Azure Maps: Reimagining location services with cloud and AI innovation

I’m thrilled to share news about the evolution of our enterprise mapping software development kit (SDK) and API offerings. Today, we’re announcing the unification of our enterprise maps offerings under Microsoft Azure Maps. We are combining the technologies and data in Bing Maps for Enterprise with Azure Maps and retiring Bing Maps for Enterprise. This marks a significant milestone as we transform our enterprise maps offerings to focus on creating a platform that empowers our customers to innovate and bring their ideas to life using cutting-edge innovations in AI and cloud—all on a trusted platform.

This unification enables our customers to accelerate innovation by leveraging other Microsoft Azure cloud services while retaining many familiar features from Bing Maps for Enterprise within Azure Maps. Moreover, Azure Maps introduces several features not found in Bing Maps for Enterprise, including advanced service authentication methods, data residency compliance, geolocation, weather information, and custom indoor maps. Unifying our enterprise maps offerings under Azure Maps will greatly simplify our enterprise mapping offerings making it easier for customers to buy and use our services in a way that is consistent with other services at Microsoft.

The concept of “where” has become integral to the decision-making and how organizations navigate through the complex business environment. While the demand for geospatial information continues to grow, the context of “when” and “how” we utilize this information is evolving. At Microsoft, we have observed how technologies in cloud and AI are reshaping how our customers engage with the services we offer. 

Making the transition to Azure Maps

Bing Maps for Enterprise customers will have ample time under their existing and renewed contracts to transition to Azure Maps. Bing Maps for Enterprise will be retired on June 30, 2028, existing Bing Maps for Enterprise customers can continue to license Bing Maps for Enterprise APIs and services until then. We will however no longer be accepting new Bing Maps for Enterprise customers from June 30, 2024. Customers with an enterprise license have until June 30, 2028, to transition to Azure Maps, while customers on the free and basic license for Bing Maps for Enterprise have until June 30, 2025. We are committed to facilitating this transition and look forward to having you join us on this journey.

Simplifying and enhancing through Microsoft products

Currently, millions of developers and businesses have access to geospatial information through a range of Microsoft products—Excel, Power BI in Microsoft Fabric, and Dynamics 365. Customers use our geospatial services to manage wildfires, respond to public emergencies, deliver products to consumers doorsteps, and so much more.

IT managers and developers are increasingly seeking tools that help them adapt to the growing demands for more data and greater agility in the business-critical solutions they build. These demands extend beyond the solutions themselves; they also apply to the building blocks used to construct those solutions. As application complexity rises, our customers are increasingly requesting ways to simplify development, enhance collaboration, and create robust solutions with fewer integration points. By unifying our offerings, we can prioritize investments in supporting the ways that developers are building enterprise applications today.

Integrating with Azure solutions

Our customers seek to deliver business impact by leveraging AI services and tools within their solutions. The inclusion of Azure Maps in the Azure platform brings geospatial data closer to other Azure services, facilitating seamless integration. Azure Maps customers already benefit from AI deeply embedded in industry-leading functions like geocoding. Being part of the Azure ecosystem also streamlines access to complementary services from the Azure Marketplace. At Microsoft Build 2024, we announced the availability of NVIDIA’s cuOpt service within the Azure Marketplace. NVIDIA cuOpt, a world-record holding graphics processing unit (GPU)-accelerated optimization AI microservice, assists teams in solving complex routing problems with multiple constraints. By combining cuOpt with Azure Maps, customers can achieve dynamic routing and real-time re-optimization at scale, driving efficiencies and revenue growth. Azure Maps, alongside the Azure Marketplace, opens up new avenues for innovation, enabling businesses to tackle diverse challenges.

The aggregation of geospatial information with additional data unlocks new insights for businesses, enabling them to reduce operating costs, generate new revenue, and deliver better services to their customers. Azure Maps provides a holistic view, allowing you to understand not only what happened but also where it happened. By leveraging Azure Maps, you can make intelligent decisions and pivot faster by correlating the location of your business elements with your overall business goals. This orientation empowers your team to comprehend the situation and chart a path forward.

Start enhancing your location data today

Understanding “where” translates to knowing how to improve and move ahead. With Azure Maps, your organization gains easier access to, utilization of, and insights from location data. By combining our industry-leading cloud infrastructure with accurate, reliable location data and Microsoft applications like Power BI, you can generate predictive insights for your business.

Source: microsoft.com

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From code to production: New ways Azure helps you build transformational AI experiences

We’re witnessing a critical turning point in the market as AI moves from the drawing boards of innovation into the concrete realities of everyday life. The leap from potential to practical application marks a pivotal chapter, and you, as developers, are key to bringing it to bear.

The news at Build is focused on the top demands we’ve heard from all of you as we’ve worked together to turn this promise of AI into reality:

• Empowering every developer to move with greater speed and efficiency, using the tools you already know and love.
• Expanding and simplifying access to the AI, data—application platform services you need to be successful so you can focus on building transformational AI experiences.
• And, helping you focus on what you do best—building incredible applications—with responsibility, safety, security, and reliability features, built right into the platform. 

I’ve been building software products for more than two decades now, and I can honestly say there’s never been a more exciting time to be a developer. What was once a distant promise is now manifesting—and not only through the type of apps that are possible, but how you can build them.

With Microsoft Azure, we’re meeting you where you are today—and paving the way to where you’re going. So let’s jump right into some of what you’ll learn over the next few days. Welcome to Microsoft Build 2024!

Create the future with Azure AI: offering you tools, model choice, and flexibility  

The number of companies turning to Azure AI continues to grow as the list of what’s possible expands. We’re helping more than 50,000 companies around the globe achieve real business impact using it—organizations like Mercedes-Benz, Unity, Vodafone, H&R Block, PwC, SWECO, and so many others.  

To make it even more valuable, we continue to expand the range of models available to you and simplify the process for you to find the right models for the apps you’re building.

Azure AI Studio, a key component of the copilot stack, is now generally available. The pro-code platform empowers responsible generative AI development, including the development of your own custom copilot applications. The seamless development approach includes a friendly user interface (UI) and code-first capabilities, including Azure Developer CLI (AZD) and AI Toolkit for VS Code, enabling developers to choose the most accessible workflow for their projects.

Developers can use Azure AI Studio to explore AI tools, orchestrate multiple interoperating APIs and models; ground models using their data using retrieval augmented generation (RAG) techniques; test and evaluate models for performance and safety; and deploy at scale and with continuous monitoring in production.

Empowering you with a broad selection of small and large language models  

Our model catalog is the heart of Azure AI Studio. With more than 1,600 models available, we continue to innovate and partner broadly to bring you the best selection of frontier and open large language models (LLMs) and small language models (SLMs) so you have flexibility to compare benchmarks and select models based on what your business needs. And, we’re making it easier for you to find the best model for your use case by comparing model benchmarks, like accuracy and relevance.

