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Microsoft is a Leader in the 2023 Gartner® Magic Quadrant™ for Cloud AI Developer Services

We are excited to announce that Microsoft is recognized as a Leader for the 4th year in a row in the Gartner Magic Quadrant for Cloud AI Developer Services and are especially proud to be placed furthest for our Completeness of Vision. 

We are excited to announce that Microsoft is recognized as a Leader for the fourth year in a row in the Gartner Magic Quadrant for Cloud AI Developer Services and are especially proud to be placed furthest for our Completeness of Vision.

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We continue to innovate with Azure AI and are committed to making Azure AI the trusted AI platform for building intelligent applications. Azure AI gives you the ability to responsibly build AI capabilities, with the flexibility to choose pre-built models, customizable models, or build, train, deploy, and manage your own models with Azure Machine Learning.  

Our Azure AI services can help modernize your business processes with ready-made tools for specific scenarios like document processing automation, language translation, video analysis, anomaly detection, and intelligent search. We also have pre-trained foundation models, through Azure OpenAI Service (which was generally available shortly after January 1, the cutoff for the report), including ChatGPT, GPT-4, and DALL-E. With Azure AI, pre-trained models can be customized and embedded in your apps to solve for industry and organization specific needs. Using pre-trained models, you can summarize documents, classify medical imagery, build conversational interfaces into applications, analyze customer sentiment in reviews, process medical text, and build many other tailored solutions.  

KPMG is a company on which banks and institutions rely to identify fraudulent transactions or other misconduct by financial traders. To help banks detect undesirable activity, KPMG created Magna, a risk analytics solution built using AI capabilities from Azure AI for Speech, Language, and Translator. It consolidates growing volumes of unstructured data from email, phone calls, and chats to identify potential risks quickly, reducing the time to issue an alert from 30 days down to 2 days. Separately, the KPMG global tax group is using Azure OpenAI Service as a foundational layer for building use cases on top of generative AI. They are incorporating it into KPMG’s Digital Gateway, initially focused on helping companies more efficiently identify and classify tax data that can be applied to ESG Taxes. Azure OpenAI Service is helping KPMG assess data relationships to pull and predict the right tax data and type, reducing risk factors and increasing confidence in making tax contributions public.  

Reddit, a popular online platform where users can create and join communities based on their interests and share various types of content, is using Azure AI pre-built models to improve the user experience on their platform. Millions of images get shared across Reddit’s communities, making it harder for users who use screen readers or have low-bandwidth internet connections to fully engage. To make its content more accessible and discoverable, Reddit decided all images needed captions as alternative text. Reddit chose Azure Cognitive Services for Vision to automatically generate the captions for images on its platform. Using our pre-trained models, Reddit was able to build this project quickly and without machine-learning engineering support. 

For those who want to build their own models, we’re making the machine learning model development process more accessible with automated machine learning (AutoML) capabilities in our Azure Machine Learning platform. Auto ML features can help train and tune a model based on provided target metrics, iterating hundreds of times to produce a model with the highest training score that fits a dataset. Our partnership with DataRobot further increases the accessibility of our machine-learning platform. With DataRobot, users can interact with and interpret model results and predictions directly using conversational AI. We believe that all developers and organizations, no matter their data science expertise, can build, deploy, and manage AI models with confidence. That’s why we’ve also built in the responsible AI dashboard, which monitors model performance for errors, fairness, and bias.  

Another customer, Broward College, is using Azure Machine Learning and has embedded responsible AI features to better support its diverse student body. Broward is harnessing its data to understand student pathways with the goal of increasing its student retention rate. Using Azure Machine Learning and responsible AI, the Broward team identified five key predictors of student attrition, leading to data-driven, actionable strategies to help more students transform their lives and reach their goals. 

Another way we are supporting our customers and developers is through collaboration and partnerships. On the Azure AI platform, you can easily access sophisticated AI models from companies like Databricks, Hugging Face, and OpenAI, all backed by Azure AI’s infrastructure and enterprise grade safety, security, and privacy. We’re continuing to expand our Azure OpenAI Services through our collaboration with OpenAI. Inside our Azure AI Studio you can run powerful AI models on your own data, and easily use the models in your own applications with plugins. We’re also embedding OpenAI models into our other Azure AI services, like Cognitive Search, Vision, Speech, and Language. 

Azure AI is more than just a cloud platform for building and deploying AI solutions. It is a comprehensive AI ecosystem that empowers developers, organizations, and customers to create transformative intelligent applications. Whether you need ready-to-integrate AI services, customizable models, or machine learning platform capabilities, Azure AI has you covered. With our extensive AI portfolio, aligned to Microsoft’s Responsible AI Standard, you can ensure that your AI solutions are accessible, inclusive, and fair. Azure AI is a platform that helps you tackle real world challenges today and build with the future in mind.

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Gartner, Magic Quadrant for Cloud AI Developer Services, Jim Scheibmeir, Svetlana Sicular, Arun Batchu, Mike Fang, Van Baker, Frank O’Connor, 22 May 2023.  

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