Microsoft Research

Vega turns a full credential into a single proof, sharing only what is needed and nothing more, with performance that works in real apps. msft.it/6013vVRQc

Modern apps and services manage memory at a scale that didn't exist a decade ago. mimalloc is the open-source project quietly making that possible. msft.it/6015vpoa7

Equipping communities to influence AI through involvement in AI development pipelines can improve AI and help communities realize the potential AI has to serve them well. news.microsoft.com/source/feature…

New in Research Focus: Cloud efficiency, smarter agentic cost reduction, a randomized trial on 3D telemedicine, and an open call for inclusive AI language projects in Africa. msft.it/6010vTpuG

New tools, models, repos, and papers out of Microsoft Research are here. Use AI and agents? It's worth watching: • MagenticLite from MSR AI Frontiers • Agentic GitHub workflows • Verification‑first agents • Meaning‑matching fine‑tuning • AI transition + the economy

New releases from Microsoft Research, live in 1 hour. Join for ai that runs your repo + verification-first research + more. 👉 msft.it/6014vRGqK ⏰ 9 AM PT/12 PM ET 💬 Join live + ask questions in chat

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: msft.it/6018vucjs

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. msft.it/6017vPamT

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. msft.it/6011vPOLF

Tyger moves the most demanding MRI processing to the cloud, helping researchers turn raw signals into readable images – meaning results in hours rather than days or weeks. msft.it/6010vMCSa

Designing AI isn’t just about performance. It’s about tradeoffs that affect people and the planet. In “The Shape of Things to Come,” hear Doug Burger, Amy Luers, and Ishai Menache on why applying AI responsibly may be key to addressing the climate crisis. msft.it/6017vMPyt

What if AI could predict your next medical event — like ChatGPT predicts your next word? @Microsoft Science president Peter Lee explains to @FrancesSSellers of @washingtonpost how that might be possible.

As AI and agents take on execution, our own agency expands. The question is whether organizations are built to capture it. The 2026 #WorkTrendIndex Report is now live: msft.it/6009vKCx5

Microsoft researchers share advances in building and operating large-scale distributed systems, spanning datacenters, networking, and the growing intersection with AI during NSDI ’26. Explore the work: msft.it/6011vz9EF

Research Focus: AI agents leaking enterprise data, a smarter OS for cloud deployment, and new research on how to actually structure AI use at work. msft.it/6016vKxQm

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. Learn more: microsoft.com/en-us/research…

Coming May 14 at Microsoft Research Forum: a new release and demo from MSR AI Frontiers. Plus new work on Agentic GitHub Workflows, Real-time agent verification, Energy-based fine-tuning, and Guiding the AI transition. Register now:

Congratulations to Philippe Laban, Jennifer Neville, and collaborators on their Best Paper Award at ICLR 2026 for “LLMs Get Lost In Multi-Turn Conversation.” This research explores how LLMs perform across multi-turn conversations is shaping how the field thinks about real-world AI evaluation: msft.it/6017vE12f

AutoAdapt automates the design and tuning of domain adaptation workflows for large language models. It improves performance without requiring additional compute, making deployment more accessible: msft.it/6013vDkpX

Today we're sharing a major Skala update: new paper and model release. Skala is a deep-learned XC functional for DFT: 2.8 kcal/mol on GMTKN55, wins 32/55 subsets & surpasses SOTA hybrids in accuracy at semi-local cost. Paper: arxiv.org/abs/2506.14665 Code: github.com/microsoft/skala