Microsoft at NDSI 2024: Discoveries and implementations in networked systems Topics range from 5G, space, datacenters, and wide-area networking to applications in artificial intelligence, security, video conferencing, and gaming. Learn more about the discoveries and advances we're making with networked systems.
In this issue: New research helps COMET embrace African languages; FeatUp improves deep features, a computer vision research cornerstone; LLMs in the Imaginarium: Tool Learning through Simulated Trial and Error; Benchmarking LLMs across languages and more.
Microsoft researchers are taking a comprehensive and dynamic approach to help Copilot (web) continuously learn from interaction and feedback, improving the AI system and making it increasingly useful for consumers. Learn more.
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. Large language models (LLMs) have shown impressive capabilities, yet they still struggle with math reasoning. In a recent…
Integrating AI into cloud service monitoring improves incident detection accuracy, reduces unnecessary alerts, and enhances overall system reliability. This helps organizations better align with business goals and increase customer satisfaction.
Garnet is a cache-store system that addresses growing demand for data storage to support interactive web applications and services. Offering several advantages over legacy cache-stores, Garnet is now available as an open-source download.
As avatar use expands in digital spaces, advances are required to better represent all people. Discover how research into the varying perceptions of facial animation glitches in low versus high realism scenarios supports this goal.
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%.…
Structural Understanding Capabilities is a new benchmark for evaluating and improving LLM comprehension of structured table data. This advance can help LLMs process and analyze data more effectively, broadening their applicability in real-world tasks.
Research advances are driving real-world impact faster than ever. Episode 2 of Microsoft Research Forum explores how AI is transforming health care and the natural sciences, the intersection of AI and society, and the evolution of foundational AI technologies.
In this issue: Generative kaleidoscopic networks; Text diffusion with reinforced conditioning; PRISE – Learning temporal action abstractions as a sequence compression problem.
Microsoft’s Orca-Math, a specialized small language model, outperforms much larger models in solving math problems that require multi-step reasoning and shows the potential of using feedback to improve language models. Learn more.
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