This leading textbook provides a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first-year PhD students, as well as researchers and practitioners. No previous knowledge of pattern recognition or machine learning concepts is assumed. This is the first machine learning textbook to include a comprehensive […]| Microsoft Research
AI clusters today are one of the major uses of High Bandwidth Memory (HBM). However, HBM is suboptimal for AI workloads for several reasons. Analysis shows HBM is overprovisioned on write performance, but underprovisioned on density and read bandwidth, and also has significant energy per bit overheads. It is also expensive, with lower yield than […]| Microsoft Research
Link technologies in today’s data center networks impose a fundamental trade-off between reach, power, and reliability. Copper links are power-efficient and reliable but have very limited reach (| Microsoft Research
To match the blooming demand of generative AI workloads, GPU designers have so far been trying to pack more and more compute and memory into single complex and expensive packages. However, there is growing uncertainty about the scalability of individual GPUs and thus AI clusters, as state-of-the-art GPUs are already displaying packaging, yield, and cooling […]| Microsoft Research
At Microsoft, we’re expanding AI capabilities by training small language models to achieve the kind of enhanced reasoning and comprehension typically found only in much larger models.| Microsoft Research
Generative AI presents a unique challenge and opportunity to reexamine governance practices for the responsible development, deployment, and use of AI. To advance thinking in this space, Microsoft has tapped into the experience and knowledge of experts across domains—from genome editing to cybersecurity—to investigate the role of testing and evaluation as a governance tool. AI […]| Microsoft Research
By Doug Burger, Distinguished Engineer, Microsoft Today at Hot Chips 2017, our cross-Microsoft team unveiled a new deep learning acceleration platform, codenamed Project Brainwave. I’m delighted to share more details in this post, since Project Brainwave achieves a major leap forward in both performance and flexibility for cloud-based serving of deep learning models. We designed […]| Microsoft Research
Datacenter memory and network limits are restraining AI system performance. MOSAIC uses microLEDs and a wide-and-slow optical architecture to deliver faster, longer, more reliable, and energy efficient connections that could transform AI cluster designs:| Microsoft Research
Azure Research – Systems is a research group in Azure Core that brings forward-looking, world-class systems research directly into Azure, to improve the efficiency of the infrastructure.| Microsoft Research
Generative AI tools hold promise to increase human productivity. This paper presents results from a controlled experiment with GitHub Copilot, an AI pair programmer. Recruited software developers were asked to implement an HTTP server in JavaScript as quickly as possible. The treatment group, with access to the AI pair programmer, completed the task 55.8% faster […]| Microsoft Research
At RSA Conference 2018, Microsoft announced Azure Sphere, previewing a unique new solution to help connect and secure the most populous category of computing today: the tens of billions of devices powered by microcontrollers (MCUs). Azure Sphere represents an opportunity for Microsoft and our partners to serve a new era of computing with securely connected […]| Microsoft Research
Generalist foundation models such as GPT-4 have displayed surprising capabilities in a wide variety of domains and tasks. Yet, there is a prevalent assumption that they cannot match specialist capabilities without intensive training of models with specialty knowledge. For example, most explorations to date on medical competency benchmarks have leveraged domain specific training, as exemplified […]| Microsoft Research
This figure was adapted from a similar image published in DistilBERT. Turing Natural Language Generation (T-NLG) is a 17 billion parameter language model by Microsoft that outperforms the state of the art on many downstream NLP tasks. We present a demo of the model, including its freeform generation, question answering, and summarization capabilities, to academics […]| Microsoft Research
Microsoft is transforming retrieval-augmented generation with GraphRAG, using LLM-generated knowledge graphs to significantly improve Q&A when analyzing complex information and consistently outperforming baseline RAG. Get the details.| Microsoft Research
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 […]| Microsoft Research
Microsoft Chief Scientific Officer Eric Horvitz explains how new prompting strategies can enable generalist large language models like GPT-4 to achieve exceptional expertise in specific domains, such as medicine, and outperform fine-tuned specialist models.| Microsoft Research
Christopher Bishop is a Microsoft Technical Fellow and the Director of Microsoft Research AI for Science. He is also Honorary Professor of Com…| Microsoft Research
Project Silica is developing the first-ever storage technology designed and built from the ground up for the cloud, using femtosecond lasers to store data.| Microsoft Research
