The Frontiers of Modeling Atoms with AI
Larry Zitnick (Meta, Inc.)
Distinguished Lecture Series
Thursday, November 14, 2024, 3:30 pm
Abstract
The understanding of our world at the atomic level underlies many global challenges, such as drug discovery and helping mitigate climate change. With the advent of large training datasets and machine learning potentials to model the interaction of atoms, new opportunities are arising. In this talk, I will discuss our latest state-of-the-art AI models and how they are utilized. This includes our latest study in predicting the experimental outcome of a catalyst's performance for renewable fuel synthesis. I will conclude by drawing attention to several remaining open problems in generative AI models, model scalability and experimental validation.
Bio
Larry Zitnick is a research director on the Fundamental AI Research team at Meta. He is currently focused on scientific applications of AI and machine learning, such as the discovery of new catalyst for renewable energy applications. Previously, his research in computer vision covered many areas such as the FastMRI project to speed up the acquisition of MRIs, and the COCO and VQA datasets to benchmark object detection and visual language tasks. He developed the PhotoDNA technology used by Microsoft, Facebook, Google, and various law enforcement agencies to combat illegal imagery on the web. Before joining FAIR, he was a principal researcher at Microsoft Research. He received the PhD degree in robotics from Carnegie Mellon University.
This talk is available for viewing on our YouTube channel.