Microsoft Build brings AI tools to the forefront for developers - The Official Microsoft Blog (2023)

You only need two simple letters to accurately convey the major shift in the technology space this year: A and I. Beyond those letters, however, is a complex, evolving and exciting way in which we work, communicate and collaborate. As you will see, artificial intelligence is a common thread as we embark on Microsoft Build, our annual flagship event for developers.

It’s already been a landmark year for the industry, starting in January with the announcement of an extension of our partnership with OpenAI to accelerate AI breakthroughs and to ensure these benefits are broadly shared with the world. And in February, Microsoft announced an all-new, AI-powered Bing search engine and Edge browser to transform the largest software category in the world – search.

Since then, developments have accelerated at a rapid pace, with several key milestones along the way, including:

  • Greater availability of Azure OpenAI Service with added support for ChatGPT and OpenAI’s groundbreaking GPT-4 model.
  • Copilots across a wide range of users, including Dynamics 365 Copilot, Microsoft 365 Copilot and Copilot for Power Platform.
  • Expansion of a new AI-powered Bing to the Windows 11 taskbar, mobile and Skype; Bing Image Creator to chat; and a full open preview of the platform, no waitlist required.

This is just the beginning of the new era of AI. That’s why Microsoft Build is so important. During this event, we’ll be showcasing how AI is redefining what and how developers build, as well as how AI is changing the future of work.

Before we get into the news, let’s talk about two concepts we are discussing at length during Microsoft Build: copilots and plugins.

A copilot is an application that uses modern AI and large language models (LLMs) like GPT-4 to assist people with complex tasks. Microsoft first introduced the concept of a copilot nearly two years ago with GitHub Copilot, an AI pair programmer that assists developers with writing code, and we continue to release copilots across many of the company’s core businesses.

We believe the copilot represents both a new paradigm in AI-powered software and a profound shift in the way that software is built – from imagining new product scenarios, to the user experience, the architecture, the services that it uses and how to think about safety and security.

Plugins are tools first introduced for ChatGPT, and more recently Bing, which augment the capabilities of AI systems, enabling them to interact with application programming interfaces (APIs) from other software and services to retrieve real-time information, incorporate company and other business data, perform new types of computations and safely take action on the user’s behalf. Think of plugins as the connection between copilots and the rest of the digital world.

With that said, let’s focus on the news and announcements we’re unveiling during Microsoft Build.

Growing the AI plugin ecosystem

Microsoft is announcing that we will adopt the same open plugin standard that OpenAI introduced for ChatGPT, enabling interoperability across ChatGPT and the breadth of Microsoft’s copilot offerings.

Developers can now use one platform to build plugins that work across both consumer and business surfaces, including ChatGPT, Bing, Dynamics 365 Copilot and Microsoft 365 Copilot.

And if you want to develop and use your own plugins with your AI application built on Azure OpenAI Service, it will, by default, be interoperable with this same plugin standard. This means developers can build experiences that enable people to interact with their apps using the most natural user interface: the human language.

As part of this shared plugin platform, Bing is adding to its support for plugins. In addition to previously announced plugins for OpenTable and Wolfram Alpha, we will also have Expedia, Instacart, Kayak, Klarna, Redfin and Zillow, among many others in the Bing ecosystem.

In addition to the common plugin platform, Microsoft is announcing that Bing is coming to ChatGPT as the default search experience. ChatGPT will now have a world-class search engine built-in to provide more up-to-date answers with access from the web. Now, answers are grounded by search and web data and include citations so users can learn more, all directly from within chat. The new experience is rolling out to ChatGPT Plus subscribers starting today and will be available to free users soon by simply enabling a plugin.

Developers can now extend Microsoft 365 Copilot with plugins

We’re also announcing that developers can now integrate their apps and services into Microsoft 365 Copilot with plugins.

Plugins for Microsoft 365 Copilot include ChatGPT and Bing plugins, as well as Teams message extensions and Power Platform connectors – enabling developers to leverage their existing investments. And developers will be able to easily build new plugins for Microsoft 365 Copilot with the Microsoft Teams Toolkit for Visual Studio Code and Visual Studio. Developers can also extend Microsoft 365 Copilot by bringing their data into the Microsoft Graph, contextualizing relevant and actionable information with the recently announced Semantic Index for Copilot.

