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.
With Project Amelie, we are unveiling our first Foundry autonomous agent that can perform machine learning engineering tasks. ML teams can use the agent to initiate complex machine learning tasks using prompts —such as, “Help…
An evaluation of AI-driven microscopy image analysis suggests reliability issues in single cell analysis. This repository contains code used in our paper, “Representation Learning Methods for Single-Cell Microscopy are Confounded by Background Cells,” to evaluate…
In this work, we investigate automatic design composition from multimodal graphic elements. Although recent studies have developed various generative models for graphic design, they usually face the following limitations: they only focus on certain subtasks…
µProtein is an open-source framework for protein sequence optimization, combining a protein fitness prediction model with reinforcement learning to efficiently explore the mutational landscape. It demonstrates strong generalization across diverse proteins and has been experimentally…
Protein language models (PLMs) pretrained via a masked language modeling objective have proven effective across a range of structure-related tasks, including high-resolution structure prediction. However, it remains unclear to what extent these models factorize protein…
Lost in Conversation is a code repository to facilitate benchmarking LLMs on multi-turn task completion and the reproduction of experiments included in the accompanying paper: “LLMs Get Lost in Multi-Turn Conversation”.
Raha (MetaOpt) uses our open-source heuristic analyzer to quantify the impact of failures on a traffic engineered WAN.
