Nathan Lambert is a Senior Research Scientist and Post-Training Lead at the Allen Institute for AI (Ai2), where he leads open-source language model development on the OLMo and Tulu series. A UC Berkeley PhD, he previously led the RLHF team at Hugging Face, co-building the TRL library and the Zephyr model. He runs Interconnects AI, a Substack newsletter read by tens of thousands covering post-training, open models, and AI policy, and is the author of The RLHF Book (Manning Publications). With roughly 8,000 academic citations and a reputation for demystifying the hardest parts of modern AI, Lambert is one of the most trusted voices at the intersection of open-source AI research and public education.
Ryan Selkis is the co-founder and former CEO of Messari, the leading crypto intelligence and research platform. Known by his pseudonym 'Two Bit Idiot,' he broke the news of the Mt. Gox hack in 2014 that shook the crypto world, helped build CoinDesk and the Digital Currency Group, and spent six years publishing Messari's annual 'Crypto Theses' - the most widely read forecasting reports in the industry. He stepped down as Messari CEO in July 2024 amid political controversy, but remains an advisor and one of crypto's most influential voices.
Elvis Saravia is the co-founder and lead AI researcher at DAIR.AI, a mission-driven organization democratizing AI research and education worldwide. Based in Belize, he is the author of the Prompt Engineering Guide - one of the most widely read AI resources on the internet with 73,000+ GitHub stars and over 3 million learners - and publishes the AI Agents Weekly newsletter. A PhD graduate from National Tsing Hua University in Taiwan, he has contributed to landmark AI projects including the Galactica large language model at Meta AI, and is known for bridging rigorous research with accessible, production-minded education for the next generation of AI builders.
Eugene Yan is a Principal Applied Scientist turned Member of Technical Staff at Anthropic, where he bridges cutting-edge AI research with production-scale systems. Formerly at Amazon for five years building real-time recommendation and LLM-powered systems for Kindle and Search, Eugene is equally well-known for his prolific writing: 209 blog posts, 420,000+ words published, and a newsletter with over 11,800 subscribers. His open-source repository applied-ml on GitHub has become a canonical reference for teams shipping machine learning in production. He lives in Seattle, snowboards on weekends, and writes like someone who actually wants you to understand.
Osman Ali Mian is an early-career AI researcher specializing in causal discovery and trustworthy machine learning. He completed his PhD magna cum laude at CISPA Helmholtz Center for Information Security (Saarland University, Germany) and is now a postdoctoral researcher at the Institute for Artificial Intelligence in Medicine (IKIM) in Essen. He has published at top-tier venues including AAAI, ICML, AISTATS, and KDD, and won an Outstanding Paper Award at AAAI 2026 — marking him as a rising star in causal ML.
Yao Fu (符尧) is an AI researcher at xAI specializing in large language model reasoning, efficient inference, and distributed systems. A PhD graduate of the University of Edinburgh, he previously worked at Google DeepMind on Gemini 3 and Project Astra. With over 5,000 citations and key papers like ServerlessLLM (OSDI '24) and DuoAttention (ICLR '25), Fu bridges systems engineering and ML research. He writes the 'Yao Fu' newsletter on Notion and is known for the Chain-of-Thought Hub benchmark repository, which helped track LLM reasoning progress across the field.