More than 50 plugins from partners will be available for customers as part of the early access program, including Atlassian, Adobe, ServiceNow, Thomson Reuters, Moveworks and Mural, with thousands more available by the general availability of Microsoft 365 Copilot.

New Azure AI tooling to help developers build, operationalize deploy their own next-generation AI apps

It starts with our new Azure AI Studio. We’re making it simple to integrate external data sources into Azure OpenAI Service. In addition, we’re excited to introduce Azure Machine Learning prompt flow to make it easier for developers to construct prompts while taking advantage of popular open-source prompt orchestration solutions like Semantic Kernel.

In Azure OpenAI Service, which brings together advanced models including ChatGPT and GPT-4, with the enterprise capabilities of Azure, we’re announcing updates to enable developers to deploy the most cutting-edge AI models using their own data; a Provisioned Throughput SKU that offers dedicated capacity; and plugins that simplify integrating other external data sources into a customer’s use of Azure OpenAI Service. We now have more than 4,500 customers using Azure OpenAI Service.

Building responsibly together

At Microsoft, we’ve been committed to developing AI technology that has a beneficial impact and earns trust, while also sharing our own learnings and building new tools and innovations that help developers and businesses implement responsible AI practices in their own work and organizations. At Build, we’re introducing several new updates, including Azure AI Content Safety, a new Azure AI service to help businesses create safer online environments and communities. As part of Microsoft’s commitment to building responsible AI systems, Azure AI Content Safety will be integrated across Microsoft products, including Azure OpenAI Service and Azure Machine Learning.

We’re also introducing new tools to Azure Machine Learning, including expanding Responsible AI dashboard support for text and image data, in preview, enabling users to evaluate large models built with unstructured data during the model building, training and/or evaluation stage. This helps users identify model errors, fairness issues and model explanations before models are deployed, for more performant and fair computer vision and natural language processing (NLP) models. And prompt flow, in preview soon, provides a streamlined experience for prompting, evaluating and tuning large language models. Users can quickly create prompt workflows that connect to various language models and data sources and assess the quality of their workflows with measurements such as groundedness to choose the best prompt for their use case. Prompt flow also integrates Azure AI Content Safety to help users detect and remove harmful content directly in their flow of work.

In addition, Microsoft announced new media provenance capabilities coming to Microsoft Designer and Bing Image Creator in the coming months that will enable users to verify whether an image or video was generated by AI. The technology uses cryptographic methods to mark and sign AI-generated content with metadata about its origin.

Introducing Microsoft Fabric, a new unified platform for analytics

Today’s world is awash with data, constantly streaming from the devices we use, the applications we build and the interactions we have.And now, as we enter a new era defined by AI, this data is becoming even more important.Powering organization-specific AI experiences requires a constant supply of clean data from a well-managed and highly integrated analytics system. But most organizations’ analytics systems are a labyrinth of specialized and disconnected services.

Microsoft Fabric is a unified platform for analytics that includes data engineering, data integration, data warehousing, data science, real-time analytics, applied observability and business intelligence, all connected to a single data repository called OneLake.

It enables customers of all technical levels to experience capabilities in a single, unified experience. It is infused with Azure OpenAI Service at every layer to help customers unlock the full potential of their data, enabling developers to leverage the power of generative AI to find insights in their data.

With Copilot in Microsoft Fabric in every data experience, customers can use conversational language to create dataflows and data pipelines, generate code and entire functions, build machine learning models or visualize results. Customers can even create their own conversational language experiences that combine Azure OpenAI Service models and their data and publish them as plugins.

Accelerating an AI-powered future through partners

Our customers benefit from our partner collaborations, such as with NVIDIA, that enable organizations to design, develop, deploy and manage applications with the scale and security of Azure. NVIDIA will accelerate enterprise-ready generative AI with NVIDIA AI Enterprise Integration with Azure Machine Learning. Omniverse Cloud, only available on Azure, enables organizations to aggregate data into massive, high-performance models, connect their domain-specific software tools and enable multi-user live collaboration across factory locations. NVIDIA GPUs leveraging ONNX Runtime & Olive toolchain will support the implementation of accelerating AI models without needing a deeper knowledge of the hardware.

