AI tools for microsoft Indetity
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Microsoft
Microsoft is a leading technology company that develops, manufactures, licenses, supports, and sells computer software, consumer electronics, personal computers, and services. Its best-known software products are the Microsoft Windows operating system, the Microsoft Office suite, and the Internet Explorer and Edge web browsers. Its hardware products include the Xbox video game consoles and the Surface tablet computers. Microsoft is also a major provider of cloud computing services through its Azure platform.
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Microsoft Azure
Microsoft Azure is a cloud computing service that offers a wide range of products and services, including virtual machines, AI services, Kubernetes service, DevOps, SQL, and more. It provides solutions for cloud migration, data analytics, application development, and modernization. Azure aims to help organizations innovate, secure, and adapt to the era of AI by offering a flexible and scalable platform with advanced security features. Users can access Azure through a pay-as-you-go model or try it for free for up to 30 days with no upfront commitment.
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Microsoft AppSource
Microsoft AppSource is an AI-powered platform that offers a wide range of business applications to help users find solutions that drive innovation, improve business outcomes, and enhance productivity. It provides a curated collection of apps across various categories and industries, including AI, machine learning, analytics, collaboration, finance, marketing, and more. Users can explore and discover applications that cater to their specific business needs, such as boosting productivity, automating tasks, and leveraging AI capabilities to streamline operations.
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Microsoft Store
The Microsoft Store is a digital distribution platform for Microsoft Windows. It offers a wide range of apps, games, software, and other digital content for Windows PC users. Users can download and install various applications to enhance their productivity, entertainment, and overall computing experience. The Microsoft Store provides a convenient and secure way for users to discover, purchase, and manage their digital content all in one place.
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Microsoft Copilot
Microsoft Copilot is an AI-powered coding assistant that helps developers write better code, faster. It provides real-time suggestions and code completions, and can even generate entire functions and classes. Copilot is available as a Visual Studio Code extension and as a standalone application.
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Microsoft Tech Community
The Microsoft Tech Community is an online forum where users can connect with experts and peers to find answers, ask questions, build skills, and accelerate their digital transformation with the Microsoft Cloud. It offers a variety of resources, including discussions, blogs, events, and learning materials, on a wide range of topics related to Microsoft products and technologies.
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Microsoft AI
Microsoft AI is an advanced artificial intelligence solution that offers a wide range of AI-powered tools and services for businesses and individuals. It provides innovative AI solutions to enhance productivity, creativity, and connectivity across various industries. With a focus on responsible AI practices, Microsoft AI aims to empower organizations to leverage AI technology effectively and securely.
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Speech Studio
Speech Studio is a cloud-based speech-to-text and text-to-speech platform that enables developers to add speech capabilities to their applications. With Speech Studio, developers can easily transcribe audio and video files, generate synthetic speech, and build custom speech models. Speech Studio is a powerful tool that can be used to improve the accessibility, efficiency, and user experience of any application.
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Visual Studio
Visual Studio is an integrated development environment (IDE) and code editor designed for software developers and teams. It offers a comprehensive set of tools and features to enhance every stage of software development, including code editing, debugging, building, and publishing applications. Visual Studio also includes compilers, code completion tools, graphical designers, and AI-powered coding assistance through GitHub Copilot integration.
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Microsoft Copilot Studio
Microsoft Copilot Studio is an end-to-end conversational AI platform that allows users to design intelligent, actionable, and connected AI assistants for employees and customers. Users can create custom copilots, design conversational applications using generative AI and large language models, and customize Copilot for Microsoft 365. The platform offers capabilities to build copilots, generate conversations, bring systems to life, control copilot responses, handle complex queries, and offer personalized interactions. It also enables users to expand copilot reach, extend line-of-business apps, and escalate conversations with human agents.
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Neo
Zephyr Global is an AI application called Neo that provides Microsoft technical support through an AI assistant named Neo. It offers 24/7 technical support, instant solutions, and strategic guidance for Microsoft products and services. Neo assists with setup guidance, issue resolution, training opportunities, and provides additional resources for Microsoft support. The application aims to optimize operations effortlessly by delivering consistent, reliable information and round-the-clock support.
