Diffusion and it's not surprising we see this happening here. There is a lot of interest in taking these models that are in striking distance (single order of magnitude) from running inference and training on consumer level hardware and as such a lot of energy is going into making the optimizations that can get us there.
Generally speaking, research is not usually done with consumer usage in mind, so what this is, and Dreambooth etc. for Stable Diffusion was, is that gap between researcher software and accessible software being bridged.
So many parts across the stack need to work well for this to go well. Early support for popular software is a good example. This goes from partnerships all the way down to hardware designers.
I'd argue it's not about engineering more than it is about good organizational structure.
The bangle.js:
- ships significantly faster
- has an always-on display with similar 4 week maximum battery life
- can be updated without flashing
- has a thriving app ecosystem
It must be trivial to use one of these approaches to generate a removable background and render the background with something else, like a static image, video, or 3d software