A course light on math, heavy on practical applications, complexities, and ethics involved in the shifting LLM landscape. Non-majors are welcome and encouraged to enroll!
Taught by: Meica Magnani and Felix Muzny
Pre-requisites: None!
We don't need to tell you that LLMs (ChatGPT, Claude, etc.) are everywhere and will continue to be everywhere. This class is basically "learn how LLMs actually work and think about what is happening in the world as a result of them existing". Also, we're not going to do a lot of math, and no coding will be required or expected. First year and first semester students are welcome :).
Covers the internal components of large language models (LLMs), the data and technological systems necessary to build and deploy them, and the real-world applications, effects, and lines of philosophical inquiry around these models. Key concepts include computational knowledge representation, data and scale, computing infrastructure, opportunities and limitations posed by such models, and key threads of ethical inquiry surrounding them. Students will learn the history of LLMs as situated in the history of computing and automatic translation technologies. Students will study the practical capabilities and limitations of these models, explore the various contexts in which they are currently deployed, and explore the technological, societal, and environmental impacts of these technologies. This course does not teach students to program, nor does it expect students to program.
We'll be actively working together every time we meet, be it on projects, discussions, debates, or other activities. We'll have realitively few students, which means that we can have really exciting discussions!
(topics, to be adjusted as the world evolves)
Looking for more information? Stay tuned and also feel free to reach out to us!