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GenAI Summit San Francisco 2024
GenAI Summit San Francisco 2024 is an innovative AI tool designed to bring together industry leaders, researchers, and enthusiasts to explore the latest trends and advancements in artificial intelligence. The platform offers a virtual space for networking, knowledge sharing, and collaboration, enabling participants to gain insights into cutting-edge AI technologies and applications. With interactive sessions, keynote speeches, and panel discussions, GenAI Summit fosters a vibrant community of AI professionals and facilitates meaningful connections in the field.
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Frankly AI
Frankly AI is an AI-powered platform that aims to benefit communities by providing fully scalable engagement tools to enhance consultation across various situations, languages, and interfaces. The platform supports natural and engaging conversations powered by natural language processing, capturing a broad range of sentiment in real-time. Frankly AI enables users and communities to access and interact with organizations in new ways, providing insights and analysis through easy-to-read dashboards. The platform is customizable to suit specific needs, offering conversational agents, data insights, virtual consultation spaces, and interactive digital asset models.
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Pincites
Pincites is an AI contract review tool designed for busy legal teams to streamline the contract review process. It offers automated redlining, suggestions, and trend analysis within Microsoft Word, helping legal professionals negotiate contracts faster and more efficiently. Pincites leverages AI to provide real-time feedback, learn user preferences, and identify patterns in contracts to enhance negotiation strategies.
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Social Intents
Social Intents is a live chat and AI chatbot solution that helps businesses provide real-time customer support, generate leads, and automate sales processes. It integrates with popular communication platforms such as Microsoft Teams, Slack, Google Chat, Zoom, and Webex, allowing businesses to manage customer interactions from a single dashboard. Social Intents also offers pre-trained ChatGPT chatbots that can be customized to handle specific customer queries and provide personalized responses. With its advanced features and integrations, Social Intents aims to enhance customer engagement, reduce support costs, and drive sales for businesses.
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TechSpective
TechSpective is an AI tool that provides technology reviews, podcasts, security insights, and Microsoft news and analysis. The platform offers in-depth articles on cybersecurity, artificial intelligence, and emerging technologies. Users can stay informed about the latest trends in the tech industry and learn about innovative products and solutions.
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Alcion
Alcion is a backup-as-a-service solution designed specifically for Microsoft 365 users. It offers a secure backup solution driven by AI technology to protect data from ransomware, malware, accidents, and outages. Alcion provides a user-friendly experience with features like intelligent backups, robust data protection, security, and compliance. The platform is built to be easy to use, efficient, and reliable, ensuring that users can quickly set up backups and restore data when needed. Alcion is trusted by Microsoft 365 admins globally for its advanced AI-driven approach to data protection.
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MikeOnAI Copilot Buddy
Experimental Guide to Navigating Microsoft 365 Copilot Based on Public Information from Microsoft Sources
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Defender for Endpoint Guardian
To assist individuals seeking to learn about or work with Microsoft's Defender for Endpoint. I provide detailed explanations, step-by-step guides, troubleshooting advice, cybersecurity best practices, and demonstrations, all specifically tailored to Microsoft Defender for Endpoint.
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Steve Mordue's MVP Brain
Microsoft Power Platform Expert GPT, Modeled on the Knowledge and Personality of Steve Mordue MVP.
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Dynamics 365 Business Central Genius
Microsoft Dynamics 365 Business Central Genius powered by ANEGIS
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Power Platform Helper
Trained on learn.microsoft.com content including Azure Functions, Logic Apps, DAX, Dynamics365, Microsoft 365, Compliance, ODATA, Power Agents, Apps, Automate, BI, Pages, Query, Power Platform Administration, Developer, Guidance
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MS Partner Co-Sell Creator
Friendly, helpful assistant for Microsoft Partner-led campaigns
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MS Learn GPT
Factual, clear guidance based on Microsoft Learn and GitHub Docs. Ask me about cloud native solutions, GitHub collaboration or certifications.
