Scaling Interpretability

Summary

Science and engineering are inseparable. Our researchers reflect on the close relationship between scientific and engineering ... Eric is a PhD student in the Department of Physics at MIT working with Max Tegmark on improving our scientific/theoretical ... Atticus Geiger from Pr(Ai)²R Group explores “State of Lex Fridman Podcast full episode: youtube.com/watch?v=ugvHCXCOmm4 Thank you for listening ❤ our ... David Bau (Northeastern University) on whether there is a DNA inside cognition, and what scientific infrastructure Take your personal data back with Incogni! Use code WELCHLABS at the link below and get 60% off an annual plan: ... A surprising fact about modern large language models is that nobody really knows how they work internally. At Anthropic, the ... Warning: This is an ad-libbed talk, and I'm sure I got some facts wrong. This is a talk I gave to my MATS 9.0 training program on ... Andrew Mack details a project focused on developing "ambitious mechanistic credibility tools" to improve AI Explaining "Neural Networks are Already Clean" from the ground up. Cline Desktop: cline.gg/desktop-avb and ... In this talk, Mansi discusses her work with How can we reverse engineer what a neural network is doing? In this IASEAI '25 session, An Introduction to Mechanistic ... SITUATION EXPLAINED: Ex-OpenAI researcher Nick Cammarata says we can now understand most neurons inside AI models, ... MIT 6.S897 Machine Learning for Healthcare, Spring 2019 Instructor: Peter Szolovits View the complete course: ...