New capabilities for Microsoft Dev Box

Microsoft Dev Box, an Azure service that gives developers access to ready-to-code, project-specific dev boxes that are preconfigured and centrally managed, is introducing several new capabilities to enhance the developer experience and boost productivity. While in preview, we’ve seen many customers experimenting with Dev Box, and we’ve migrated more than 9,000 developers internally to the service for day-to-day software development.

Now, we’ve added additional features and capabilities, including customization using configuration-as-code and new starter developer images in Azure Marketplace that provide dev teams with ready-to-use images that can be customized further for specific dev team needs.Additionally, developers can now manage custom environments from a specialized developer portal, Azure Deployment Environments. Dev Box general availability will begin in July.

Unveiling a new home for developers on Windows 11 with Dev Home

Dev Home will launch at Microsoft Build in preview as a new Windows experience developers can get from the Microsoft Store.

Dev Home makes it easy to connect to GitHub and configure cloud development environments like Microsoft Dev Box and GitHub Codespaces.Dev Home is open source and fully extensible, enabling developers to enhance their experience with a customizable dashboard and the tools they need to be successful.

Introducing Windows Copilot for Windows 11

Last fall at our Windows and Surface launch, Chief Product Officer Panos Panay talked about the power of AI to unlock new interaction models on the PC with Windows Studio Effects and DALL-E 2 in Microsoft Designer, and at CES he talked about how AI is going to reinvent the way people get things done on Windows.

This brings us to Windows Copilot.

Windows will be the first PC platform to centralize AI assistance with the introduction of Windows Copilot. Together, with Bing Chat and first- and third-party plugins, users can focus on bringing their ideas to life, completing complex projects and collaborating instead of spending energy finding, launching and working across multiple applications.

This builds on the integration we released into Windows 11 back in February that brought the new AI-powered Bing to the taskbar.

A preview of Windows Copilot will start to become available for Windows 11 in June.

As you can see, it’s going to be a busy time at Microsoft Build. To give you a sense of what developers are going to experience at the event, we’re expecting approximately 200,000 registered attendees, with 350 sessions and more than 125 hours of content over two days. In total, we’ll announce more than 50 new products and features.

For more information, make sure to watch keynotes on demand from Microsoft Chairman and CEO Satya Nadella, Kevin Scott and Scott Guthrie on Day 1. On Day 2, watch the keynotes anchored by Rajesh Jha and Panos Panay. Additionally, you can explore all the news and announcements in the Book of News and read more stories and news about products from Microsoft Build here:


Watch Microsoft Build keynotes and view videos and photos

Microsoft outlines framework for building AI apps and copilots; expands AI plugin ecosystem

Bing at Microsoft Build 2023: Continuing the Transformation of Search

Empowering every developer with plugins for Microsoft 365 Copilot

Bringing the power of AI to Windows 11 – unlocking a new era of productivity for customers and developers with Windows Copilot and Dev Home

Build next-generation, AI-powered applications on Microsoft Azure

Introducing Microsoft Fabric: Data analytics for the era of AI

Tags: AI, Azure AI Content Safety, Azure OpenAI Service, Bing, copilots, developers, Microsoft 365 Copilot, Microsoft Build, plugins, Windows 11


Which Azure tool can help you build artificial intelligence AI applications answer? ›

Use familiar tools like Jupyter and Visual Studio Code, alongside frameworks like PyTorch on Azure, TensorFlow, and Scikit-Learn.

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Microsoft AI, powered by Azure, provides billions of intelligent experiences every day in Windows, Xbox, Microsoft 365, Teams, Azure AI, Power Platform, Dynamics 365 and Microsoft Defender. Our AI tools and technologies are designed to benefit everyone at every level in every organization.

What is the name of Microsoft's new AI tool? ›

Synopsis. The main three functions of the Copilot are to free up creativity, free up productivity, and sharpen user skills. Microsoft recently announced its artificial intelligence (AI)-powered digital assistant named 'Copilot'.

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At Microsoft, we've recognized six principles that we believe should guide AI development and use — fairness, reliability and safety, privacy and security, inclusiveness, transparency, and accountability.

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Azure Cognitive Services

Transcribe audible speech into readable, searchable text. Convert text to lifelike speech for more natural interfaces. Integrate real-time speech translation into your apps. Identify and verify the people speaking based on audio.