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CDR Guru
To master Unified Communications Data across platforms like Cisco, Avaya, Mitel, and Microsoft Teams, by orchestrating a team of expert agents and providing actionable solutions.
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Azure-Analytics-and-AI-Engagement
The Azure-Analytics-and-AI-Engagement repository provides packaged Industry Scenario DREAM Demos with ARM templates (Containing a demo web application, Power BI reports, Synapse resources, AML Notebooks etc.) that can be deployed in a customerโs subscription using the CAPE tool within a matter of few hours. Partners can also deploy DREAM Demos in their own subscriptions using DPoC.
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autogen
AutoGen is a framework that enables the development of LLM applications using multiple agents that can converse with each other to solve tasks. AutoGen agents are customizable, conversable, and seamlessly allow human participation. They can operate in various modes that employ combinations of LLMs, human inputs, and tools.
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onnxruntime-genai
ONNX Runtime Generative AI is a library that provides the generative AI loop for ONNX models, including inference with ONNX Runtime, logits processing, search and sampling, and KV cache management. Users can call a high level `generate()` method, or run each iteration of the model in a loop. It supports greedy/beam search and TopP, TopK sampling to generate token sequences, has built in logits processing like repetition penalties, and allows for easy custom scoring.
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promptflow
**Prompt flow** is a suite of development tools designed to streamline the end-to-end development cycle of LLM-based AI applications, from ideation, prototyping, testing, evaluation to production deployment and monitoring. It makes prompt engineering much easier and enables you to build LLM apps with production quality.
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TypeChat
TypeChat is a library that simplifies the creation of natural language interfaces using types. Traditionally, building natural language interfaces has been challenging, often relying on complex decision trees to determine intent and gather necessary inputs for action. Large language models (LLMs) have simplified this process by allowing us to accept natural language input from users and match it to intent. However, this has introduced new challenges, such as the need to constrain the model's response for safety, structure responses from the model for further processing, and ensure the validity of the model's response. Prompt engineering aims to address these issues, but it comes with a steep learning curve and increased fragility as the prompt grows in size.
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semantic-kernel
Semantic Kernel is an SDK that integrates Large Language Models (LLMs) like OpenAI, Azure OpenAI, and Hugging Face with conventional programming languages like C#, Python, and Java. Semantic Kernel achieves this by allowing you to define plugins that can be chained together in just a few lines of code. What makes Semantic Kernel _special_ , however, is its ability to _automatically_ orchestrate plugins with AI. With Semantic Kernel planners, you can ask an LLM to generate a plan that achieves a user's unique goal. Afterwards, Semantic Kernel will execute the plan for the user.
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AIforEarthDataSets
The Microsoft AI for Earth program hosts geospatial data on Azure that is important to environmental sustainability and Earth science. This repo hosts documentation and demonstration notebooks for all the data that is managed by AI for Earth. It also serves as a "staging ground" for the Planetary Computer Data Catalog.
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RecAI
RecAI is a project that explores the integration of Large Language Models (LLMs) into recommender systems, addressing the challenges of interactivity, explainability, and controllability. It aims to bridge the gap between general-purpose LLMs and domain-specific recommender systems, providing a holistic perspective on the practical requirements of LLM4Rec. The project investigates various techniques, including Recommender AI agents, selective knowledge injection, fine-tuning language models, evaluation, and LLMs as model explainers, to create more sophisticated, interactive, and user-centric recommender systems.