I’m excited to announce OpenAI’s latest flagship model, GPT-4o, is now generally available in Azure OpenAI Service. This groundbreaking multimodal model integrates text, image, and audio processing in a single model and sets a new standard for generative and conversational AI experiences. Pricing for GPT-4o is $5/1M Tokens for input and $15/1M Tokens for output.

Earlier this month, we enabled GPT-4 Turbo with Vision through Azure OpenAI Service. With these new models developers can build apps with inputs and outputs that span across text, images, and more, for a richer user experience. 

We’re announcing new models through Models-as-a-Service (MaaS) in Azure AI Studio leading Arabic language model Core42 JAIS and TimeGen-1 from Nixtla are now available in preview. Models from AI21, Bria AI, Gretel Labs, NTT DATA, Stability AI as well as Cohere Rerank are coming soon.  

Phi-3: Redefining what’s possible with SLMs

At Build we’re announcing Phi-3-small, Phi-3-medium, and Phi-3-vision, a new multimodal model, in the Phi-3 family of AI small language models (SLMs), developed by Microsoft. Phi-3 models are powerful, cost-effective and optimized for resource constrained environments including on-device, edge, offline inference, and latency bound scenarios where fast response times are critical. 

Sized at 4.2 billion parameters, Phi-3-vision supports general visual reasoning tasks and chart/graph/table reasoning. The model offers the ability to input images and text, and to output text responses. For example, users can ask questions about a chart or ask an open-ended question about specific images. Phi-3-mini and Phi-3-medium are also now generally available as part of Azure AI’s MaaS offering.

In addition to new models, we are adding new capabilities across APIs to enable multimodal experiences. Azure AI Speech has several new features in preview including Speech analytics and Video translation to help developers build high-quality, voice-enabled apps. Azure AI Search now has dramatically increased storage capacity and up to 12X increase in vector index size at no additional cost to run RAG workloads at scale.

Bring your intelligent apps and ideas to life with Visual Studio, GitHub, and the Azure platform

The tools you choose to build with should make it easy to go from idea to code to production. They should adapt to where and how you work, not the other way around. We’re sharing several updates to our developer and app platforms that do just that, making it easier for all developers to build on Azure. 

Access Azure services within your favorite tools for faster app development

By extending Azure services natively into the tools and environments you’re already familiar with, you can more easily build and be confident in the performance, scale, and security of your apps.  

We’re also making it incredibly easy for you to interact with Azure services from where you’re most comfortable: a favorite dev tool like VS Code, or even directly on GitHub, regardless of previous Azure experience or knowledge. Today, we’re announcing the preview of GitHub Copilot for Azure, extending GitHub Copilot to increase its usefulness for all developers. You’ll see other examples of this from Microsoft and some of the most innovative ISVs at Build, so be sure to explore our sessions.  

Also in preview today is the AI Toolkit for Visual Studio Code, an extension that provides development tools and models to help developers acquire and run models, fine-tune them locally, and deploy to Azure AI Studio, all from VS Code.  

Updates that make cloud native development faster and easier

.NET Aspire has arrived! This new cloud-native stack simplifies development by automating configurations and integrating resilient patterns. With .NET Aspire, you can focus more on coding and less on setup while still using your preferred tools. This stack includes a developer dashboard for enhanced observability and diagnostics right from the start for faster and more reliable app development. Explore more about the general availability of .NET Aspire on the DevBlogs post.   

We’re also raising the bar on ease of use in our application platform services, introducing Azure Kubernetes Services (AKS) Automatic, the easiest managed Kubernetes experience to take AI apps to production. In preview now, AKS Automatic builds on our expertise running some of the largest and most advanced Kubernetes applications in the world, from Microsoft Teams to Bing, XBox online services, Microsoft 365 and GitHub Copilot to create best practices that automate everything from cluster set up and management to performance and security safeguards and policies.

As a developer you now have access to a self-service app platform that can move from container image to deployed app in minutes while still giving you the power of accessing the Kubernetes API. With AKS Automatic you can focus on building great code, knowing that your app will be running securely with the scale, performance and reliability it needs to support your business.

Data solutions built for the era of AI

Developers are at the forefront of a pivotal shift in application strategy which necessitates optimizations at every tier of an application—including databases—since AI apps require fast and frequent iterations to keep pace with AI model innovation. 

We’re excited to unveil new data and analytics features this week designed to assist you in the critical aspects of crafting intelligent applications and empowering you to create the transformative apps of today and tomorrow.

Enabling developers to build faster with AI built into Azure databases 

Vector search is core to any AI application so we’re adding native capabilities to Azure Cosmos DB with Azure Cosmos DB for NoSQL. Powered by DiskANN, a powerful algorithm library, this makes Azure Cosmos DB the first cloud database to offer lower latency vector search at cloud scale without the need to manage servers. 

We’re also announcing the availability of Azure Database for PostgreSQL extension for Azure AI to make bringing AI capabilities to data in PostgreSQL data even easier. Now generally available, this enables developers who prefer PostgreSQL to plug data directly into Azure AI for a simplified path to leverage LLMs and build rich PostgreSQL generative AI experiences.   

Embeddings enable AI models to better understand relationships and similarities between data, which is key for intelligent apps. Azure Database for PostgreSQL in-database embedding generation is now in preview so embeddings can be generated right within the database—offering single-digit millisecond latency, predictable costs, and the confidence that data will remain compliant for confidential workloads. 

Making developer life easier through in-database Copilot capabilities

These databases are not only helping you build your own AI experiences. We’re also applying AI directly in the user experience so it’s easier than ever to explore what’s included in a database. Now in preview, Microsoft Copilot capabilities in Azure SQL DB convert queries into SQL language so developers can use natural language to interact with data. And, Copilot capabilities are coming to Azure Database for MySQL to provide summaries of technical documentation in response to user questions—creating an all-around easier and more enjoyable management experience.

Microsoft Copilot capabilities in the database user experience

Microsoft Fabric updates: Build powerful solutions securely and with ease

We have several Fabric updates this week, including the introduction of Real-Time Intelligence. This completely redesigned workload enables you to analyze, explore, and act on your data in real time. Also coming at Build: the Workload Development Kit in preview, making it even easier to design and build apps in Fabric. And our Snowflake partnership expands with support for Iceberg data format and bi-directional read and write between Snowflake and Fabric’s OneLake.

Spend a day in the life of a piece of data and learn exactly how it moves from its database home to do more than ever before with the insights of Microsoft Fabric, real-time assistance by Microsoft Copilot, and the innovative power of Azure AI.  

Build on a foundation of safe and responsible AI

What began with our principles and a firm belief that AI must be used responsibly and safely has become an integral part of the tooling, APIs, and software you use to scale AI responsibly. Within Azure AI, we have 20 Responsible AI tools with more than 90 features. And there’s more to come, starting with updates at Build.

New Azure AI Content Safety capabilities

We’re equipping you with advanced guardrails that help protect AI applications and users from harmful content and security risks and this week, we’re announcing new  feature for Azure AI Content Safety. Custom Categories are coming soon so you can create custom filters for specific content filtering needs. This feature also includes a rapid option, enabling you to deploy new custom filters within an hour to protect against emerging threats and incidents.  

Prompt Shields and Groundedness Detection are both available in preview now in Azure OpenAI Service and Azure AI Studio help fortify AI safety. Prompt shields mitigate both indirect and jailbreak prompt injection attacks on LLMs, while Groundedness Detection enables detection of ungrounded materials or hallucinations in generated responses.  

Features to help secure and govern your apps and data

Microsoft Defender for Cloud now extends its cloud-native application protection to AI applications from code to cloud. And, AI security posture management capabilities enable security teams to discover their AI services and tools, identify vulnerabilities, and proactively remediate risks. Threat protection for AI workloads in Defender for Cloud leverages a native integration with Azure AI Content Safety to enable security teams to monitor their Azure OpenAl applications for direct and in-direct prompt injection attacks, sensitive data leaks and other threats so they can quickly investigate and respond.

With easy-to-use APIs, app developers can easily integrate Microsoft Purview into line of business apps to get industry-leading data security and compliance for custom-built AI apps. You can empower your app customers and respective end users to discover data risks in AI interactions, protect sensitive data with encryption, and govern AI activities. These capabilities are available for Copilot Studio in public preview and soon (coming in July) will be available in public preview for Azure AI Studio, and via the Purview SDK, so developers can benefit from the data security and compliance controls for their AI apps built on Azure AI.

Two final security notes. We’re also announcing a partnership with HiddenLayer to scan open models that we onboard to the catalog, so you can verify that the models are free from malicious code and signs of tampering before you deploy them. We are the first major AI development platform to provide this type of verification to help you feel more confident in your model choice. 

Second, Facial Liveness, a feature of the Azure AI Vision Face API which has been used by Windows Hello for Business for nearly a decade, is now available in preview for browser. Facial Liveness is a key element in multi-factor authentication (MFA) to prevent spoofing attacks, for example, when someone holds a picture up to the camera to thwart facial recognition systems. Developers can now easily add liveness and optional verification to web applications using Face Liveness, with the Azure AI Vision SDK, in preview.

Our belief in the safe and responsible use of AI is unwavering. You can read our recently published Responsible AI Transparency Report for a detailed look at Microsoft’s approach to developing AI responsibly. We’ll continue to deliver more innovation here and our approach will remain firmly rooted in principles and put into action with built-in features.

Move your ideas from a spark to production with Azure

Organizations are rapidly moving beyond AI ideation and into production. We see and hear fresh examples every day of how our customers are unlocking business challenges that have plagued industries for decades, jump-starting the creative process, making it easier to serve their own customers, or even securing a new competitive edge. We’re curating an industry-leading set of developer tools and AI capabilities to help you, as developers, create and deliver the transformational experiences that make this all possible.

Source: microsoft.com

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Unleashing innovation: The new era of compute powering Azure AI solutions

As AI continues to transform industries, Microsoft is expanding its global cloud infrastructure to meet the needs of developers and customers everywhere. At Microsoft Build 2024, we’re unveiling our latest progress in developing tools and services optimized for powering your AI solutions. Microsoft’s cloud infrastructure is unique in how it provides choice and flexibility in performance and power for customers’ unique AI needs, whether that’s doubling deployment speeds or lowering operating costs.

That’s why we’ve enhanced our adaptive, powerful, and trusted platform with the performance and resilience you’ll need to build intelligent AI applications. We’re delivering on our promise to support our customers by providing them with exceptional cost-performance in compute and advanced generative AI capabilities.

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Powerful compute for general purpose and AI workloads

Microsoft has the expertise and scale to run the AI supercomputers that power some of the world’s biggest AI services, such as Microsoft Azure OpenAI Service, ChatGPT, Bing, and more. Our focus as we continue to expand our AI infrastructure is on optimizing performance, scalability, and power efficiency.

Microsoft takes a systems approach to cloud infrastructure, optimizing both hardware and software to efficiently handle workloads at scale. In November 2023, Microsoft introduced its first in-house designed cloud compute processor, Azure Cobalt 100, which enables general-purpose workloads on the Microsoft Cloud. We are announcing the preview of Azure virtual machines built to run on Cobalt 100 processors. Cobalt 100-based virtual machines (VMs) are Azure’s most power efficient compute offering, and deliver up to 40% better performance than our previous generation of Arm-based VMs. And we’re delivering that same Arm-based performance and efficiency to customers like Elastic, MongoDB, Siemens, Snowflake, and Teradata. The new Cobalt 100-based VMS are expected to enhance efficiency and performance for both Azure customers and Microsoft products. Additionally, IC3, the platform that powers billions of customer conversations in Microsoft Teams, is adopting Cobalt 100 to serve its growing customer base more efficiently, achieving up to 45% better performance on Cobalt 100 VMs.

We’re combining the best of industry and the best of Microsoft in our AI infrastructure. Alongside our custom Azure Cobalt 100 and Maia series and silicon industry partnerships, we’re also announcing the general availability of the ND MI300X VM series, where Microsoft is the first cloud provider to bring AMD’s most powerful Instinct MI300X Accelerator to Azure. With the addition of the ND MI300X VM combining eight AMD MI300X Instinct accelerators, Azure is delivering customers unprecedented cost-performance for inferencing scenarios of frontier models like GPT-4. Our infrastructure supports different scenarios for AI supercomputing, such as building large models from scratch, running inference on pre-trained models, using model as a service providers, and fine-tuning models for specific domains.

One of Microsoft’s advantages in AI is our ability to combine thousands of virtual machines with tens of thousands of GPUs with the best of InfiniBand and Ethernet based networking topologies for supercomputers in the cloud that can run large scale AI workloads to lower costs. With a diversity of silicon across AMD, NVIDIA, and Microsoft’s Maia AI accelerators, Azure’s AI infrastructure delivers the most complete compute platform for AI workloads. It is this combination of advanced AI accelerators, datacenter designs, and optimized compute and networking topology that drive cost efficiency per workload. That means whether you use Microsoft Copilot or build your own copilot apps, the Azure platform ensures you get the best AI performance with optimized cost.

Microsoft is further extending our cloud infrastructure with the Azure Compute Fleet, a new service that simplifies provisioning of Azure compute capacity across different VM types, availability zones, and pricing models to more easily achieve desired scale, performance, and cost by enabling users to control VM group behaviors automatically and programmatically. As a result, Compute Fleet has the potential to greatly optimize your operational efficiency and increase your core compute flexibility and reliability for both AI and general-purpose workloads together at scale.

AI-enhanced central management and security

As businesses continue to expand their computing estate, managing and governing the entire infrastructure can become overwhelming. We keep hearing from developers and customers that they spend more time searching for information and are less productive. Microsoft is focused on simplifying this process through AI-enhanced central management and security. Our adaptive cloud approach takes innovation to the next level with a single, intelligent control plane that spans from cloud to edge, making it easier for customers to manage their entire computing estate in a consistent way. We’re also aiming to improve your experience with managing these distributed environments through Microsoft Copilot in Azure.