Which of the following is part of the Azure artificial intelligence service the correct answer will display here shortly? ›

Which of the following is part of the Azure Artificial Intelligence service? Azure Machine Learning service. Machine Learning service provides a cloud-based environment that you can use to develop, train, test, deploy, manage, and track machine learning models.

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Faster, more accurate decisions

AI reduces human error, which makes it helpful for decisions that are heavily informed by data and involve a lot of complex calculations.

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An Azure Fundamentals Certification can be an excellent way to make your resume stand out to potential employers. Certifications from industry leaders like Microsoft can help demonstrate your knowledge of cloud computing models, cloud governance strategy, cloud migration, and more.

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  • Dynamics 365.
  • Microsoft 365.
  • Microsoft Teams.
  • Windows 365.

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10 “Best” AI Tools for Business (July 2023)
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Does Microsoft own OpenAI? ›

″OpenAI was created as an open source (which is why I named it 'Open' AI), non-profit company to serve as a counterweight to Google, but now it has become a closed source, maximum-profit company effectively controlled by Microsoft,” Musk tweeted in February.

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

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At Microsoft, we've recognized six principles that we believe should guide AI development and use — fairness, reliability and safety, privacy and security, inclusiveness, transparency, and accountability.

What is one of four key principles of AI? ›

Establishing Accountability

Focusing on those four foundations of responsible AI — empathy, fairness, transparency, and accountability — will not only benefit customers, it will differentiate any organization from its competitors and help generate a significant financial return.

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Google Bard is an AI-powered chatbot tool designed by Google to simulate human conversations using natural language processing and machine learning.

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Oracle Analytics uses embedded machine learning and artificial intelligence to analyze data from across your organization so you can make smarter predictions and better decisions.

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Microsoft outlines six key principles for responsible AI: accountability, inclusiveness, reliability and safety, fairness, transparency, and privacy and security. These principles are essential to creating responsible and trustworthy AI as it moves into more mainstream products and services.

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Azure Logic Apps is a cloud platform where you can create and run automated workflows with little to no code. By using the visual designer and selecting from prebuilt operations, you can quickly build a workflow that integrates and manages your apps, data, services, and systems.

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The following are the primary advantages of AI:
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  • AI augments the capabilities of differently abled individuals.

What are 3 major benefits of using AI in software testing? ›

What Are The Significant Advantages Of Artificial Intelligence In Software Testing?
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  • Savings in Time and Money. ...
  • Greater Test Coverage. ...
  • Enhanced Defect Tracing. ...
  • Improved Regression Tests. ...
  • Conduct Visual Testing. ...
  • Automated API Test Generation. ...
  • Self-Repair Involved in the Implementation of Selenium Tests.

How is Microsoft investing in AI? ›

Microsoft announces major investment in artificial intelligence startup OpenAI. Microsoft says it is making a “multiyear, multibillion dollar investment” in the artificial intelligence startup OpenAI, maker of ChatGPT and other tools that can write readable text and generate new images.

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Today, we are bringing the power of next-generation AI to work. Introducing Microsoft 365 Copilot — your copilot for work. It combines the power of large language models (LLMs) with your data in the Microsoft Graph and the Microsoft 365 apps to turn your words into the most powerful productivity tool on the planet.

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Microsoft Corp. is investing $10 billion in OpenAI, whose artificial intelligence tool ChatGPT has lit up the internet since its introduction in November, amassing more than a million users within days and touching off a fresh debate over the role of AI in the workplace.

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Does Microsoft have an AI assistant? ›

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By automating certain tasks and providing real-time insights, AI can help organizations make faster and more informed decisions. This can be particularly valuable in high-stakes environments, where decisions must be made quickly and accurately to prevent costly errors or save lives.

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GPT-3 was released in 2020 and is the largest and most powerful AI model to date. It has 175 billion parameters, which is more than ten times larger than its predecessor, GPT-2.

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In a recent interview on CNBC, Elon Musk, Tesla founder, CEO, and billionaire entrepreneur, said he invested $50 million into OpenAI and is ultimately the reason that the company exists.

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OpenAI, founded in 2015 with Altman and Musk as initial board members, achieved global recognition with the introduction of ChatGPT. Altman took the helm as CEO in 2020, following his transition from leadership roles at Y Combinator.