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generative-ai-for-beginners
This course has 18 lessons. Each lesson covers its own topic so start wherever you like! Lessons are labeled either "Learn" lessons explaining a Generative AI concept or "Build" lessons that explain a concept and code examples in both **Python** and **TypeScript** when possible. Each lesson also includes a "Keep Learning" section with additional learning tools. **What You Need** * Access to the Azure OpenAI Service **OR** OpenAI API - _Only required to complete coding lessons_ * Basic knowledge of Python or Typescript is helpful - *For absolute beginners check out these Python and TypeScript courses. * A Github account to fork this entire repo to your own GitHub account We have created a **Course Setup** lesson to help you with setting up your development environment. Don't forget to star (๐) this repo to find it easier later. ## ๐ง Ready to Deploy? If you are looking for more advanced code samples, check out our collection of Generative AI Code Samples in both **Python** and **TypeScript**. ## ๐ฃ๏ธ Meet Other Learners, Get Support Join our official AI Discord server to meet and network with other learners taking this course and get support. ## ๐ Building a Startup? Sign up for Microsoft for Startups Founders Hub to receive **free OpenAI credits** and up to **$150k towards Azure credits to access OpenAI models through Azure OpenAI Services**. ## ๐ Want to help? Do you have suggestions or found spelling or code errors? Raise an issue or Create a pull request ## ๐ Each lesson includes: * A short video introduction to the topic * A written lesson located in the README * Python and TypeScript code samples supporting Azure OpenAI and OpenAI API * Links to extra resources to continue your learning ## ๐๏ธ Lessons | | Lesson Link | Description | Additional Learning | | :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ | | 00 | Course Setup | **Learn:** How to Setup Your Development Environment | Learn More | | 01 | Introduction to Generative AI and LLMs | **Learn:** Understanding what Generative AI is and how Large Language Models (LLMs) work. | Learn More | | 02 | Exploring and comparing different LLMs | **Learn:** How to select the right model for your use case | Learn More | | 03 | Using Generative AI Responsibly | **Learn:** How to build Generative AI Applications responsibly | Learn More | | 04 | Understanding Prompt Engineering Fundamentals | **Learn:** Hands-on Prompt Engineering Best Practices | Learn More | | 05 | Creating Advanced Prompts | **Learn:** How to apply prompt engineering techniques that improve the outcome of your prompts. | Learn More | | 06 | Building Text Generation Applications | **Build:** A text generation app using Azure OpenAI | Learn More | | 07 | Building Chat Applications | **Build:** Techniques for efficiently building and integrating chat applications. | Learn More | | 08 | Building Search Apps Vector Databases | **Build:** A search application that uses Embeddings to search for data. | Learn More | | 09 | Building Image Generation Applications | **Build:** A image generation application | Learn More | | 10 | Building Low Code AI Applications | **Build:** A Generative AI application using Low Code tools | Learn More | | 11 | Integrating External Applications with Function Calling | **Build:** What is function calling and its use cases for applications | Learn More | | 12 | Designing UX for AI Applications | **Learn:** How to apply UX design principles when developing Generative AI Applications | Learn More | | 13 | Securing Your Generative AI Applications | **Learn:** The threats and risks to AI systems and methods to secure these systems. | Learn More | | 14 | The Generative AI Application Lifecycle | **Learn:** The tools and metrics to manage the LLM Lifecycle and LLMOps | Learn More | | 15 | Retrieval Augmented Generation (RAG) and Vector Databases | **Build:** An application using a RAG Framework to retrieve embeddings from a Vector Databases | Learn More | | 16 | Open Source Models and Hugging Face | **Build:** An application using open source models available on Hugging Face | Learn More | | 17 | AI Agents | **Build:** An application using an AI Agent Framework | Learn More | | 18 | Fine-Tuning LLMs | **Learn:** The what, why and how of fine-tuning LLMs | Learn More |
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mscclpp
MSCCL++ is a GPU-driven communication stack for scalable AI applications. It provides a highly efficient and customizable communication stack for distributed GPU applications. MSCCL++ redefines inter-GPU communication interfaces, delivering a highly efficient and customizable communication stack for distributed GPU applications. Its design is specifically tailored to accommodate diverse performance optimization scenarios often encountered in state-of-the-art AI applications. MSCCL++ provides communication abstractions at the lowest level close to hardware and at the highest level close to application API. The lowest level of abstraction is ultra light weight which enables a user to implement logics of data movement for a collective operation such as AllReduce inside a GPU kernel extremely efficiently without worrying about memory ordering of different ops. The modularity of MSCCL++ enables a user to construct the building blocks of MSCCL++ in a high level abstraction in Python and feed them to a CUDA kernel in order to facilitate the user's productivity. MSCCL++ provides fine-grained synchronous and asynchronous 0-copy 1-sided abstracts for communication primitives such as `put()`, `get()`, `signal()`, `flush()`, and `wait()`. The 1-sided abstractions allows a user to asynchronously `put()` their data on the remote GPU as soon as it is ready without requiring the remote side to issue any receive instruction. This enables users to easily implement flexible communication logics, such as overlapping communication with computation, or implementing customized collective communication algorithms without worrying about potential deadlocks. Additionally, the 0-copy capability enables MSCCL++ to directly transfer data between user's buffers without using intermediate internal buffers which saves GPU bandwidth and memory capacity. MSCCL++ provides consistent abstractions regardless of the location of the remote GPU (either on the local node or on a remote node) or the underlying link (either NVLink/xGMI or InfiniBand). This simplifies the code for inter-GPU communication, which is often complex due to memory ordering of GPU/CPU read/writes and therefore, is error-prone.
