Generative Models AAA: Acceleration, Application, Adversary

Abstract: In this talk, we will delve into the dynamic and evolving landscape of generative AI, concentrating on three areas: the acceleration of foundation models for extensive context lengths, the implications of such accelerations in teaching these models the intricate 'language of the brain', and the critical issue of their susceptibility to adversarial threats. 

Speaker Bio: Amin Karbasi is currently an associate professor of Electrical Engineering, Computer Science, and Statistics & Data Science at Yale University. He is also a staff scientist at Google NY. He has been the recipient of the National Science Foundation (NSF) Career Award, Office of Naval Research (ONR) Young Investigator Award, Air Force Office of Scientific Research (AFOSR) Young Investigator Award, DARPA Young Faculty Award, National Academy of Engineering Grainger Award, Amazon Research Award, Nokia Bell-Labs Award, Google Faculty Research Award, Microsoft Azure Research Award, Simons Research Fellowship, and ETH Research Fellowship. His work has also been recognized with a number of paper awards, including Graphs in Biomedical Image Analysis (GRAIL), Medical Image Computing and Computer Assisted Interventions Conference (MICCAI), International Conference on Artificial Intelligence and Statistics (AISTATS), IEEE ComSoc Data Storage, International Conference on Acoustics, Speech, and Signal Processing (ICASSP), ACM SIGMETRICS, and IEEE International Symposium on Information Theory (ISIT). His Ph.D. thesis received the Patrick Denantes Memorial Prize from the School of Computer and Communication Sciences at EPFL, Switzerland.