ilya-sutskever-recommended-reading

This Deep Learning textbook by Ian Goodfellow is a good intro to the fundamentals: https://www.deeplearningbook.org/ It does require some math, but has an appendix with a refresher. Then, read through this list from Ilya Sutskevar: https://github.com/dzyim/ilya-sutskever-recommended-reading Be patient. It might take a couple of years to get up to speed. :)

In the thread about John Carmack presentation, somebody mentioned the reading list he got from Ilya which were crucial to understand what matters and the current state of the knowledge (at the time). After some googling, it seems like this list is plausible, although not confirmed: https://github.com/dzyim/ilya-sutskever-recommended-reading?tab=readme-ov-file What would an actualized list look today ? I'm asking since I'm taking a similar direction to Carmack (with maybe 1% of his talent and skills, but hey it's all about the journey !) in that I don't intend to work on improvement existing models, which I also believe are a road to nowhere, but rather understand things from the ground up, and maybe figure out 'something different' at the end.