Experiential Reinforcement Learning
By Taiwei Shi, Sihao Chen, Longqi Yang, Jaime Teevan Reinforcement Learning is at the core of building and improving frontier AI models and products. Yet most state-of-the-art RL methods learn primarily from outcomes: a scalar reward signal that says whether…
Media Authenticity Methods in Practice: Capabilities, Limitations, and Directions
| Eric Horvitz, Andrew Jenks, and Jessica Young
As synthetic media grows, verifying what’s real, and the origin of content, matters more than ever. Our latest report explores media integrity and authentication methods, their limits, and practical paths toward trustworthy provenance across images, audio, and video.
Project Silica’s advances in glass storage technology
| Richard Black
Project Silica introduces new techniques for encoding data in borosilicate glass, as described in the journal Nature. These advances lower media cost and simplify writing and reading systems while supporting 10,000-year data preservation.
In the news | Nature
Laser writing in glass for dense, fast and efficient archival data storage
Long-term preservation of digital information is vital for safeguarding the knowledge of humanity for future generations. Existing archival storage solutions, such as magnetic tapes and hard disk drives, suffer from limited media lifespans that render them unsuitable for long-term data…
In the news | National Academy of Engineering
Doug Burger elected to National Academy of Engineering
Academy membership honors individuals who have made outstanding contributions to engineering research, practice, or education. Burger was elected for accelerating cloud-scale computing and networking infrastructures with field-programmable systems.
From One to Many
By Jaime Teevan, Chief Scientist & Technical Fellow In recent years we’ve all lived through the transition to cloud computing, a sudden shift to remote work, and now the rapid rise of AI. Each individually has felt like a seismic…
In the news | New benchmarks and models for low-resource languages, medical and brain foundation models, AI in space, and innovation kits
“Cognitive Load Estimation Using Brain Foundation Models and Interpretability for BCIs” paper featured in MSR Research Focus Channel
The paper "Cognitive Load Estimation Using Brain Foundation Models and Interpretability for BCIs", accepted for publication during ICASSP 2026, with authors Deeksha M Shama, Dimitra Emmanouilidou, Ivan Tashev, is featured in the MSR Research Focus Channel.
Rethinking imitation learning with Predictive Inverse Dynamics Models
| Pallavi Choudhury, Lukas Schäfer, Chris Lovett, Katja Hofmann, and Sergio Valcarcel Macua
This research looks at why Predictive Inverse Dynamics Models often outperform standard Behavior Cloning in imitation learning. By using simple predictions of what happens next, PIDMs reduce ambiguity and learn from far fewer demonstrations.
Paza: Introducing automatic speech recognition benchmarks and models for low resource languages
| Mercy Muchai, Kevin Chege, Nick Mumero, and Stephanie Nyairo
Microsoft Research unveils Paza, a human-centered speech pipeline, and PazaBench, the first leaderboard for low-resource languages. It covers 39 African languages and 52 models and is tested with communities in real settings.