Scaling early detection of esophageal cancer with AI

Microsoft Research and Cyted have collaborated to build novel AI models (opens in new tab) to scale the early detection of esophageal cancer. The AI-supported methods demonstrated the same diagnostic performance as the existing manual workflow, potentially reducing the pathologist’s workload by up to 63%. Esophageal cancer is the sixth most common cause of cancer deaths worldwide, in part because this disease  

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Improving LLM understanding of structured data and exploring advanced prompting methods

This research paper was presented at the 17th ACM International Conference on Web Search and Data Mining (opens in new tab) (WSDM 2024), the premier conference on web-inspired research on search and data mining. In today’s data-driven landscape, tables are indispensable for organizing and presenting information, particularly text. They streamline repetitive content, enhance  

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Research Forum Episode 2: Transforming health care and the natural sciences, AI and society, and the evolution of foundational AI technologies

Research advances are driving real-world impact faster than ever. Recent developments in AI are reshaping the way people live, work, and think. In the latest episode of Microsoft Research Forum (opens in new tab), we explore how AI is transforming health care and the natural sciences, the intersection of AI and society, and the continuing evolution of foundational AI technologies.  Below is a brief recap of the event, including select quotes from the presentations. Full replays of each session and […]

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Research Focus: Week of March 4, 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 Generative Kaleidoscopic Networks Neural networks are deep learning models that can be trained to learn complex patterns and relationships within data. In a recent paper: Generative Kaleidoscopic Networks, researchers from Microsoft detail how they discovered an “over-generalization” phenomenon, which indicates that the neural networks tend to  

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Orca-Math: Demonstrating the potential of SLMs with model specialization

Our work on Orca and Orca 2 demonstrated the power of improved training signals and methods to enhance the reasoning abilities of smaller language models, getting closer to the levels found in much larger language models. Orca-Math is another step in this direction, where we explore the capabilities of small language models (SLMs) when specialized in a certain area, in this case solving grade school math problems, which has long been recognized as a complex task for SLMs. Orca-Math  

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Abstracts: February 29, 2024

LEV TANKELEVITCH: Thanks for having me.  HUIZINGA: So in just a couple sentences—a metacognitive elevator pitch, if you will—tell us about the issue or problem your paper addresses and, more importantly, why we should care about it.  TANKELEVITCH: Sure. So as generative AI has, sort of, rolled out over the last year or two, we’ve seen some user studies come out, and as we read these studies, we noticed there are a lot of challenges that people face with these […]

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Structured knowledge from LLMs improves prompt learning for visual language models

This research paper was presented at the 38th Annual AAAI Conference on Artificial Intelligence (opens in new tab) (AAAI-24), the premier forum for advancing understanding of intelligence and its implementation in machines. We’re seeing remarkable abilities from visual language models in transforming text descriptions into images. However, creating high-quality visuals requires crafting precise prompts that  

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Research Focus: Week of February 19, 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 Vertically Autoscaling Monolithic Applications with CaaSPER: Scalable Container-as-a-Service Performance Enhanced Resizing Algorithm for the Cloud Kubernetes is a prominent open-source platform for managing cloud applications, including stateful databases, which keep track of changes and transactions involving the underlying data. These monolithic applications often must rely on vertical  

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GraphRAG: Unlocking LLM discovery on narrative private data

Perhaps the greatest challenge – and opportunity – of LLMs is extending their powerful capabilities to solve problems beyond the data on which they have been trained, and to achieve comparable results with data the LLM has never seen.  This opens new possibilities in data investigation, such as identifying themes and semantic concepts with context and grounding on datasets.  In this post, we introduce GraphRAG, created by Microsoft Research, as a significant advance in enhancing the capability of LLMs. Retrieval-Augmented […]

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