We created Microsoft Copilot in Azure to act as an AI companion, helping your teams manage operations seamlessly across both cloud and edge environments. By using natural language, you can ask Copilot questions and receive personalized recommendations related to Azure services. Simply ask, “Why is my app slow?” or “How do I fix this error?” and Copilot will navigate a customer through potential causes and fixes.

Starting today, we will be opening the preview of Copilot in Azure to all customers over the next couple of weeks. With this update, customers can choose to have all their users access Copilot or grant access to specific users or groups within a tenant. With this flexibility to manage Copilot, you can tailor your approach and control which groups of users or departments within your organization have access to it. You can feel secure knowing you can deploy and use the tool in a controlled manner, ensuring it aligns with your organization’s operational standards and security policies.

We’re continually enhancing Copilot and making the product better with every release to help developers be more productive. One of the ways we’ve simplified the developer’s experience is by making databases and analytics services easier to configure, manage, and optimize through AI-enhanced management. Several new skills are available for Azure Kubernetes Service (AKS) in Copilot for Azure that simplify common management tasks, including the ability to configure AKS backups, change tiers, locate YAML files for editing, and construct kubectl commands.

We’ve also added natural language to SQL conversion and self-help for database administration to support your Azure SQL database-driven applications. Developers can ask questions about their data in plain text, and Copilot generates the corresponding T-SQL query. Database administrators can independently manage databases, resolve issues, and learn more about performance and capabilities. Developers benefit from detailed explanations of the generated queries, helping them write code faster.

Lastly, you’ll notice a few new security enhancements to the tool. Copilot now includes Microsoft Defender for Cloud prompting capabilities to streamline risk exploration, remediation, and code fixes. Defender External Attack Surface Management (EASM) leverages Copilot to help surface risk-related insights and convert natural language to corresponding inventory queries across data discovered by Defender EASM. These features make database queries more user-friendly, enabling our customers to use natural language for any related queries. We’ll continue to expand Copilot capabilities in Azure so you can be more productive and focused on writing code.

Cloud infrastructure built for limitless innovation

Microsoft is committed to helping you stay ahead in this new era by giving you the power, flexibility, and performance you need to achieve your AI ambitions. Our unique approach to cloud and AI infrastructure helps us and developers like you meet the challenges of the ever-changing technological landscape head-on so you can continue working efficiently while innovating at scale.

Source: microsoft.com

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Azure Data, AI, and Digital Applications: Harness the Power of Intelligent Apps

In today's rapidly evolving digital landscape, leveraging Azure Data, AI, and Digital Applications is essential for businesses aiming to stay ahead of the curve. By harnessing the power of intelligent apps, organizations can unlock unprecedented levels of efficiency, insight, and innovation. This comprehensive guide explores how Azure's suite of tools and services can transform your business operations and drive significant growth.

Understanding Azure's Data Capabilities

Azure offers a robust set of data services designed to help businesses store, manage, and analyze their data efficiently. These services are critical for building intelligent applications that can provide actionable insights and drive business value.

Azure SQL Database

Azure SQL Database is a fully managed relational database service that offers high performance, scalability, and security. It supports modern cloud applications and facilitates easy migration from on-premises databases. Key features include automated backups, built-in high availability, and advanced security features such as encryption and threat detection.

Azure Cosmos DB

For businesses requiring a globally distributed, multi-model database service, Azure Cosmos DB is an ideal choice. It offers seamless scalability and guarantees low latency, high availability, and consistency. Cosmos DB supports various data models, including document, key-value, graph, and column-family, making it versatile for different application needs.

Azure Data Lake Storage

Azure Data Lake Storage is designed for big data analytics, providing a scalable and secure data lake for high-performance analytics workloads. It integrates with Azure Data Services like Azure Databricks and Azure Synapse Analytics, enabling seamless data ingestion, processing, and analysis.

Harnessing the Power of AI with Azure

Artificial Intelligence (AI) is at the core of transforming business processes and applications. Azure provides a comprehensive suite of AI services that empower businesses to build, deploy, and manage AI models at scale.

Azure Machine Learning

Azure Machine Learning is a cloud-based service that allows data scientists and developers to build, train, and deploy machine learning models. It supports end-to-end machine learning lifecycle management, including data preparation, model training, deployment, and monitoring. With Azure Machine Learning, businesses can leverage automated machine learning (AutoML) to accelerate model development and improve accuracy.

Azure Cognitive Services

Azure Cognitive Services offers pre-built AI models that can be easily integrated into applications. These services include Vision, Speech, Language, and Decision APIs, enabling businesses to incorporate capabilities such as image and video analysis, speech recognition, language understanding, and anomaly detection into their apps without needing deep AI expertise.

Azure Bot Services

Azure Bot Services simplifies the process of building intelligent bots that can interact with users across various channels, including websites, mobile apps, and messaging platforms. These bots leverage natural language processing (NLP) to understand and respond to user queries, enhancing customer engagement and support.

Building Intelligent Applications with Azure

Intelligent applications leverage data and AI to deliver enhanced user experiences, improve decision-making, and drive operational efficiency. Azure provides a range of tools and frameworks to support the development of these applications.

Azure Logic Apps

Azure Logic Apps allows businesses to automate workflows and integrate various systems and services. With its visual designer, users can create workflows that connect cloud-based and on-premises applications, enabling seamless data flow and process automation.

Azure Functions

Azure Functions is a serverless computing service that enables developers to build and deploy event-driven applications. It supports various programming languages and can be triggered by numerous events, such as HTTP requests, database changes, or messages from other services. This flexibility makes it ideal for building microservices and automating backend processes.

Azure App Service

Azure App Service provides a fully managed platform for building, deploying, and scaling web apps and APIs. It supports multiple languages and frameworks, including .NET, Java, Node.js, and Python. With built-in DevOps capabilities, businesses can automate deployment and ensure continuous integration and delivery (CI/CD).

Integrating Data and AI for Maximum Impact

Combining data and AI enables businesses to create intelligent applications that deliver real-time insights and personalized experiences. Azure's integrated services facilitate this integration, ensuring seamless data flow and model deployment.

Azure Synapse Analytics

Azure Synapse Analytics is an analytics service that brings together big data and data warehousing. It provides a unified platform for data ingestion, preparation, management, and serving, allowing businesses to analyze large volumes of data in real-time. With built-in AI and machine learning capabilities, Azure Synapse Analytics enables predictive analytics and advanced data visualization.

Azure Databricks

Azure Databricks is an Apache Spark-based analytics platform optimized for Azure. It supports collaborative data engineering, data science, and machine learning workflows, enabling teams to work together efficiently. Azure Databricks integrates with other Azure services, such as Azure Data Lake Storage and Azure Machine Learning, to streamline the development of intelligent applications.

