Media Summary: MIT 6.S897 Machine Learning for Healthcare, Spring 2019 Instructor: Peter Szolovits View the complete course: ... How can we reverse engineer what a neural network is doing? In this IASEAI ' Zeta transform, Möbius inversion, streaming algorithms, necessity of randomization and approximation, distinct elements.
Lecture 25 Interpretability - Detailed Analysis & Overview
MIT 6.S897 Machine Learning for Healthcare, Spring 2019 Instructor: Peter Szolovits View the complete course: ... How can we reverse engineer what a neural network is doing? In this IASEAI ' Zeta transform, Möbius inversion, streaming algorithms, necessity of randomization and approximation, distinct elements. How can we use the language of causality to understand and edit the internal mechanisms of AI models? Atticus Geiger ... May 13, 2025 Large language models do many things, and it's not clear from black-box interactions how they do them. We will ... Intelligent Analysis of Biomedical Images Winter 2023 Lecture 25
This is a talk I gave to my MATS 9.0 training scholars about the big picture of mech interp - as of Oct 2025, what had changed? This talk was recorded at NDC AI in Oslo, Norway. Attend the next NDC ... Visit our sponsor 80000 hours - grab their free career guide and check out their podcast! Use our ... Deep neural network models have been extremely successful for natural language processing (NLP) applications in recent years, ... What's happening inside an AI model as it thinks? Why are AI models sycophantic, and why do they hallucinate? Are AI models ...
