Eiichiro Kazumori (collaboration/inputs with UMass Dartmouth students)
(Source: https://phdcomics.com/comics.php?f=1583)
The bottom line of the state university is education and community. Given the crucial significance of education in the age of AI, it is critical to ensure this bottom line. Nevertheless, students, instructors, and the university currently spend a significant amount of time inefficiently on issues other than actual teaching and learning. Students need to spend significant time learning about student life, academic resources, technical issues, and campus information by looking at the university webpage, which is not necessarily easy to navigate. Often, students get lost before asking for help. At the same time, instructors and the university repeatedly spend a significant amount of time answering similar questions from students each semester. The UMass Dartmouth Large Language Model Helper automates the process to reduce inefficiencies, helping students get answers quickly so that students, instructors, and the university can refocus on education and community.
One use case is a student wanting to learn about the University of Massachusetts Dartmouth. A student may type the question, ‘Tell me about the University of Massachusetts Dartmouth.’ The chatbot will then provide an answer.
Further use cases (not implemented yet): (1) Students, instructors, and staff can check whether a facility is open without calling the facility. (2) Students can access course information from the syllabus without contacting instructors each time. (3) Students need not contact instructors and staff for tech support. (4) Students can learn class offerings that fit their needs and preferences. (5) Students can receive initial health support without going to the health center. (6). Students can obtain community contacts.
The project will help students, instructors, and the university refocus on education and community, which is the bottom line of the state university.
At this moment, Kazumori is managing the project with limited resources. Thus we cannot offfer continuous high-quality service. The output may not be satisfactory at this stage only due to the lack of resources.
This is a proof of concept version. The code has not undergone testing, verification, fine-tuning, and RLHF. This is not a production deployment. It is highly recommended to thoroughly verify the output before proceeding with any actual use.
Kazumori would like to thank the students who participated in the initial discussions that inspired this project when he discussed the generative TA project. Kazumori did all the work on his own. The current presentation of the project is preliminary, ongoing, and is subject to further revision.
The current version takes some time to return the answer. Please be patient.
