I've been eager to go deeper into areas at the intersection of representation theory and learning for quite some time. In particular, I plan to let this paper on quiver representations and neural networks provide me with an initial orientation. I learned about quiver representations in a graduate linear algebra class that I took in 2021, but I haven't thought about them since exploring more of the learning literature. Next, I plan to spend a few weeks exploring Erik Bekker's work as well as others' work from this conference workshop. I'll fixate (as usual) on a set of ideas from a paper that seems particularly full of salient ideas.