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Microsoft Research Blog
MagenticLite, MagenticBrain, Fara1.5: An agentic experience optimized for small models
May 21, 2026 |
Microsoft Research AI Frontiers
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.
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Recent Posts
MagenticLite, MagenticBrain, Fara1.5: An agentic experience optimized for small models
May 21, 2026 |
Microsoft Research AI Frontiers
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.
Vega: Zero-knowledge proofs for digital identity in the age of AI
May 21, 2026 |
Srinath Setty
Vega turns a full credential into a single proof, sharing only what is needed and nothing more, with performance that works in real apps.
Further Notes on Our Recent Research on AI Delegation and Long-Horizon Reliability
May 15, 2026 |
Philippe Laban
,
Tobias Schnabel
, and
Jennifer Neville
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…
mimalloc: A new, high-performance, scalable memory allocator for the modern era
May 13, 2026 |
Daan Leijen
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…
GridSFM: A new, small foundation model for the electric grid
May 13, 2026
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.
Advancing AI for materials with MatterSim: experimental synthesis, faster simulation, and multi-task models
May 12, 2026
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.
SocialReasoning-Bench: Measuring whether AI agents act in users’ best interests
May 11, 2026
Using SocialReasoning Bench, we observed a stable pattern across models—agents execute competently, but fail to consistently improve the user’s position, even with explicit instructions to optimize for user interest.
Building realistic electric transmission grid dataset at scale: a pipeline from open dataset
May 8, 2026
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 expansion, demand growth,…
Microsoft at NSDI 2026: Advances in large-scale networked systems
May 5, 2026 |
Sujata Banerjee
Microsoft researchers share advances in building and operating large-scale distributed systems, spanning datacenters, networking, and the growing intersection with AI during NSDI ’26.
Red-teaming a network of agents: Understanding what breaks when AI agents interact at scale
April 30, 2026
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.
AutoAdapt: Automated domain adaptation for large language models
April 22, 2026
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 manual process that…
New Future of Work: AI is driving rapid change, uneven benefits
April 9, 2026
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, as…
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来源
- 原文：https://www.microsoft.com/en-us/research/blog/
- 来源：Microsoft Research Blog