MIT-IBM Watson AI Lab: Overview and Project Highlights

 Abstract:

The MIT-IBM Watson AI Lab, a joint academic-industry research initiative, advances AI through foundational and applied work, emphasizing AI science for real-world impact. This talk outlines the Lab's mission, impact, and project portfolio before highlighting work from several Lab projects that focus on methods to efficiently enhance large language models (LLMs). This includes (1) disentangling knowledge from skills via synthetic data, enabling targeted skill integration; (2) training LLMs to self-report uncertainty for reliability; (3) creating a modular library of intrinsic capabilities as low-rank adapters (LoRAs) for parameter-efficient customization; and (4) scalable serving infrastructure for dynamic multi-adapter deployment. Together, these approaches enable efficient injection of specialized skills into LLMs while preserving core functionality and reducing computational costs. The discussion highlights their potential to democratize advanced AI capabilities and accelerate deployment across domains, exemplifying the Lab’s commitment to AI science for real-world impact.

Speaker Bio:

Kenney Ng is a Principal Research Scientist at IBM Research Cambridge and the Science Program Manager for the MIT-IBM Watson AI Lab. Previously, he was Senior Manager of the Center for Computational Health and Principal Investigator on "AI for Healthcare" research collaborations with the Broad Institute, Massachusetts General Hospital, Cleveland Clinic, and JDRF. Before IBM Research, he was a Senior Software Engineer and Architect in IBM Software Group. Prior to IBM, he was a principal software engineer at iPhrase Technologies and held research positions at the MIT Laboratory for Computer Science, BBN Technologies, and MIT Lincoln Laboratory. His current research focus is on the development and application of data mining, machine learning, and AI techniques to analyze, model and derive actionable insights from real world data. His prior research areas include information retrieval, speech recognition, probabilistic modeling, topic modeling, and natural language processing. Kenney has Bachelors, Masters, and Ph.D. degrees in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology. He is a Fellow of the American Medical Informatics Association (AMIA) and a Senior member of IEEE. He is a co-author on over 100 scientific publications and a co-inventor on over 25 patents.