CIS Grace Hopper Distinguished Lecture: “OLMo: Accelerating the Science of Language Modeling”
October 24 at 3:30 PM - 4:30 PM
Language models (LMs) have become ubiquitous in both AI research and commercial product offerings. As their commercial importance has surged, the most powerful models have become closed off, gated behind proprietary interfaces, with important details of their training data, architectures, and development undisclosed. Given the significance of these details in scientifically studying these models, including their biases and potential risks, I argue that it is essential for the research community to have access to powerful, truly open LMs. In this talk, I present our OLMo project aimed at building strong language models and making them fully accessible to researchers along with open-source code for data, training, and inference. I describe our efforts in building language modeling from scratch, expanding their scope to make them applicable and useful for real-world applications, and investigating a new generation of LMs that address fundamental challenges inherent in current models.
Hanna Hajishirzi
Torode Family Associate Professor, Allen School of Computer Science and Engineering, University of Washington and a Senior Director of NLP at AI2.
Hanna Hajishirzi is the Torode Family Associate Professor in the Allen School of Computer Science and Engineering at the University of Washington and a Senior Director of NLP at AI2.
Her current research delves into various domains within Natural Language Processing (NLP) and Artificial Intelligence (AI), with a particular emphasis on accelerating the science of language modeling, broadening their scope, and enhancing their applicability and usefulness for human lives. She has published over 140 scientific articles in prestigious journals and conferences across ML, AI, NLP, and Computer Vision. She is the recipient of numerous awards, including the Sloan Fellowship, NSF CAREER Award, Intel Rising Star Award, Allen Distinguished Investigator Award, Academic Achievement UIUC Alumni Award, and Innovator of the Year Award by GeekWire. The work from her lab has been nominated for or has received best paper awards at various conferences and has been featured in numerous magazines and newspapers.