Microsoft Research Blog

Tool-space interference in the MCP era: Designing for agent compatibility at scale 

September 11, 2025 | Adam Fourney, Tyler Payne, Maya Murad, and Saleema Amershi
As agentic AI ushers in a new era marked by tool expansion, systems are converging, and complexity is rising. Microsoft Research explores the Model Context Protocol (MCP) as a new standard for agent collaboration across fragmented tool ecosystems.

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    RenderFormer: How neural networks are reshaping 3D rendering 

    September 10, 2025 | Yue Dong

    RenderFormer, from Microsoft Research, is the first model to show that a neural network can learn a complete graphics rendering pipeline. It’s designed to support full-featured 3D rendering using only machine learning—no traditional graphics computation required.

  2. Three white icons on a gradient background transitioning from blue to green. From left to right: a network structure with connected circles, an upward-trending line graph with bars and an arrow, and a checklist with horizontal lines and checkmarks.

    Applicability vs. job displacement: further notes on our recent research on AI and occupations 

    August 21, 2025

    Recently, we released a paper Working with AI: Measuring the Occupational Implications of Generative AI that studied what occupations might find AI chatbots useful, and to what degree. The paper sparked significant discussion, which is no surprise since people care deeply about the future of AI and jobs--that’s part of why we think it’s important to study these topics.

  3. Three white icons on a gradient background transitioning from blue to green. From left to right: a network of interconnected nodes, a speedometer with the needle pointing right, and a flowchart with squares and a diamond shape.

    Dion: the distributed orthonormal update revolution is here 

    August 12, 2025 | Kwangjun Ahn and John Langford

    Dion is a new AI model optimization method that boosts scalability and performance over existing leading methods by orthonormalizing only a top rank subset of singular vectors, enabling more efficient training of large models such as LLaMA-3 with reduced overhead.

  4. Stylized digital illustration of a multi-layered circuit board. A glowing blue microchip sits at the top center, with intricate circuitry radiating outward. Beneath it, four stacked layers transition in color from blue to orange, each featuring circuit-like patterns. Smaller rectangular and circular components are connected around the layers, all set against a dark background with scattered geometric shapes.

    Project Ire autonomously identifies malware at scale 

    August 5, 2025

    Designed to classify software without context, Project Ire replicates the gold standard in malware analysis through reverse engineering. It streamlines a complex, expert-driven process, making large-scale malware detection faster & more consistent.

  5. The image features four white icons on a gradient background that transitions from blue on the left to green on the right. The first icon is a network or molecule structure with interconnected nodes. The second icon shows a stylized person in front of a computer screen. The third icon shows an organization tree with one main node and three nodes branching out side by side below it.

    Technical approach for classifying human-AI interactions at scale 

    July 23, 2025

    Semantic Telemetry helps LLMs run efficiently, reliably, and in near real-time. Learn about the engineering behind that system, including the trade-offs and lessons learned along the way—from batching strategies to token optimization and orchestration.

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