The best Large Language Models newsletters

Long-form technical articles on machine learning and AI research, covering new model releases, architectures and the history behind them. Issues include in-depth explainers, literature reviews and video lectures with transcripts.

Deep (Learning) Focus is a long-form newsletter by Cameron R. Wolfe that explains important AI research topics in depth, with recent issues covering agent evaluation, NVIDIA Nemotron post-training, and reinforcement learning for LLMs. Readers get structured, reference-style overviews that synthesize research and practical implementation details.

A weekly digest of recent AI research papers with a focus on large language models, pairing a news roundup with structured breakdowns of key papers. Each paper is explained by the problem it addresses, the method, and the results.

A weekly show and newsletter recapping the past week's AI news, covering model releases, open source, and lab announcements, with a rotating panel of experts and guest interviews. Each issue includes commentary, panel discussion, and a links roundup.

A daily-style AI newsletter that filters model launches, agent tools and industry news down to what matters for practical work, with short items on each development. It pairs headline coverage with sponsored business AI offers and occasional light historical framing.

A newsletter rounding up the latest news, model releases, repos, demos, and papers in large language models and machine learning. Issues are mostly collections of embedded posts from X with short headline lists of topics.