CSCI 178 - Understanding Large Language Models

Large language models (LLMs) are both hyped and hated but rarely understood. This course begins with a careful introduction to probability, machine learning, and the workings of LLMs. Then we turn our attention to a range of philosophical and social questions posed by their rise. Do they actually think? How can they be “aligned” with human values? What broader impacts will LLMs have on jobs, education, and society? These questions have led to interesting work in both the sciences and the humanities, and this course will attempt an interdisciplinary dialogue that spans these fields.

Unit(s): 1
Group Distribution Requirement(s): Distribution Group III
Instructional Method: Lecture-conference
Grading Mode: Letter grading (A-F)
Cross-listing(s): PHIL 278
Group Distribution Learning Outcome(s):

Use and evaluate quantitative data or modeling, or use logical/mathematical reasoning to evaluate, test or prove statements.
Given a problem or question, formulate a hypothesis or conjecture, and design an experiment, collect data, or use mathematical reasoning to test or validate it.