Two speakers:

Len Kahn, Chair of Physics, URI – Hear how we are preparing for quantum computing at URI

Stephen Bach, Computer Science, Brown University:

It’s All About Data: The Promises and Limitations of Recent Developments in AI 

Talk Abstract: This talk will overview the evolution of AI over the last five years, through the lens of machine learning and large language models. Accessible to scientists with a general computing background, we will discuss the key technical developments that have enabled recent advances. Many of them are data-centric, meaning that the development of datasets has been at least as important as advances in model architectures and algorithms. The centrality of data means that further AI advances are also limited by data, particularly in specialized domains requiring subject matter expertise. I will discuss these challenges and share some of our lab’s recent work on overcoming them.

Bio: Stephen Bach is an assistant professor of computer science at Brown University. His research focuses on weakly supervised, zero-shot, and few-shot machine learning. The goal of his work is to create methods and systems that drive down the labor cost of AI. He was a core contributor to the Snorkel framework, which was recognized with a Best of VLDB 2018 award. Snorkel is used in production at numerous Fortune 500 companies for programmatic training data curation. He also co-led the team that developed the T0 family of large language models. The team was also one of the proposers of instruction tuning, which is the process of fine-tuning language models with supervised training to follow instructions. Instruction tuning is now a standard part of training large language models. Stephen is also an advisor to Snorkel AI, a company that provides software and services for data-centric AI.

Nov 22nd 12pm Galanti Lounge (Library)