Azure Data Factory

Azure Data Factory is a data integration service that allows businesses to create, schedule, and orchestrate data workflows. It supports the ingestion of data from various sources, including on-premises databases, cloud-based storage, and SaaS applications. With its robust ETL capabilities, Azure Data Factory ensures that data is processed and transformed efficiently, ready for analysis and AI model training.

Enhancing Security and Compliance

Security and compliance are paramount when dealing with data and AI. Azure offers a comprehensive set of security features and compliance certifications to protect data and ensure regulatory adherence.

Azure Security Center

Azure Security Center provides advanced threat protection across hybrid cloud environments. It offers continuous assessment and security recommendations, helping businesses to strengthen their security posture. With integrated threat intelligence and AI-driven insights, Azure Security Center enables proactive threat detection and response.

Azure Active Directory

Azure Active Directory (Azure AD) is a cloud-based identity and access management service that ensures secure user authentication and authorization. It supports single sign-on (SSO), multi-factor authentication (MFA), and conditional access policies, enhancing security while simplifying user access to applications and data.

Compliance Certifications

Azure meets a wide range of industry and regional compliance standards, including GDPR, HIPAA, ISO 27001, and SOC 2. This extensive compliance portfolio ensures that businesses can confidently handle sensitive data and meet regulatory requirements.

Driving Innovation with Azure

By leveraging Azure's data, AI, and digital application capabilities, businesses can drive innovation and stay competitive in their respective industries. Azure's comprehensive ecosystem supports the development of intelligent applications that can transform customer experiences, optimize operations, and unlock new business opportunities.

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3 ways Microsoft Azure AI Studio helps accelerate the AI development journey

The generative AI revolution is here, and businesses across the globe and across industries are adopting the technology into their work. However, the learning curve for your own AI applications can be steep, with 52% of organizations reporting that a lack of skilled workers is their biggest barrier to implement and scale AI. To reap the true value of generative AI, organizations need tools to simplify AI development, so they can focus on the big picture of solving business needs. Microsoft Azure AI Studio, Microsoft’s generative AI platform, is designed to democratize the AI development process for developers, bringing together the models, tools, services, and integrations you need to get started developing your own AI application quickly.  

“Azure AI Studio improved the experience for creating AI products. We found it mapped perfectly to our needs for faster development and time to market, and greater throughput, scalability, security, and trust.” 

Denis Yarats, Chief Technology Officer and Cofounder, Perplexity.AI 

1. Develop how you want   

The Azure AI Studio comprehensive user interface (UI) and code-first experiences empower developers to choose their preferred method of working, whether it’s through a user-friendly, accessible interface or by diving directly into code. This flexibility is crucial for rapid project initiation, iteration, and collaboration—allowing teams to work in the manner that best suits their skills and project requirements.  

The choice for where to develop was important for IWill Therapy and IWill CARE, a leading online mental health care provider in India, when they started using Azure AI Studio to build a solution to reach more clients. IWill created a Hindi-speaking chatbot named IWill GITA using the cutting-edge products and services included in the Azure AI Studio platform. IWill‘s scalable, AI-powered copilot brings mental health access and therapist-like conversations to people throughout India.

The comprehensible UI in Azure AI Studio made it easy for cross functional teams to get on the same page, allowing workers with less AI development experience to skill up quickly.  

“We found that the Azure user interface removed the communication gap between engineers and businesspeople. It made it easy for us to train subject-matter experts in one day”. 

Ashish Dwivedi, Co-founder and COO, iWill Therapy

Azure AI Studio allows developers to move seamlessly between its friendly user interface and code, with software development kits (SDKs) and Microsoft Visual Studio code extensions for local development experiences. The Azure AI Studio dual approach caters to diverse development preferences, streamlining the process from exploration to deployment, ultimately enabling developers to bring their AI projects to life more quickly and effectively. 

2. Identify the best model for your needs

The Azure AI Studio model catalog offers a comprehensive hub for discovering, evaluating, and consuming foundation models, including a wide array of leading models from Meta, Mistral, Hugging Face, OpenAI, Cohere, Nixtla, G42 Jais, and many more. To enable developers to make an informed decision about which model to use, Azure AI Studio offers tools such as model benchmarking. With model benchmarking, developers can quickly compare models by task using open-source datasets and industry-standard metrics, such as accuracy and fluency. Developers can also explore model cards that detail model capabilities and limitations and try sample inferences to ensure the model is a good fit. 

The Azure AI Studio integration of models from leading partners is already helping customers streamline their development process and accelerating the time to market for their AI solutions. When Perplexity.AI was building their own copilot, a conversational answer engine named Perplexity Ask, Azure AI Studio enabled them to explore various models and to choose the best fit for their solution.  

“Trying out large language models available with Azure OpenAI Service was easy, with just a few clicks to get going. That’s an important differentiator of Azure AI Studio: we had our first prototype in hours. We had more time to try more things, even with our minimal headcount.”  

Denis Yarats, CTO and Cofounder, Perplexity.AI 

3. Streamline your development cycles

Prompt flow in Azure AI Studio is a powerful feature that streamlines the development cycle of generative AI solutions. Developers can develop, test, evaluate, debug, and manage large language model (LLM) flows. You can now monitor their performance, including quality and operational metrics, in real-time, and optimize your flows as needed. Prompt flow is designed to be effortless, with a visual graph for easy orchestration, and integrations with open-source frameworks like LangChain and Semantic Kernel. Prompt flow also facilitates collaboration across teams; multiple users can work together on prompt engineering projects, share LLM assets, evaluate quality and safety of flows, maintain version control, and automate workflows for streamlined large language model operations (LLMOps). 

When Siemens Digital Industries Software wanted to build a solution for its customers and frontline work teams to communicate with operations and engineering teams in real-time to better drive innovation and rapidly address problems as they arise, they looked to Azure AI Studio to create their own copilot. Siemens developers combined Microsoft Teams capabilities with Azure AI Studio and its comprehensive suite of tools, including prompt flow, to streamline workflows that included prototyping, deployment, and production. 

“Our developers really like the UI-first approach of prompt flow and the ease of Azure AI Studio. It definitely accelerated our adoption of advanced machine learning technologies, and they have a lot of confidence now for ongoing AI innovation with this solution and others to come.”  

Manal Dave, Advanced Software Engineer, Siemens Digital Industries Software

Source: microsoft.com

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Accelerate AI innovation with the Microsoft commercial marketplace

With Microsoft Build 2024 right around the corner, I am excited to share how the Microsoft commercial marketplace is extending innovation. As we enter the era of AI, I’m seeing developers utilize the marketplace to use cutting-edge AI tools that accelerate adoption of next-generation solutions for their organizations. At the same time, more customers than ever are using the marketplace to find, try, and adopt new AI solutions quickly. Ultimately, the marketplace—as an extension of the Microsoft Cloud—is how your AI and Microsoft Copilot applications are discovered and deployed.

