Nathan is a machine learning researcher who works on building, understanding, and advocating for open language models and other responsible autonomous systems. He is currently a post-training lead at the Allen Institute for AI.
Papers → Google Scholar, my CV, Semantic Scholar, see PhD Thesis.
Talks → YouTube channel or CV.
Newsletter → Interconnects.ai
Book → RLHF Book
Recent: Building American Truly Open Models (ATOM Project - atomproject.ai), finished the web version of my RLHF book, coming to print soon!
Upcoming: The Curve (Oct 3-5), COLM (Oct 6-10), PyTorch Conference (Oct 21-24), NeurIPS (Dec 10-15)
Podcast appearances
I host two podcasts (sporadically).
- Interconnects Interviews cover the latest technical trends in AI.
- (On hold) The Retort covers the political economy and stakes of AI.
Otherwise, I sometimes appear on friends' podcasts:
- Aug. 2025: Lawfare's "Scaling Laws" - The Open Questions Surrounding Open Source AI.
- Aug. 2025: Nonzero (The Wright Show) - The Open Source AI Question.
- Jul. 2025: Latent Space - The RLVR Revolution.
Guides
Some useful links for graduate students and academics.
- How to Review a Paper - My process for writing thorough paper reviews.
- Applying to Graduate School - Advice for prospective graduate students.
Popular Posts
Some of my most popular posts before transitioning to Substack (Top Posts there).
- Job Search as a PhD in ML - My experience on the AI job market.
- AI Research Job Market (Part 2) - Follow-up thoughts on the job market.
- Debugging Model-Based RL Systems - Practical debugging strategies.
Other
- Office Hours - I (sometimes) hold regular office hours through the ML Collective.
- Contact - Get in touch with me.
- Bookshelf - Books I've read and recommend.
- Buy me a ☕️ - Support my work.
- RLHF Book - My upcoming book on reinforcement learning from human feedback.