AI4BIO Seminar with Professor Eric Xing, Mohamed Bin Zayed University of Artificial Intelligence скачать в хорошем качестве

AI4BIO Seminar with Professor Eric Xing, Mohamed Bin Zayed University of Artificial Intelligence

AI4BIO Seminar featuring Professor Eric Xing, President of Mohamed Bin Zayed University of Artificial Intelligence and Professor, Machine Learning Department, Language Technology Institute & Computer Science Department in Carnegie Mellon University on December 2, 2024. "Toward AI-Driven Digital Organism: Multiscale Foundation Models for Predicting, Simulating, and Programming Biology at All Levels" Hosted by: Jian Ma, Ray and Stephanie Lane Professor of Computational Biology Abstract: At the core of medicine, pharmacy, public health, longevity, agriculture, food security, environmental protection, and clean energy, it is biology at work. Biology systems in the physical world is too complex to manipulate and always expensive and risky to temper with; and first-principle-based methods based on laws of physics and chemistry scale poorly to offer predictive and actionable understanding of biology. In this talk, I present a vision of using AI to model and simulate biology and life. I will layout an engineering viable approach to construct an AI-Driven Digital Organism (AIDO), leveraging self-supervised pretraining and adaption of large-scale foundation models, and I introduce some early results including 5 SOTA foundation models for DNA, RNA, Protein, Structure, and Single Cell, respectively, and their abilities to tackle biological problems at the full spectrum of granularities, from sequence, to structure, to network, to phenotype, to diseases, and to drug responses. Based on these early results, I posit that an AIDO can be built in a modular and connectable way to reflect biological scales, complexities, and connectedness, and open a safer and affordable alternative platform to Predicting, Simulating, and Programming Biology at All Levels. I envision that AIDO is poised to trigger a new wave of low cost high-throughput biological designs, interventions, and experimentation through artificial life resulting from generative AI, eventually can help to decode life in a close loop collaboration with better-guided wet-lab experimentation and better informed first-principle reasoning. About Eric Xing: Professor Eric Xing is the President of the Mohamed bin Zayed University of Artificial Intelligence, and a Professor of Computer Science at Carnegie Mellon University. His main research interests are the development of machine learning and statistical methodology, and large-scale distributed computational systems and architectures, for solving problems involving automated learning, reasoning, and decision-making in artificial, biological, and social systems. In recent years, he has been focusing on building large language models, world models, agent models, and foundation models for biology. Prof. Xing has served on the editorial boards of several leading journals including JASA, AOAS, JMLR; was a recipient of several awards including NSF Career, Sloan, Carnegie Science Award, and best papers in conferences such as ACL, NeurIPS, OSDI, and ISMB; and is a fellow of several societies including AAAI, ACM, ASA, IEEE, and IMS. This seminar is brought to you by The Center for AI-Driven Biomedical Research (AI4BIO) in Carnegie Mellon University. More information at cmu.edu/ai4bio.