Seminars

View all Seminars  |  Download ICal for this event

Probabilistic Hash Functions and Hash Tables: A New Paradigm for Efficient AI Training and Inference

Series: Department Seminar

Speaker: Prof. Anshumali Srivastava Associate Professor Department of Computer Science Rice University

Date/Time: Jan 05 16:00:00

Location: CSA Seminar Hall (Room No. 254, First Floor)

Abstract:
Neural Scaling Law informally states that an increase in model size and data automatically improves AI. However, we have reached a point where the growth has reached a tipping end where the cost and energy associated with AI are becoming prohibitive.

This talk will demonstrate the algorithmic progress that can exponentially reduce the compute and memory cost of training and inference with neural networks. We will show how data structures can fundamentally break the barriers of some of the classical adaptive sampling subroutines. In particular, randomized hash tables can be used to design an efficient

Speaker Bio:
Anshumali Shrivastava is an associate professor in the computer science department at Rice University. He is also the Founder and CEO of ThirdAI Corp, a company that is democratizing AI to commodity hardware through software innovations. His broad research interests include probabilistic algorithms for resource-frugal deep learning. In 2018, Science news named him one of the Top-10 scientists under 40 to watch. He is a recipient of the National Science Foundation CAREER Award, a Young Investigator Award from the Air Force Office of Scientific Research, a machine learning research award from Amazon, and a Data Science Research Award from Adobe. He has won numerous paper awards, including Best Paper Award at NIPS 2014, MLSys 2022, and Most Reproducible Paper Award at SIGMOD 2019. His work on efficient machine learning technologies on CPUs has been covered by popular press including Wall Street Journal, New York Times, TechCrunch, NDTV, Engadget, Ars technica, etc.

Host Faculty: Dr. Arindam Khan