Microsoft Research

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Microsoft Research

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Microsoft researchers introduce MatterGen, a model that can discover new materials tailored to specific needs—like efficient solar cells or CO2 recycling—advancing progress beyond trial-and-error experiments.

LLMs do not get smarter just by remembering more. EvoLib turns experience into evolving knowledge, taking reusable skills and insights that help models learn and adapt across tasks long after deployment.

Cryptographic code supports vital protections in modern computing systems. Learn how a new method helps verify code as developers write it while preserving speed and adaptability as it gets implemented and evolves.

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:

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.

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

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:

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:

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.

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.

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:

In Episode 1 of the podcast “The AI Revolution in Medicine, Revisited,” host Peter Lee, president of Microsoft Research, &amp; guests Dr. Christopher A. Longhurst, MD &amp; Dr. Sara Murray discuss how generative AI is impacting patient care &amp; workflows in healthcare:

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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:

The latest Microsoft Research Forum episode is now available on-demand. Explore new ARO, Dion2, Magentic Marketplace, OptiMind, Agent Lightning, and Healthbots. Register to watch:

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

AI is transforming the way we all live, work, and think. Join us for Microsoft Research Forum, where you'll learn about the most recent advances and hear bold new ideas from the global research community. See you on June 4 for Episode 3. Register now.

Today in the journal Science: BioEmu from Microsoft Research AI for Science. This generative deep learning method emulates protein equilibrium ensembles – key for understanding protein function at scale.

Orchard is an open-source framework for the research community to train and evaluate AI agents across task types. It reduces complexity while supporting strong performance from smaller models by enabling researchers to reuse the same infrastructure.

Radiology AI is evolving beyond report generation. CARE-X explores a unified approach that combines flexible reasoning, calibrated predictions, and measurement-based tools for chest X-ray interpretation.

LLMs do not get smarter just by remembering more. EvoLib turns experience into evolving knowledge, taking reusable skills and insights that help models learn and adapt across tasks long after deployment.

Small language models learn to negotiate with SocialRL, PazaBench V2 expands speech AI evaluation across African languages, and EvoLib helps agents turn experience into knowledge. Plus: new methods for more reliable A/B testing and advances in AI-driven precision oncology.

The wait is over! Microsoft Research is sharing Skala, the new exchange-correlation functional, marking a major milestone in the accuracy/cost trade-off in DFT. Help us learn from your testing so we can improve. Available on Azure AI Foundry and GitHub.

Cryptographic code supports vital protections in modern computing systems. Learn how a new method helps verify code as developers write it while preserving speed and adaptability as it gets implemented and evolves.

Microsoft Chief Scientific Officer Eric Horvitz on what stood out at NeurIPS 2025, what’s next, and why these moments matter for the future of AI research.

MagenticLite's models are now fully open source. MagenticBrain and Fara 1.5, previously available on Microsoft Foundry, are live on Hugging Face with open weights. The app, the harness, and every model in the stack are now open.

Aurora 1.5 scales open forecasting; Flint redefines visualization; FlowDAgger accelerates adaptation. Plus: AI agents crack Rowhammer defenses and memory reshapes conversational AI.

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:

Researchers Jenna Butler, Jake Hofman, and Rebecca Janssen spend a lot of time studying AI’s influence on how people do their jobs. On the Microsoft Research Podcast, they share their thoughts on what the future of work looks like in the age of AI.

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.

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

In Episode 1 of the podcast “The AI Revolution in Medicine, Revisited,” host Peter Lee, president of Microsoft Research, & guests Dr. Christopher A. Longhurst, MD & Dr. Sara Murray discuss how generative AI is impacting patient care & workflows in healthcare: