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The recent success of large vision language models shows great potential in driving the agent system operating on user interfaces. However, we argue that the power multimodal models like GPT-4V as a general agent on multiple operating systems across different applications is largely underestimated due to the lack of a robust screen parsing technique capable of: 1. reliably identifying interactable
👉 Microsoft Research Blog Post 👉 GraphRAG Accelerator 👉 GitHub Repository 👉 GraphRAG Arxiv Figure 1: An LLM-generated knowledge graph built using GPT-4 Turbo. GraphRAG is a structured, hierarchical approach to Retrieval Augmented Generation (RAG), as opposed to naive semantic-search approaches using plain text snippets. The GraphRAG process involves extracting a knowledge graph out of raw text
GarnetA high-performance cache-store from Microsoft Research High PerformanceGarnet uses a thread-scalable storage layer called Tsavorite, and provides cache-friendly shared-memory scalability with tiered storage support. Garnet supports cluster mode (sharding and replication). It has a fast pluggable network design to get high end-to-end performance (throughput and 99th percentile latency). Garne
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Multi-Agent Conversation FrameworkAutoGen provides multi-agent conversation framework as a high-level abstraction. With this framework, one can conveniently build LLM workflows.
Power Platform による、企業で有用なアプリのサンプルを無償提供しています。 本アプリは、日本マイクロソフトの社員有志により作成・公開しています。 こちらのアプリは Power Platform の Premium 機能を利用しています。 また、アプリは無償でダウンロードが可能です。 アプリについて 以下のリンクからソースをダウンロードし、フォルダ内の手順書に従ってインストール、ご利用をお願いします。 また、アプリご利用の際には Premium ライセンスが必要となります。 評価環境について アプリサンプルを Power Platform の評価環境でお試しされたい場合、以下の手順書または動画をご参考に評価環境を作成してください。 Power Platform (Power Apps, Power Automate) のお試し環境を準備しよう(手順書) Power Platfo
July 20, 2023 by Anders Hejlsberg, Steve Lucco, Daniel Rosenwasser, Pierce Boggan, Umesh Madan, Mike Hopcroft, and Gayathri Chandrasekaran In the last few months, we've seen a rush of excitement around the newest wave of large language models. While chat assistants have been the most direct application, there's a big question around how to best integrate these models into existing app interfaces.
TypeChat TypeChat helps get well-typed responses from language models to build pragmatic natural language interfaces. All powered through your types.
If you are missing a server please create a pull request in GitHub against this markdown document Language Maintainer Repository Implementation Language
Experimental Project from Microsoft Research - Join the discussions to provide feedback.
Introduction This is a (non-comprehensive) guide for C# and .NET developers that are completely new to the Rust programming language. Some concepts and constructs translate fairly well between C#/.NET and Rust, but which may be expressed differently, whereas others are a radical departure, like memory management. This guide provides a brief comparison and mapping of those constructs and concepts w
Introduction to Machine Learning for Beginners
YARP: Yet Another Reverse Proxy Welcome to the documentation for YARP! YARP is a library to help create reverse proxy servers that are high-performance, production-ready, and highly customizable. Please provide us your feedback by going to the GitHub repository. This is the documentation for YARP 2.2. For documentation of YARP 1.1.1, see https://github.com/microsoft/reverse-proxy/tree/release/1.1/
Introducing DoWhy DoWhy | An end-to-end library for causal inference Graphical Models and Potential Outcomes: Best of both worlds Four steps of causal inference Citing this package Roadmap Contributing Quick-Start Tutorial Tutorial on Causal Inference and its Connections to Machine Learning (Using DoWhy+EconML) Starter Notebooks Getting started with DoWhy: A simple example Confounding Example: Fin
Azure Synapse Analytics Azure Storage および Azure Data Lake Storage Gen2 Azure Stream Analytics Azure Machine Learning Azure App Service Event Hubs IoT Hub Power BI
Finally a task runner that truly understands the structure of my workspaces! —Jason Gore, Microsoft Loop Seriously, never build more than onceBuilding once is painful enough! Lage will remember what is done before and skip any work that is not needed. Lage even skips the work based on your changes… really!
Design, Code and Play Games on MakeCode Arcade Devices
We're excited to announce our first preview release aligning with React Native 0.62! As a preview release, we will try our best not to make breaking changes, but still have a few bumps to sort out before we're ready for release. You can now start trying out the 0.62-preview of React Native for Windows! A similar upgrade for React Native for macOS is in progress. Stay tuned for the next update! Wha
Extend your desktop experience to more than just Windows! Try out our fully supported macOS extension to React Native. React Native for Windows + macOS brings React Native support for the Windows SDK as well as the macOS 10.14 SDK. With this, you can use JavaScript to build native Windows apps for all devices supported by Windows 10 and higher including PCs, tablets, 2-in-1s, Xbox, Mixed reality d
Skip to the content. Forecasting Best Practices Time series forecasting is one of the most important topics in data science. Almost every business needs to predict the future in order to make better decisions and allocate resources more effectively. This repository provides examples and best practice guidelines for building forecasting solutions. The goal of this repository is to build a comprehen
Modern and Seamless UIs WinUI makes it easy to build modern, seamless UIs that feel natural to use on every Windows device. It embodies Fluent Design to enable intuitive, accessible, and powerful experiences and the latest user interface patterns. Unmatched Native Performance WinUI is powered by a highly optimized C++ core that delivers blistering performance, long battery life, and responsive int
Theme: ■ ■ ■ ■ BasicsStatic type-checkingNon-exception FailuresTypes for Toolingtsc, the TypeScript compilerEmitting with ErrorsExplicit TypesErased TypesDownlevelingStrictnessnoImplicitAnystrictNullChecksEveryday TypesPrimitives string, number, and booleanArraysanynoImplicitAnyType Annotations on VariablesFunctionsParameter Type AnnotationsReturn Type AnnotationsFunction ExpressionsObject TypesOp
HomeTasks Composition of tasksLoggingCommand line argumentsControlling Task Flow with ConditionalsHigher Order Task FunctionsScripts TypeScriptWebpackTypeScript LintJest Flexible Unlike create-react-app, just gives sensible defaults but does not hide config files
Day 1 Get set up and learn to build a todo app using HTML, CSS, JavaScript, and React.
Home Home What and Why Where How Developing Docs Developing Code FAQ License Code Repositories Welcome to Project Mu¶ Project Mu is a modular adaptation of TianoCore's edk2 tuned for building modern devices using a scalable, maintainable, and reusable pattern. Mu is built around the idea that shipping and maintaining a UEFI product is an ongoing collaboration between numerous partners. For too lon
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