LLM Safety, Alignment, and Generalization
Offered By: Simons Institute via YouTube
Course Description
Overview
Explore a comprehensive lecture on the critical aspects of Large Language Model (LLM) safety, alignment, and generalization. Delve into the challenges of ruling out catastrophic harms as LLM capabilities rapidly improve across various domains. Understand the importance of making affirmative safety cases for LLMs and the need to comprehend their motivational structures, especially as they become capable of complex autonomous plans. Examine the necessity for developing a science of LLM generalization to understand how training data influences a model's beliefs and motivations. Learn from Roger Grosse of the University of Toronto as part of the Simons Institute's Special Year on Large Language Models and Transformers: Part 1 Boot Camp.
Syllabus
LLM Safety, Alignment, and Generalization
Taught by
Simons Institute
Related Courses
Introduction to Artificial IntelligenceStanford University via Udacity Natural Language Processing
Columbia University via Coursera Probabilistic Graphical Models 1: Representation
Stanford University via Coursera Computer Vision: The Fundamentals
University of California, Berkeley via Coursera Learning from Data (Introductory Machine Learning course)
California Institute of Technology via Independent