Join University Libraries for an engaging panel discussion where we delve in and learn about the impacts of artificial intelligence on the 2024 US elections! Panelists are Paige Lord, Tom Costello, and Musa al-Gharbi. The discussion will be moderated by Library Dean, Karim Boughida. Co-sponsored by the Office of Diversity, Inclusion, and Intercultural Initiatives.

Please RSVP for Democracy in the Digital Age: AI's Influence on 2024 Elections here.
Learn how these two AI tools will help you this year. AI has been all over, but figuring out the tools that we may use is critical. Background remover of images and a replacement for Google Search may disrupt the industry this year. Learn and refresh your knowledge about these tools.
IACS and the Dept of Ecology and Evolution invite you to a PRODiG+ Fellowship Seminar.

Computational Approaches to Understanding and Forecasting Biodiversity Responses to Global Change

Summary: Advancing biodiversity forecasting requires developing computational approaches that better represent ecological complexity. In this talk, I will discuss how my research integrates field observations, predictive modeling, machine learning, and spatiotemporally explicit environmental data to develop more mechanistic and reliable forecasting tools.

Speaker: Dr. Anna Thonis, a postdoctoral researcher in NYU's Winchell Lab and Founder and Co-Chair of the IUCN SSC Anoline Lizard Specialist Group, studies how anthropogenic change reshapes the distributions of reptiles. Combining field and quantitative modeling methods, her work focuses on the ecology and conservation of Puerto Rican and urban Anolis lizards. Her website can be accessed here.

Location: IACS Seminar Room, and via Zoom.

Zoom: https://stonybrook.zoom.us/j/97023584426?pwd=HrnrYeYJfVUhaS8iOKjWF3Tbh8HYS1.1&jst=2
ID: 97023584426
Passcode: 241762

Launching a University-Wide AI Innovation Institute:

Last spring, the Office of the Provost led a group of over 30 faculty, staff, and administrators to consider how we can expand and leverage our strengths in AI research and discovery. The resulting recommendation was to launch a university-wide AI Innovation Institute (AI3), which would expand the Institute for AI-driven Discovery and Innovation established in 2018 from a department-level institute within the College of Engineering and Applied Science (CEAS) to the university-wide AI Innovation Institute reporting to the provost.

As a university-wide enterprise, the AI Innovation Institute (AI3) is intended to accelerate, coordinate, and organize AI innovation and education across Stony Brook. The institute will serve to empower the entire university community and beyond, catalyzing core AI research, curriculum innovation, and societal change in the ever-evolving landscape of knowledge work.

The AI Town Hall, led by AI3 Interim Director Skiena, is an open house event that will provide an overview of the major AI initiatives on campus, including the new AI Seed Grant program and Stony Brook's role in New York State's Empire AI program. The session will include time for questions and discussion about the future of AI at Stony Brook.

Abstract: Large language models are prone to memorizing some of their training data. Memorized (and possibly sensitive) samples can then be extracted at generation time by adversarial or benign users. There is hope that model alignment---a standard training process that tunes a model to harmlessly follow user instructions---would mitigate the risk of extraction. However, we develop two novel attacks that undo a language model's alignment and recover thousands of training examples from popular proprietary aligned models such as OpenAI's ChatGPT. Our work highlights the limitations of existing safeguards to prevent training data leakage in production language models.

Speaker: Pegah Alipoormolabashi

Location: CS2311
Abstract: Theory-internal work on opacity in phonology has been focused on the challenges these interactions present for one theory (rules, constraints) versus another. But there has also been interest in studying the formal, invariant properties of opaque and other process interactions (Chandlee et al. 2018; Bakovic and Blumenfeld 2024), though these works crucially differ in their underlying assumptions. In this talk I will recontextualize Chandlee et al. (2018)'s result that opaque maps are ISL in light of Bakovic and Blumenfeld (2024)'s recent formal typology of process interactions, and this recontextualization will provide an answer to an open question about the k-value of an interaction map. I will then discuss the implications of this collective formal understanding of opacity for a recent model of lexicon and phonological grammar learning (i.e., Hua and Jardine 2021, Chandlee and Jardine to appear).


Speaker: Prof. Jane Chandlee, Associate Professor in the Department of Linguistics at Haverford College

Location: IACS Seminar room.

Learn how to use AI Studio to build mini-agents that could handle repetitive tasks, save your time, and keep yourself organized.

In this workshop, you will understand the basics of the platform and trigger real-time notifications for emails or calendar events. This will give you the basis for you to create your own.

Register to attend.

University Libraries Presents: Do you want more control over when to use AI features in your Google apps and when browsing online? Are you tired of Gmail trying to finish your sentences for you? Drop in to this brief tutorial, which will walk through the settings you can turn on and off in various Google products to keep your agency where you want it.

Register here for the Zoom session.