Discover an index of datasets, SDKs, APIs and open-source tools developed by Microsoft researchers and shared with the global academic community below. These experimental technologies—available through Azure AI Foundry Labs (opens in new tab)—offer a glimpse into the future of AI innovation.
Open Source fuels the AI for Good Lab’s mission by providing research tools, data, and code that drive innovation, foster collaboration, and enhance accessibility for the global community. Explore our full library of resources to…
This repository hosts the official code and data artifact for the “Affective Air Quality” dataset. Details about the user study and data collection can be found in our paper. The dataset released it’s the first to…
The absolute trainer to light up AI agents. We present Agent Lightning, a flexible and extensible framework that enables seamless agent optimization for any existing agent framework.
AI Behavioral Science for Anthropomorphic Agents: toward human‑centric, symbiotic, and autonomous AI. This project centers on evaluating and promoting anthropomorphic intelligence—AI agents with a human-like mindset and a degree of awareness, capable of acting proactively…
TRELLIS is a large 3D asset generation model that creates high-quality 3D assets from simple text or image inputs. Using a unified latent space (SLAT), it delivers detailed, textured 3D models in formats like meshes,…
MatterSim is a deep learning model for accurate and efficient materials simulation and property prediction over a broad range of elements, temperatures and pressures to enable in silico materials design.
This repository contains all scripts for re-producing the results of our paper “Lost in Transmission: When and Why LLMs Fail to Reason Globally”.
ExACT is an approach for teaching AI agents to explore more effectively, enabling them to intelligently navigate their environments, gather valuable information, evaluate options, and identify optimal decision-making and planning strategies.
