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Modern AI systems such as LLMs are pervasive and helpful, but do they really have the social intelligence to seamlessly and safely engage in interactions with humans? In this talk, I will delve into the limits of social intelligence of LLMs and how we can measure and anticipate their risks.

In this talk, we delve into the evolution of low-rank optimization techniques for Large Language Models (LLMs), highlighting the journey from GaLore, to Q-GaLore and WeLore.

SCI is pleased to welcome a new chair of the Department of Computer Science (CS), Adriana Kovashka! 

Senior computer science Student Griffin J. Hurt has been named a 2024 Graduate Research Fellowship Program (GRFP) scholar. 

In this talk, we will discuss the evolution of this theorem and the surprising developments of the 1980s that led to the concept of the geometric phase. We will use simple models to demonstrate how QAC is applied in applications. Additionally, we will explore how the discovery of geometric phases has led to the idea of quantum holonomic computing.

In this talk, I will present our recent research on creating AI systems that can learn to understand our multimodal world with minimal human supervision. I will focus on systems that can understand images and text, and also touch upon those that utilize video, audio, and lidar.