Artificial Intelligence (AI)

Consulting: Supercharge Your Research with Hugging Face’s Toolkit

October 1, 2024
Iñigo Parra
Supercharge Your Research with Hugging Face’s Toolkit

Are you looking to elevate your research projects with cutting-edge machine learning models? Hugging Face might be just the tool you need. This platform makes it easy to access and implement state-of-the-art models, bringing efficiency and innovation to your work like never before.

Hugging Face is highly user-friendly, even for those new to Python or machine learning. It hosts thousands of models, offering diverse tools from natural language processing and computer...

AI Ethics in Action: UC Berkeley’s Data Science for Social Justice Workshop

August 28, 2024, 5:00pm
Claudia von Vacano, Ph.D., Founding Executive Director of D-Lab, introduces the Data Science for Social Justice Workshop, highlighting its goals, structure, and outcomes. Three students who have participated in the workshop present lightning talks on their experience with DSSJ, highlighting their personal journeys, the projects they worked on, and what they gained from the workshop.

Conceptual Mirrors: Reflecting on LLMs' Interpretations of Ideas

April 23, 2024
María Martín López
by María Martín López. As large language models begin to engrain themselves in our daily lives we must leverage cognitive psychology to explore the understanding that these algorithms have of our world and the people they interact with. LLMs give us new insights into how conceptual representations are formed given the limitations of data modalities they have access to. Is language enough for these models to conceptualize the world? If so, what conceptualizations do they have of us?

Computational Social Science in a Social World: Challenges and Opportunities

March 26, 2024
José Aveldanes
by José Aveldanes. The rise of AI, Machine Learning, and Data Science are harbingers of the need for a significant shift in social science research. Computational Social Science enables us to go beyond traditional methods such as Ordinary Least Squares, which face challenges in addressing complexities of social phenomena, particularly in modeling nonlinear relationships and managing high-dimensionality data. This paradigmatic shift requires that we embrace these new tools to understand social life and necessitates understanding methodological and ethical challenges, including bias and representation. The integration of these technologies into social science research calls for a collaborative approach among social scientists, technologists, and policymakers to navigate the associated risk and possibilities of these new tools.

Dive into the Future of AI with the LLM Working Group at D-Lab

February 7, 2024
Tom van Nuenen, Ph.D.
by Tom van Nuenen, Celebrating 10 years of innovation in data-intensive social science, D-Lab in collaboration with Grad Div is excited to introduce the LLM Working Group, an initiative focused on the exploration and discussion of Large Language Models (LLMs) like ChatGPT within academic research and teaching. This group aims to unite scholars, students, and data scientists to address crucial questions about AI's role in academia, including access, impact, creativity, and learning in the age of information automation. Through a series of interactive sessions, participants will gain insights into LLM capabilities, discuss ethical considerations, and explore innovative approaches to utilizing these tools in their work. Whether you're an AI veteran or a novice curious about the potentials of GenAI, the LLM Working Group offers a collaborative platform to learn, share, and shape the future of academic inquiry. Join us in navigating the world of LLMs together.