This repository compiles a list of foundational deep learning papers that Ilya Sutskever allegedly recommended to John Carmack, claiming mastery of these materials covers 90% of what matters in the field. The list includes landmark papers on transformers, LSTM networks, RNN regularization, ImageNet classification, and sequence-to-sequence models, each linked to blogs, PDFs, or code implementations.