Is this a new finding? I'm not an expert on the deeper mathematical side of ML, but I remember a friend of mine already telling me about something that sounded exactly like this (ca. 2016-17).
The fact that kernel machines can approximate other models isn't new. I think the novel idea is that they have explicitly constructed the "translation" between the arbitrary model to the kernel machine, and it's quite clean.
