Artificial Intelligence
Building intelligent machines that complement human reasoning and extend what people can do.
Event
Mathematical foundations of AI workshop
The workshop on the mathematical foundations of AI, hosted by Microsoft Research Cambridge, brings together researchers from academia and industry to explore emerging directions and open challenges.
Event
Advancing the science of AI agent evaluation and governance
On October 22–23, 2026, Microsoft Research and Carnegie Mellon University’s AI Measurement Science & Engineering Center (AIMSEC) will convene 120 key leaders across academia, industry, civil society, and government to define shared standards and measurement science for evaluating and governing…
Project
debug-gym: A Text-Based Environment for Interactive Debugging
A Text-Based Environment for Interactive Debugging In most existing approaches (shown in black), an agent rewrites its code conditioned on error messages obtained from executing its code. debug-gym equips the agent with additional tools such…
Project
T A L E S
the Text Adventure Learning Environment Suite Reasoning is an essential skill to enable Large Language Models (LLMs) to interact with the world. As tasks become more complex, they demand increasingly sophisticated and diverse reasoning capabilities…
Video
Scalable Training of Diffusion Samplers via Fixed-point Score Matching
This talk explores recent advancements in neural sampling using diffusion models. I will begin by highlighting the shortcomings of prior methods and explaining how recent approaches, inspired by the success of data-driven paradigms, overcome these…
Video
AI World Models for Memory, Meaning, and Human Futures
Interactive world models are emerging as a new design material, enabling people to become creators by transforming their personal data into explorable visual worlds. Moving beyond traditional world-model applications in gaming, robotics, and autonomous-driving simulations,…
Microsoft Research Blog
Simulating student learning for better AI tutoring
StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like…
