From static prediction to dynamic characterization: AI2BMD advances protein dynamics with ab initio accuracy

The essence of the biological world lies in the ever-changing nature of its molecules and their interactions. Understanding the dynamics and interactions of biomolecules is crucial for deciphering the mechanisms behind biological processes and for developing biomaterials and drugs. As Richard Feynman famously said, “Everything that living things do can be understood in terms of the jigglings and wigglings of atoms.” Yet capturing these real-life movements is nearly impossible through experiments.  In recent years, with the development of deep  

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AI-powered microgrids facilitate energy resilience and equity in regional communities

The rise of affordable small-scale renewable energy, like rooftop solar panels, is reshaping energy systems around the world. This shift away from fossil fuel-powered grids creates new opportunities for energy distribution that prioritize decentralized energy ownership and community empowerment. Despite this progress, centralized energy systems still dominate, often failing to provide vulnerable communities with reliable, affordable renewable energy. In response, Microsoft researchers are collaborating with local communities to explore how AI can enable community-scale energy solutions focused on energy  

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Research Focus: Week of October 28, 2024

Welcome to Research Focus, a series of blog posts that highlights notable publications, events, code/datasets, new hires and other milestones from across the research community at Microsoft. NEW RESEARCH FLASH: A Workflow Automation Agent for Diagnosing Recurring Incidents Cloud incidents such as unplanned interruptions or performance degradation can reduce customer satisfaction and revenue. Recurring incidents, typically raised by system monitors, allow for timely resolution, but also demand significant human effort for troubleshooting. Automating the diagnosis of recurring incidents  

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Introducing DRIFT Search: Combining global and local search methods to improve quality and efficiency

GraphRAG is a technique that uses large language models (LLMs) to create knowledge graphs and summaries from unstructured text documents and leverages them to improve retrieval-augmented generation (RAG) operations on private datasets. It offers comprehensive global overviews of large, private troves of unstructured text documents while also enabling exploration of detailed, localized information. By using LLMs to create comprehensive knowledge graphs that connect and describe entities and relationships contained in those documents, GraphRAG leverages semantic structuring  

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Intern Insights: Vaishnavi Ranganathan with Angela Busheska

ANGELA BUSHESKA: Yeah, absolutely. Thank you so much for having me. Super excited to be here and super excited to have spent three months—time flies!— as a researcher along with the project. So my name is Angela. I am originally from North Macedonia, a very small country next to Greece in the Balkans. And I spent my first, like, 16 years thinking that I would become a mathematician, really focused on math Olympiads. And then I moved to the capital […]

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Research Focus: Week of October 7, 2024

Welcome to Research Focus, a series of blog posts that highlights notable publications, events, code/datasets, new hires and other milestones from across the research community at Microsoft. NEW RESEARCH Securely Training Decision Trees Efficiently In a recent paper: Securely Training Decision Trees Efficiently that will appear at ACM CCS 2024, researchers from Microsoft significantly reduce the communication complexity of secure decision tree training. Decision trees are an important  

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Data Formulator: Exploring how AI can help analysts create rich data visualizations 

Transforming raw data into meaningful visuals, such as charts, is key to uncovering hidden trends and valuable insights, but even with advances in AI-powered tools, this process remains complex. Integrating AI into the iterative nature of the data visualization process is particularly challenging, as data analysts often struggle to describe complicated tasks in a single text prompt while lacking the direct control of traditional tools. This highlights the need for smarter, more intuitive solutions that combine AI’s  

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Abstracts: September 30, 2024

MARTIN GRAYSON: Pleasure, thank you.  DANIELA MASSICETI: Thanks very much, Amber. Nice to be here.  TINGLE: So, Daniela, let’s start with a Find My Things overview. What is it, how does it work, and who’s it for?  MASSICETI: I think the best way I can describe Find My Things is a personalizable object recognizer. So when we think about object recognizers in the past, they’ve, kind of, been what I would call generic object recognizers. So they can only really […]

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Microsoft Research Forum Episode 4: The future of multimodal models, a new “small” language model, and other AI updates

Microsoft Research Forum is a continuous exchange of ideas about science and technology research in the era of general AI. In the latest episode (opens in new tab), researchers discussed the latest multimodal AI models, advanced benchmarks for AI evaluation and model self-improvement, and an entirely new kind of computer for AI inference and hard optimization. Researchers at Microsoft are working to explore breakthrough technology that can help advance everything from weather prediction to materials design.  Below is a brief recap […]

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