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aici
The Artificial Intelligence Controller Interface (AICI) lets you build Controllers that constrain and direct output of a Large Language Model (LLM) in real time. Controllers are flexible programs capable of implementing constrained decoding, dynamic editing of prompts and generated text, and coordinating execution across multiple, parallel generations. Controllers incorporate custom logic during the token-by-token decoding and maintain state during an LLM request. This allows diverse Controller strategies, from programmatic or query-based decoding to multi-agent conversations to execute efficiently in tight integration with the LLM itself.
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BitBLAS
BitBLAS is a library for mixed-precision BLAS operations on GPUs, for example, the $W_{wdtype}A_{adtype}$ mixed-precision matrix multiplication where $C_{cdtype}[M, N] = A_{adtype}[M, K] \times W_{wdtype}[N, K]$. BitBLAS aims to support efficient mixed-precision DNN model deployment, especially the $W_{wdtype}A_{adtype}$ quantization in large language models (LLMs), for example, the $W_{UINT4}A_{FP16}$ in GPTQ, the $W_{INT2}A_{FP16}$ in BitDistiller, the $W_{INT2}A_{INT8}$ in BitNet-b1.58. BitBLAS is based on techniques from our accepted submission at OSDI'24.
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Mastering-GitHub-Copilot-for-Paired-Programming
Mastering GitHub Copilot for AI Paired Programming is a comprehensive course designed to equip you with the skills and knowledge necessary to harness the power of GitHub Copilot, an AI-driven coding assistant. Through a series of engaging lessons, you will learn how to seamlessly integrate GitHub Copilot into your workflow, leveraging its autocompletion, customizable features, and advanced programming techniques. This course is tailored to provide you with a deep understanding of AI-driven algorithms and best practices, enabling you to enhance code quality and accelerate your coding skills. By embracing the transformative power of AI paired programming, you will gain the tools and confidence needed to succeed in today's dynamic software development landscape.
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azure-openai-dev-skills-orchestrator
An opinionated .NET framework, that is built on top of Semantic Kernel and Orleans, which helps creating and hosting event-driven AI Agents.
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CoML
CoML (formerly MLCopilot) is an interactive coding assistant for data scientists and machine learning developers, empowered on large language models. It offers an out-of-the-box interactive natural language programming interface for data mining and machine learning tasks, integration with Jupyter lab and Jupyter notebook, and a built-in large knowledge base of machine learning to enhance the ability to solve complex tasks. The tool is designed to assist users in coding tasks related to data analysis and machine learning using natural language commands within Jupyter environments.
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responsible-ai-toolbox
Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment interfaces and libraries for understanding AI systems. It empowers developers and stakeholders to develop and monitor AI responsibly, enabling better data-driven actions. The toolbox includes visualization widgets for model assessment, error analysis, interpretability, fairness assessment, and mitigations library. It also offers a JupyterLab extension for managing machine learning experiments and a library for measuring gender bias in NLP datasets.