At the beginning of the week, I wrote a full first draft of a section for a paper formalizing the kinds of experiments that we’re running. It needs a bit of work—I run the risk of overformalizing aspects of our experimentation, and we also need to do some more literature review to understand whether or not aspects of our approach go by other names in other fields of machine learning—but it was a useful start.
I also got the codebase running on my new Framework Desktop with a PR adapting CUDA (Nvidia) hardware acceleration to ROCM, the analogous software that allows GPUs to process machine learning tasks on AMD. This was pleasantly straightforward, as hardware acceleration in Python has come a long way since I was last messing with it in 2018/19. I’m really excited about this project, as I hope it will be a real contribution to machine learning interpretation from a more humanistically-centered place.