Inspired by this comment on lw: https://www.lesswrong.com/posts/yS9LJDKjZ6oJXN9WC/which-ml-skills-are-useful-for-finding-a-new-ais-research#bS5jwD2tCw97gGuyu
I might start with something from this list, but open to suggestions. Only interested in pushing AI notkillingeveryoneism not capabilites.

• Balestriero’s spline theory of deep learning (2018) and the geometry of deep networks (2019)

• Olah et al.’s theory of circuits (2020)

• Roberts, Yaida, and Hanin’s deep learning theory (2021)

• Vanchurin’s theory of machine learning (2021)

• Anthropic’s mathematical framework for transformers (2021)

• Boyd, Crutchfield, and Gu’s theory of thermodynamic machine learning (2022)

• Marciano’s theory of DNNs as a semi-classical limit of topological quantum NNs (2022)

• Bahri et al.’s review of statistical mechanics of deep learning (2022)

• Alfarra et al.’s tropical geometry perspective on decision boundaries of NNs (2022)