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 or CV
Talks → See Library
Newsletter → Interconnects.ai
Book → RLHF Book
Recent: I've launched a post-training course for my RLHF Book that is coming to print in a couple of months. In April I had the pleasure of visiting a lot of open model labs in China; read my trip report here.
Podcast appearances
I host Interconnects Interviews covering the latest technical trends in AI. Otherwise, I sometimes appear on friends' podcasts:
- Feb. 2026: Lex Fridman - My second time on Lex's podcast, covering everything in AI!
- Feb. 2026: Turing Post - Conversation on open models, reasoning systems, and where AI is headed.
- Jan. 2026: ChinaTalk - Overfit: Claude Code is Everything, Trump Vibe Codes.
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
- Contact - Get in touch with me.
- Bookshelf - Books I've read and recommend.
- Buy me a ☕️ - Support my work.
- The Retort - Retired podcast on the political economy of AI.
- Semantic Scholar · PhD Thesis