Media coverage

Nathan has been involved in many media outlets covering the rapid progress of AI. He's been on old school outlets NPR and involved in many outlets including The Verge, Business Insider, Fortune, and more! This same work has also been featured highly on Hacker News and Techmeme.

[2023] Berkeley Low-cost Interplanetary Solar Sail

Some fun work on small space craft! This was featured in The Register.

[Fall 2022 - 2023] Reinforcement learning from human feedback

My work and research on RLHF has been referenced in many popular media sources.

[2022] Reward Reports for Reinforcement Learning

Our call for new forms of ML documentation is growing.

[Fall 2021] Choices, Risks, and Reward Reports: Charting Public Policy for Reinforcement Learning Systems

This paper has been covered in a few newsletters as we begin to publicize this growing line of work.
  • ChinAI by Jeffry Ding "Must Read"
  • ImportAI by Jack Clark "Why we need public policy for powerful reinforcement learning systems"

Podcast appearances

For my AI podcast, The Retort, click here. Podcasts where I can access the recordings are embedded directly below!

Generating Conversation, September 2023

Discussing changing tides in RLHF and LLM evaluation! Plus, checking in on my Berkeley roots.

Latent Space, July 2023

Discussing the launch and implications of the Llama 2 LLM release.

Practically Intelligent, July 2023

Discussing evaluation and growth of open-source large language models.

TalkRL Podcast, March 2021

This episode is a great introduction to my research in a casual format. Though, it does get technical at times, so feel free to reach out with questions. Additionally, the TalkRL podcast is a great resource for connecting with ideas from other emerging researchers.

Software Engineering Daily, January 2021

This episode discusses a lot of content of interest to my blog, with a less technical coverage of my research. It is more on the bigger picture of why robotics and why RL (maybe deep).