Recent books include Bishop & Bishop, Deep Learning: Foundations and Concepts, Simon Prince, Understanding Deep Learning, Zhang et al, Dive into Deep Learning, and Jurafsky and Martin, Speech and Language Processing, 3rd ed. These all have free previews online, and Zhang et al. provides Jupyter notebooks for most sections using PyTorch and other frameworks.
Andrej Karpathy has released a one-hour intro to LLMs as well as a multi-part Zero to Hero series building a language model from the ground up. Grant Sanderson (3Blue1Brown) made an extraordinary visual introduction to neural networks and transformers. Many of Jeremy Howard's videos are also very good.
Here is daturkel's list of landmark learning papers. Another list of deep learning papers up to 2017, and another. Recent papers on arxiv. Sebastian Raschka's noteworthy AI research papers of 2023 and 2022.
Rich Sutton, The Bitter Lesson. Compare Rodney Brooks, A Better Lesson.
Bender et al., On the Dangers of Stochastic Parrots.