What is Microsoft doing in artificial intelligence? ›

Our approach to AI infrastructure

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Who is leading in AI? ›

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The key elements of AI include: Natural language processing (NLP) Expert systems. Robotics.

What are the 5 components of AI? ›

The components of AI include Machine Learning, Natural Language Processing, Computer Vision, Robotics, and Expert Systems.

What are the 3 components of AI program? ›

To understand some of the deeper concepts, such as data mining, natural language processing, and driving software, you need to know the three basic AI concepts: machine learning, deep learning, and neural networks.

What are the 4 major principles? ›

The 4 main ethical principles, that is beneficence, nonmaleficence, autonomy, and justice, are defined and explained.

What are the 7 principles of trustworthy AI? ›

The seven requirements (human agency and oversight; robustness and safety; privacy and data governance; transparency; diversity, non-discrimination and fairness; societal and environmental wellbeing; and accountability) are analyzed from a triple perspective: What each requirement for trustworthy AI is, Why it is ...

What are the 4 stages of AI? ›

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What are the 4 steps of the AI process? ›

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Which is your tool can help you build artificial intelligence applications? ›

List of Artificial Intelligence Tools
  • Scikit Learn.
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  • PyTorch.
  • CNTK.
  • Caffe.
  • Apache MXNet.
  • Keras.
  • OpenNN.

Which Azure tool can help you build artificial intelligence applications Mcq? ›

Answer: a) Azure Machine Learning. Explanation: Azure Machine Learning is used for building and deploying machine learning models. It provides a platform for building, training, and deploying machine learning models at scale, with support for a range of frameworks and programming languages.

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Here are a few examples of Azure's machine learning and AI offerings for specific industries: Healthcare: Azure provides a range of machine learning and AI offerings for the healthcare industry, including Azure Cognitive Services, Azure Synapse Analytics, and Azure Bot Service.

What are the most used AI tools? ›

10 “Best” AI Tools for Business (May 2023)
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  • Jasper. ...
  • Murf. ...
  • HitPaw Photo Enhancer. ...
  • Flick. ...
  • ...
  • Fireflies. ...
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What are some of the main tools in AI? ›

List of AI Tools & Frameworks
  • Scikit Learn.
  • TensorFlow.
  • Theano.
  • Caffe.
  • MxNet.
  • Keras.
  • PyTorch.
  • CNTK.
Mar 3, 2023

Which type of Azure AI service is used to help apps identify and tag people's faces in photographs? ›

The Azure Face service provides AI algorithms that detect, recognize, and analyze human faces in images.

Which Azure service contains pre built machine learning model that you can use in your own code using an API? ›

Cloud-based machine learning products
Cloud optionsWhat it is
Azure Machine LearningManaged platform for machine learning
Azure Cognitive ServicesPre-built AI capabilities implemented through REST APIs and SDKs
Azure SQL Managed Instance Machine Learning ServicesIn-database machine learning for SQL
3 more rows
Dec 16, 2022

Which Azure machine learning feature enables non experts to quickly create an effective machine learning model from data? ›

Artificial Machine Learning – Features

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Because AI Builder is built on top of Azure AI capabilities—and uses your data in Dynamics 365, Microsoft 365, and Microsoft Dataverse—you're able to train and build no-code models to enhance the intelligence of your business apps.

Is Microsoft AI Builder free? ›

AI Builder features that are in preview release status are free to use. You don't need to obtain a license to use AI Builder preview features.

What is the difference between Azure Data Scientist and Azure AI Engineer? ›

A data scientist builds machine learning models on IDE's while an AI engineer builds a deployable version of the model built by data scientists and integrates these models with the end product. AI engineers are also responsible for building secure web service APIs for deploying models if required.

What is responsible AI in Azure machine learning? ›

Build responsible AI solutions with Azure Machine Learning

The responsible AI dashboard consolidates responsible AI capabilities to support deep-dive investigations in your flow of work, while model monitoring helps you optimize performance in production.

Which of the following are examples of key AI technologies? ›

Examples of AI:
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  • Facial Recognition.
  • Chatbots.
  • Digital Assistants.
  • Speech Recognition.
  • Self Driving Vehicles.
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What is an example of artificial intelligence in data security? ›

AI systems in cybersecurity – examples of use

cyber incident response. home security systems. CCTV cameras and crime prevention. credit card fraud detection and risk reduction.


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