Aurora 1.5: Extending open foundation models for weather and Earth-system applications
Aurora 1.5 adds 22 more variables, hourly temporal resolution, and probabilistic ensemble forecasting to the Aurora foundation model, making it more useful for real-world weather, climate, and energy applications.
The post Aurora 1.5: Extending open foundation models for weather and Earth-system app...
Short chart specifications are easy to write, but often produce uninspiring results. Flint is an open-source visualization language that offers a middle path, letting AI agents create expressive charts from compact, human-editable specifications.
The post Flint: A visualization language for the AI e...
AI agents often fail because their instructions, or skills, are manually modified with no guarantee of improvement. Learn how SkillOpt turns skill editing into a training process, making agent behavior more reliable without changing model weights.
The post SkillOpt: Agent skills as trainable paramet...
Memora: A Harmonic Memory Representation Balancing Abstraction and Specificity
AI agents can't remember past conversations. They must constantly reload or retrieve context, which grows less efficient as tasks get longer and more complex. Memora solves this with a scalable memory system separating what’s stored from how it's retrieved.
The post Memora: A Harmonic Memory Represe...
Understanding the brain with AI-driven explanations and experiments
Researchers introduce generative causal testing, which translates black box models into clear hypotheses and verifies them in the scanner, revealing what specific brain regions respond to in language.
The post Understanding the brain with AI-driven explanations and experiments appeared first on Micr...
Talos: Scaling rare disease diagnosis with automated, iterative genomic reanalysis
Talos was built to help resolve a major bottleneck in genomic medicine: human review time. The open-source system recovered 90% of in-scope diagnoses while surfacing just 1.3 candidate variants per patient for expert review.
The post Talos: Scaling rare disease diagnosis with automated, iterative g...
Project Ire examined a timely malware sample and determined its intent through reverse engineering—identifying LOTUSLITE characteristics even as most major EDR tools did not detect it.
The post Ire identifies another LOTUSLITE specimen appeared first on Microsoft Research.
Data Formulator 0.7: AI-powered data analytics for enterprise data
Data Formulator introduces AI-powered analytics for enterprise data workflows. Data teams can easily bring enterprise data into an AI-ready workspace where users can explore, analyze, and visualize data with AI agents to turn raw data into actionable insights.
The post Data Formulator 0.7: AI-powere...
Understanding AI as an extension of human intelligence—not a replacement for it—offers a more grounded path for building trustworthy AI systems.
The post Extending Human Intelligence Through AI appeared first on Microsoft Research.
MagenticLite, MagenticBrain, Fara1.5: An agentic experience optimized for small models
MagenticLite is an agentic system for small models that works across the browser and local file system in a single workflow. It combines specialized models and orchestration to support efficient agentic performance on everyday tasks.
The post MagenticLite, MagenticBrain, Fara1.5: An agentic experien...
Further Notes on Our Recent Research on AI Delegation and Long-Horizon Reliability
Our recent paper, “LLMs Corrupt Your Documents When You Delegate”, has generated discussion about the reliability of AI systems in delegated workflows. We appreciate the interest in this work and want to clarify several important points about what the paper does—and does not—claim. The research aims...
mimalloc: A high-performance, scalable memory allocator for the modern era
mimalloc is an open-source, modern, scalable memory allocator that is a drop-in replacement for malloc and free. It is relatively small (~12K lines), with clear internal data structures, and is easy to build and integrate into other projects. It provides bounded worst-case allocation times (up to OS...
GridSFM: A new, small foundation model for the electric grid
Introducing GridSFM, a small foundation model that can predict AC optimal power flow in milliseconds, boosting efficiency and unlocking cost savings. Learn how GridSFM gives grid operators direct visibility into congestion, stability, and system health.
The post GridSFM: A new, small foundation mode...
Advancing AI for materials with MatterSim: experimental synthesis, faster simulation, and multi-task models
MatterSim is expanding what AI can do for materials science—from faster large-scale simulations to MatterSim-MT, a new multi-task model for simulating properties beyond potential energy surfaces alone.
The post Advancing AI for materials with MatterSim: experimental synthesis, faster simulation, and...
Building realistic electric transmission grid dataset at scale: a pipeline from open dataset
Microsoft Research is excited to release an open dataset of approximate transmission topology of the U.S. power grid derived from publicly available data. The ability to study transmission-level power grid behavior is essential for modern power systems research. Analyses of congestion, transmission ...
Microsoft at NSDI 2026: Advances in large-scale networked systems
Microsoft researchers share advances in building and operating large-scale distributed systems, spanning datacenters, networking, and the growing intersection with AI during NSDI ’26.
The post Microsoft at NSDI 2026: Advances in large-scale networked systems appeared first on Microsoft Research.
Red-teaming a network of agents: Understanding what breaks when AI agents interact at scale
Safe agents don’t guarantee a safe ecosystem of interconnected agents. Microsoft Research examines what breaks when AI agents interact and why network-level risks require new approaches.
The post Red-teaming a network of agents: Understanding what breaks when AI agents interact at scale appeared fir...
AutoAdapt: Automated domain adaptation for large language models
Deploying large language models (LLMs) in real-world, high-stakes settings is harder than it should be. In high-stakes settings like law, medicine, and cloud incident response, performance and reliability can quickly break down because adapting models to domain-specific requirements is a slow and ma...
New Future of Work: AI is driving rapid change, uneven benefits
For the past five years, the New Future of Work report has captured how work is changing. This year, the shift feels especially sharp. Previous editions have focused on technology’s role in increasing productivity by automating tasks, accelerating communication, and expanding access to information, ...