Computers will transform into effective, personalized, conversational assistants for everybody, including the pre-literate and the non-literate. Commercial chatbots today are notoriously brittle as they are hardcoded to handle a few possible choices of user inputs. Recently introduced large language neural models, such as GPT-3, are remarkably fluent, but they are often erroneous and prone to hallucinations. This course studies how we can tame these neural models into robust, trustworthy, and cost-effective conversational agents across all industries and languages.
Students will learn both the theory and practice with two assignments, and a major open-ended course project of their own design.
Topics include:
👩🏫 Instructor | Monica Lam ( lam at cs )
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👩 CA | Jian Vora ( jianv at cs ) |
👩 CA | Paridhi Maheshwari ( paridhi at cs ) |
🕒 Time | Mon, Wed 3:00-4:20pm |
🏫 Location | Turing Auditorium |
💳 Credits | 3-4 units |
Monica | Wed 4:20pm, Turing Aud |
Paridhi | Tue 11am-12pm, 240-202 |
Jian | Mon 4:20pm, Turing Aud |
Prerequisites: one of LINGUIST 180/280, CS 124, CS 224N, CS 224S, 224U.
Grading is according to the following scheme: