Artificial Intelligence
Pursuing computing advances to create intelligent machines that complement human reasoning to augment and enrich our experience and competencies.
Dataset Source Code
Code Release for Reprompting: Automated Chain-of-Thought Prompt Inference Through Gibbs Sampling
We introduce Reprompting, an iterative sampling algorithm that automatically learns the Chain-of-Thought (CoT) recipes for a given task without human intervention. Through Gibbs sampling, Reprompting infers the CoT recipes that work consistently well for a…
Publication
Chain-of-Model Learning for Language Model
Dataset Source Code
fLSA: Learning Semantic Structures in Document Collections Using Foundation Models
Humans can learn to solve new tasks by inducing high-level strategies from example solutions to similar problems and then adapting these strategies to solve unseen problems. Can we use large language models to induce such…
Video
MIT Technology Review’s EmTech Conference: What’s Next?
The future of AI is full of untapped opportunities that lie just beyond the horizon. In this session, we’ll peer into the crystal ball of AI’s next 1-3 years, uncovering emerging trends, hidden opportunities, and…
Podcast
Coauthor roundtable: Reflecting on real world of doctors, developers, patients, and policymakers
Peter Lee and his coauthors, Carey Goldberg and Dr. Zak Kohane, reflect on how generative AI is unfolding in real-world healthcare, drawing on earlier guest conversations to examine what’s working, what’s not, and what questions…
Publication