LLM Working Group

Hybrid: D-Lab Collaboratory, 356 Social Sciences Building or Zoom

The LLM Working Group is a community founded to facilitate conversations about Large Language Models (LLMs) and Generative AI within academia. This 4-part series will provide fundamental knowledge of LLMs, and generate conversation about the promises and challenges of LLMs in different facets of academic work. In the second session, Teaching with LLMs, Kimberly Vinall, Emily Hellmich, Genevieve Smith, and Ben Spanbock will lead a dialogue on the potential of LLMs in reshaping educational landscapes. It discusses educational challenges such as AI literacy, academic integrity, biases, hallucinations, and privacy issues, as well as opportunities such as accessibility and democratization. Questions we will be addressing include: How can we cultivate openness in class about students using LLMs and GenAI? Will LLMs fundamentally alter the importance of remembering knowledge and learning? Are LLMs fundamentally different from other information technologies like Wikipedia? How to cultivate openness in class about students using LLMs and GenAI? LLM working Group sessions will be interactive, encouraging participants to share their experiences, pose questions, and collaboratively explore the challenges and potential of these technologies in their respective fields. Please send in your questions ahead of time for priority consideration – you can use this Google Form to let us know what’s on your mind. We review all submitted questions but may need to shorten, consolidate, or clarify them for discussion. We encourage everyone to participate, regardless of their experience level with LLMs and GenAI. The LLM Working Group is a welcoming and supportive community for all. This is a hybrid event. In-person seating is limited to 35.

LLM Working Group

Hybrid: D-Lab Collaboratory, 356 Social Sciences Building or Zoom

The LLM Working Group is a community founded to facilitate conversations about Large Language Models (LLMs) and Generative AI within academia. This 4-part series will provide fundamental knowledge of LLMs, and generate conversation about the promises and challenges of LLMs in different facets of academic work. In the second session, Teaching with LLMs, Kimberly Vinall, Emily Hellmich, Genevieve Smith, and Ben Spanbock will lead a dialogue on the potential of LLMs in reshaping educational landscapes. It discusses educational challenges such as AI literacy, academic integrity, biases, hallucinations, and privacy issues, as well as opportunities such as accessibility and democratization. Questions we will be addressing include: How can we cultivate openness in class about students using LLMs and GenAI? Will LLMs fundamentally alter the importance of remembering knowledge and learning? Are LLMs fundamentally different from other information technologies like Wikipedia? How to cultivate openness in class about students using LLMs and GenAI? LLM working Group sessions will be interactive, encouraging participants to share their experiences, pose questions, and collaboratively explore the challenges and potential of these technologies in their respective fields. Please send in your questions ahead of time for priority consideration – you can use this Google Form to let us know what’s on your mind. We review all submitted questions but may need to shorten, consolidate, or clarify them for discussion. We encourage everyone to participate, regardless of their experience level with LLMs and GenAI. The LLM Working Group is a welcoming and supportive community for all. This is a hybrid event. In-person seating is limited to 35.

2024 Gabriel E. Gallardo Research Symposium

The Office for Graduate Diversity's Diversity and Community Fellows will be tabling at the Gabriel E. Gallardo Symposium Grad Fair on Monday, April 22, 2024, in-person at the University of Washington. Stop by to learn more about the graduate student experience at UC Berkeley, receive information about our graduate programs, and get added to our mailing list for more information and resources for all!