Stephen Bach

Stephen Bach

Title: Applied Research Scientist
Company: Brown University
Bio

Stephen Bach is an assistant professor of computer science at Brown University. Previously, he was a visiting scholar at Google, and a postdoctoral scholar in the computer science department at Stanford University advised by Christopher Ré.

He received his Ph.D. in computer science from the University of Maryland, where he was advised by Lise Getoor. 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. 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.

The latest from
Stephen Bach

Large language model training: how three training phases shape LLMs

Training large language models is a multi-layered stack of processes, each with its unique role and contribution to the model’s performance.

February 27, 2024

Better not bigger: How to get GPT-3 quality at 0.1% the cost

We created Data-centric Foundation Model Development to bridge the gaps between foundation models and enterprise AI. New Snorkel Flow capabilities (Foundation Model Fine-tuning, Warm Start, and Prompt Builder) give data science and machine learning teams the tools they need to effectively put foundation models (FMs) to use for performance-critical enterprise use cases. The need is clear: despite undeniable excitement about…

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