At the heart of the marketplace is our extensive catalog of solutions from Microsoft’s robust network of partners and software development companies. These solutions are surfaced across our in-product experiences, as well as in our storefronts. Today, the marketplace supports a diverse catalog of AI-powered solutions, including AI-enabled software-as-a-service (SaaS) offerings, Copilot extensions, AI-enabled Microsoft Teams applications, machine learning models from partners such as Mistral AI, and more. While Microsoft supports a number of ways for partners to build AI-based technology, the marketplace is where customers can find all of these solutions from one trusted source.

Partners innovating with AI

We’ve seen a triple-digit percentage increase year-over-year in transactable AI offers published on the Microsoft commercial marketplace. And customers are eager to discover the AI solutions that best fit their unique needs. Visits to AI solution pages on our storefronts have increased more than 700% year-over-year, and AI solutions continue to make up a rapidly growing percentage of sales transacted through the marketplace.

During one of our Microsoft Build sessions, you’ll hear from two partners who are building exciting AI solutions that leverage the Microsoft Cloud and are available now through the marketplace:

• Pinecone helps companies build generative AI applications faster with vector databases. Pinecone can be deployed with Microsoft Azure and across various data sources, models, and frameworks. Pinecone serverless, coming to the marketplace soon, will deliver generative AI applications even faster at up to 50 times lower cost.
• UiPath’s Business Automation Platform enables customers to supercharge productivity, transform user experiences, and innovate faster with AI-powered automations. With more than 80 platform integrations, customers can tap into UiPath enterprise-grade automation capabilities directly from Microsoft 365, Azure, Microsoft Dynamics 365, and Copilot.

Smarter purchasing through the marketplace

Microsoft is the only company that can support the entire ecosystem of AI—from the infrastructure and data layers all the way to the front-end user experience with Copilot. This enables developers to build next-generation AI tools quickly and for partners to connect their AI solutions to the Microsoft customer base through the marketplace—making it efficient and scalable for organizations to discover and adopt AI broadly. During this AI transformation, the Microsoft commercial marketplace is how we are enabling businesses of every size to access the solutions they need.

With rapid technological development, it has become even more important to balance the need to innovate with meeting business requirements. By aligning SaaS strategy to the marketplace, organizations can unify their data to get the most out of their AI investments:

• Try before you buy. The marketplace allows you to try new solutions before you make a larger commitment. Free trials or direct purchases of a small number of licenses can ensure the technology works for your organization before making a big investment. The marketplace also supports proofs-of-concept with private offers, so you can further vet solutions before widescale adoption.
• Innovate faster. Centralizing cloud portfolios helps you decrease time-to-value. AI solutions are part of one comprehensive catalog and pre-certified to run on Azure. Vendors can be onboarded instantly, and billing is simplified through a single invoice.
• Maximize investments. Organizations can optimize cloud spend by counting the solutions they need towards their Azure consumption commitment. Microsoft automatically counts 100% of eligible offers towards your commitment, helping unlock discounts on Azure infrastructure.
• Create alignment across teams. The marketplace makes it easier to keep teams aligned using approved solutions. With private Azure marketplace, an administrator can pre-select approved solutions so your team can compliantly access what they need. If a needed solution is not yet approved, team members can easily request it be added, empowering innovation with the right guardrails to safeguard investments. 

All of this translates into huge savings of time and money. In a 2023 Total Economic Impact™ study commissioned by Microsoft, Forrester Consulting found the marketplace delivers customers a three-year 587% return on investment (ROI) with a payback period of less than six months.

Join us at Microsoft Build

We’re excited to be accelerating the era of AI by setting the standard for the creation and commerce of AI solutions. For developers building new solutions, I encourage you to check out tools and benefits from ISV Success that will help you realize these innovations. Partners can also use Marketplace Rewards to accelerate their marketplace growth and generate high impact opportunities.

Source: microsoft.com

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Introducing GPT-4o: OpenAI’s new flagship multimodal model now in preview on Azure

Microsoft is thrilled to announce the launch of GPT-4o, OpenAI’s new flagship model on Azure AI. This groundbreaking multimodal model integrates text, vision, and audio capabilities, setting a new standard for generative and conversational AI experiences. GPT-4o is available now in Azure OpenAI Service, to try in preview, with support for text and image.

A step forward in generative AI for Azure OpenAI Service

GPT-4o offers a shift in how AI models interact with multimodal inputs. By seamlessly combining text, images, and audio, GPT-4o provides a richer, more engaging user experience.

Launch highlights: Immediate access and what you can expect

Azure OpenAI Service customers can explore GPT-4o’s extensive capabilities through a preview playground in Azure OpenAI Studio starting today in two regions in the US. This initial release focuses on text and vision inputs to provide a glimpse into the model’s potential, paving the way for further capabilities like audio and video.

Efficiency and cost-effectiveness

GPT-4o is engineered for speed and efficiency. Its advanced ability to handle complex queries with minimal resources can translate into cost savings and performance.

Potential use cases to explore with GPT-4o

The introduction of GPT-4o opens numerous possibilities for businesses in various sectors: 

1. Enhanced customer service: By integrating diverse data inputs, GPT-4o enables more dynamic and comprehensive customer support interactions.
2. Advanced analytics: Leverage GPT-4o’s capability to process and analyze different types of data to enhance decision-making and uncover deeper insights.
3. Content innovation: Use GPT-4o’s generative capabilities to create engaging and diverse content formats, catering to a broad range of consumer preferences.

Exciting future developments: GPT-4o at Microsoft Build 2024 

We are eager to share more about GPT-4o and other Azure AI updates at Microsoft Build 2024, to help developers further unlock the power of generative AI.

Source: microsoft.com

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Bringing generative AI to Azure network security with new Microsoft Copilot integrations

Today we are excited to announce the Azure Web Application Firewall (WAF) and Azure Firewall integrations in the Microsoft Copilot for Security standalone experience. This is the first step we are taking toward bringing interactive, generative AI-powered capabilities to Azure network security.

Copilot empowers teams to protect at the speed and scale of AI by turning global threat intelligence (78 trillion or more security signals), industry best practices, and organizations’ security data into tailored insights. With the growing cost of security breaches, organizations need every advantage to protect against skilled and coordinated cyber threats. To see more and move faster, they need generative AI technology that complements human ingenuity and refocuses teams on what matters.

• Experienced security analysts were 22% faster with Copilot.
• They were 7% more accurate across all tasks when using Copilot.
• And, most notably, 97% said they want to use Copilot the next time they do the same task.

Generative AI for Azure network security

Azure WAF and Azure Firewall are critical security services that many Microsoft Azure customers use to protect their network and applications from threats and attacks. These services offer advanced threat protection using default rule sets as well as detection and protection against sophisticated attacks using rich Microsoft threat intelligence and automatic patching against zero-day vulnerabilities. These systems process huge volumes of packets, analyze signals from numerous network resources, and generate vast amounts of logs. To reason over terabytes of data and cut through the noise to detect threats, analysts spend several hours if not days performing manual tasks. In addition to the scale of data there is a real shortage of security expertise. It is difficult to find and train cybersecurity talent and these staff shortages slow down responses to security incidents and limit proactive posture management. 

With our announcement of Azure WAF and Azure Firewall integrations in Copilot for Security, organizations can empower their analysts to triage and investigate hyperscale data sets seamlessly to find detailed, actionable insights and solutions at machine speeds using a natural language interface with no additional training. Copilot automates manual tasks and helps upskill Tier 1 and Tier 2 analysts to perform tasks that would otherwise be reserved for more experienced Tier 3 or Tier 4 professionals, redirecting expert staff to the hardest challenges, thus elevating the proficiency of the entire team. Copilot can also easily translate threat insights and investigations into natural language summaries to quickly inform colleagues or leadership. The organizational efficiency gained by Copilot summarizing vast data signals to generate key insights into the threat landscape enables analysts to outpace adversaries in a matter of minutes instead of hours or days.

How Copilot for Security works with the Azure Firewall and Azure WAF plugins.

Azure Web Application Firewall integration in Copilot

Today, Azure WAF generates detections for a variety of web application and API security attacks. These detections generate terabytes of logs that are ingested into Log Analytics. While the logs give insights into the Azure WAF actions, it is a non-trivial and time-consuming activity for an analyst to understand the logs and gain actionable insights.

The Azure WAF integration in Copilot for Security helps analysts perform contextual analysis of the data in minutes. Specifically, it synthesizes data from Azure Diagnostics logs to generate summarization of Azure WAF detections tailored to each customer’s environment. The key capabilities include investigation of security threats—including analyzing WAF rules triggered, investigating malicious IP addresses, analyzing SQL Injection (SQLi) and Cross-site scripting (XSS) attacks blocked by WAF, and natural language explanations for each detection.

By asking a natural-language question about these attacks, the analyst receives a summarized response that includes details about why that attack occurred and equips the analyst with enough information to investigate the issue further. In addition, with the assistance of Copilot, analysts can retrieve information on the most frequently offending IP addresses, identify top malicious bot attacks, and pinpoint the managed and custom Azure WAF rules that have been triggered most frequently within their environment.

A sneak peek at the Azure WAF integration in Copilot for Security.

Azure Firewall integration in Copilot

Azure Firewall intercepts and blocks malicious traffic using the intrusion detection and prevention system (IDPS) feature today. However, when analysts need to perform a deeper investigation of the threats that Azure Firewall catches using this feature, they need to do this manually—which is a non-trivial and time-consuming task. The Azure Firewall integration in Copilot helps analysts perform these investigations with the speed and scale of AI.

The first step in an investigation is to pick a specific Azure Firewall and see the threats it has intercepted. Analysts today spend hours writing custom queries or navigating through several manual steps to retrieve threat information from Log Analytics workspaces. With Copilot, analysts just need to ask about the threats they’d like to see, and Copilot will present them with the requested information.

The next step is to better understand the nature and impact of these threats. Today, analysts must retrieve additional contextual information such as geographical location of IPs, threat rating of a fully qualified domain name (FQDN), details of common vulnerabilities and exposures (CVEs) associated with an IDPS signature, and more manually from various sources. This process is slow and involves a lot of effort. Copilot pulls information from the relevant sources to enrich your threat data in a fraction of the time.

Once a detailed investigation has been performed for a single Azure Firewall and single threat, analysts would like to determine if these threats were seen elsewhere in their environment. All the manual work they performed for an investigation for a single Azure Firewall is something they would have to repeat fleet wide. Copilot can do this at machine speed and help correlate this information with other security products integrated with Copilot to better understand how attackers are targeting their entire infrastructure.

A sneak peek at the Azure Firewall integration in Copilot for Security.

Looking forward

The future of technology is here, and users will increasingly expect their network security products to be AI enabled; and Copilot positions organizations to fully leverage the opportunities presented by the emerging era of generative AI. The integrations announced today combine Microsoft’s expertise in security with state-of-the-art generative AI packaged together in a solution built with security, privacy, and compliance at its heart to help organizations better defend themselves from attackers while keeping their data completely private.

Getting access

We look forward to continuing to integrate Azure network security into Copilot to make it easier for our customers to be more productive and be able to quickly analyze threats and mitigate vulnerabilities ahead of their adversaries. These new capabilities in Copilot for Security are already being used internally by Microsoft and a small group of customers. Today, we’re excited to announce the upcoming public preview. We expect to launch the preview for all customers for Azure WAF and Azure Firewall at Microsoft Build on May 21, 2024. In the coming weeks, we’ll continuously add new capabilities and make improvements based on your feedback.

Source: microsoft.com    

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Harnessing the power of intelligent apps through modernization

In this era of AI, the pace of innovation is accelerating at an unprecedented rate, triggering a paradigm shift in how businesses think of and deliver digital experiences to their customers. More applications and digital experiences are getting enhanced with AI every day. In fact, 81% of surveyed organizations believe AI will give them a competitive edge. Applications are where AI comes to life and are the path to driving business impact.

However, AI isn’t just a catalyst for new, intelligent services. It is shifting the way applications are built and deployed, and placing new requirements on businesses to modernize their infrastructure, processes and application architectures. Simply put, many of the legacy models for supporting applications will not work for the wave of AI-enhanced, data intensive applications that are arriving in this new era.

Modernization: An imperative for innovating with AI 

The focus and demand for AI is creating an urgency to modernize existing applications, creating new opportunities to innovate with AI and enhance business processes. Businesses are accelerating modernization efforts to meet the demands of their digital and AI transformation. They are adopting cloud native architectures and principles to better facilitate AI adoption and creating a flexible platform that is purpose built for AI and ensures all applications are served with the optimal performance, scale, and security. In her talk on the May 8, 2024 Azure Application Modernization Webinar, Jessica Hawk, Product Marketing Corporate Vice President for Microsoft Azure Data, AI, and Digital Applications sheds more light on Driving Innovation Through Modernization in the Era of AI.

Modernization goes beyond just lifting and shifting application workloads to cloud virtual machines. Modernization is optimizing those applications for the cloud and innovating by infusing AI to make them more intelligent.

• Scalability and flexibility: AI applications have higher requirements for scale and flexibility due to data intensity, the complexities of AI models, the required business impact, and the need for agile development practices to support the fast pace of innovation. If they fail to meet these requirements, AI apps fall short of the expectations and value they drive for businesses. Whether building new applications or modernizing existing ones, cloud platform services offer the flexibility to scale needed to meet business needs, ensuring businesses can respond swiftly to opportunities and customer needs. 
• Data integration: Intelligent applications and datea are inextricably linked. A a critical building block for intelligent apps is access and integration with organizations’ business data. Modernizing to be cloud-centric enables better access to the data needed to drive intelligent apps, even across data sources. This integration is crucial for AI models that drive intelligent applications, enabling them to deliver richer insights and more personalized experiences to customers.
• Innovation and competitive advantage: Perhaps the greatest promise for intelligent applications is the ability to accelerate or enhance innovation. But achieving this promise requires a union of platform and developer services that enables developers to build at speed, freely access the services they need, and adapt without the friction and complexity of traditional infrastructures. The cloud is an enabler for innovation, providing the tools and services necessary for developer teams to build and deploy intelligent application easily. Modernizing legacy applications to the cloud not only provides the needed scalability and flexibility, it also provides development teams with the right tools and services to build and deploy intelligent apps quickly.
• Enhanced security: As with all paradigm shifts in applications, the advent of intelligent apps necessitates rethinking the way that we infuse security into the application, data, and platform—with an unrelenting focus on protecting business and customers. Legacy applications unfortunately aren’t the most secure, modernizing them affords businesses the security needed for their business and customer’s data.

Furthermore, we know the path to modernization isn’t all rosy and easy, with a lot of organizations not yet achieving the goals they set for their modernization projects. Even with the incredible pace of innovation in intelligent apps, we must remember that we are just at the beginning of a massive, long-term transformation in how we build, deliver, and support applications. The market is still learning and evolving and thus businesses need the right strategy, process, and platform to support innovation needed for this era and beyond.

Azure: The platform for AI innovation 

Microsoft is committed to making Azure the best place for all your applications—from the new services you’re building to the existing applications slated for modernization. Architected for the demands of AI, Azure brings together best-in-class apps, data, and AI services for your entire application estate, enabling you to modernize at your own pace, helping developers of all skills work quickly to build new services, and supporting every app with the security, performance, and scale needed to run your most critical business services in production. An IDC study showed that customers that migrated and modernized their application on Azure reduced their overall development lifecycle for new applications by 46% and spent 51% less time deploying new features.

“The Azure Application Platform provides familiar technologies that app developers are used to, but gives them support for the scale and reliability they need to deliver useful applications with generative AI,” said Amanda Silver, Corporate Vice President and Head of Product for Microsoft’s Developer Division, speaking about powering future innovation with Azure Application Platform at the Application Modernization Webinar.

Microsoft is a leader in security and compliance, with significant investments made in cybersecurity and a large team of security experts making a top choice for enterprise security. The Azure platform is backed by this enterprise security. Security and compliance are infused in the innovations of the platform to ensure enterprise security across every layer of the stack from application code to the data layer as well as standards of responsible AI practices across all the vast portfolio of Azure AI services. That same study from IDC states that customers who migrated and modernized to Azure gained up to 46% more efficiency across security teams and up to 27% fewer security breaches.

Coles modernizes customer shopping experience with Azure 

Coles, the Australian grocery retailer, is one of the many customers leveraging the power of Azure to power innovation and drive significant growth. With the need to deliver improved and enhanced customer experiences across all channels at improved speed—Coles embarked on a modernization journey with Azure. Their modernization not only revamped the digital experiences they provide to their customers but also improved the speed at which they delivered and shipped new and innovative digital experiences to their customers.

“Instead of doing six-week releases, we now do weekly releases. And the build time now takes roughly 10 to 15 minutes, compared to what used to be a couple of hours.”

Anton Vishnyakov, Senior Engineer and Manager for Platform Engineering at Coles

Source: microsoft.com

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Microsoft is a Leader in the 2024 Gartner Magic Quadrant for Cloud AI Developer Services

We are excited to announce that Microsoft has been named a Leader for the fifth 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’re pleased by the recognition from Gartner as we continue to prioritize investments across our Azure AI portfolio. We’re at the forefront of empowering customers on their generative AI journey—offering a feature rich, unified platform that provides cutting-edge models, services, and fully integrated tooling to accelerate innovation. It’s why over 65% of the Fortune 500 now use Azure OpenAI Service, and tens of thousands of other organizations across industries and around the world are innovating with Azure AI.

Cutting-edge APIs and models 

Azure AI has continued to push the boundaries of innovation, providing customers with cutting-edge APIs and models that are transforming industries and empowering businesses to achieve more. Our Azure AI services are feature rich and bring the capabilities for responsible AI solutions to create, receive, and respond with images, videos, and audio—enabling more natural interactions with technology, and expanding the possibilities for generative AI applications.    

Azure AI’s model catalog is a testament to Microsoft’s commitment to bringing the most advanced AI models to our customers, fostering an environment of innovation and growth. Through industry leaders like OpenAI, Mistral AI, Cohere, Hugging Face, Meta, and more, the model catalog makes available a diverse selection of over 1,600 large language, small language, and vision models accelerating the availability and diversity of AI models for customers, allowing them to choose the best performance and cost options for their applications.  

Albert Heijn, the leading supermarket chain in the Netherlands, is using Azure AI’s cutting-edge APIs and models to power a series of initiatives covering use cases from customer personalization to demand forecast and food waste projects. One of these applications is “Scan my Recipe,” powered by Microsoft Azure AI Vision and Azure OpenAI Service, the tool allows users to conveniently add all the ingredients from a cookbook recipe to their shopping cart, making healthy cooking more accessible.  

“Because we rely heavily on Azure OpenAI and other Azure services for the use of generative AI, we are co-creating with Microsoft and exploring all the technological possibilities together.” 

Noortje van Genugten, Vice President, Product Operations, Albert Heijn 

Fully integrated tooling 

In the fast-paced realm of AI development, developers need a comprehensive ecosystem of tools that support the development lifecycle, from concept to production and ongoing monitoring. Azure AI’s integrated tooling brings together all the tools you need for building your generative AI solution. Retrieval augmented generation, powered by Azure AI Search, enhances AI models by grounding them securely on your chosen data sources, allowing for more contextually relevant and accurate outputs. Fine-tuning further refines these models with specific data, improving their performance on tasks. Prompt flow orchestrates the development process, enabling efficient experimentation and iteration, while model evaluations offer a robust mechanism to assess and improve model performance systematically. Azure AI Content Safety includes a set of customizable filters for both human- and AI-generated content to help ensure safe generative AI experiences for employees, customers, and partners—free of harmful content. Together, these tools streamline the path from AI conception to deployment, enabling rapid innovation and providing the tools to safeguard your applications across the generative AI lifecycle. 

Telstra, Australia’s leading telecommunications and technology company, is using retrieval augmented generation, powered by Azure AI Search, to ground their generative AI solutions securely on their own data. Their new solutions help frontline workers and customer service agents respond to customers more quickly and effectively with Ask Telstra, which puts technical information at the agents’ fingertips, and One Sentence Summary, which instantly brings agents up-to-speed on customer history.  

“90% of customer service agents who tested One Sentence Summary increased their effectiveness. Their calls required 20% less follow-up….Ask Telstra was judged by 84% of the agents using it to positively impact customer interactions.” 

Rohit Lakhotia, General Manager of Customer and Channel AI, Telstra 

Unified AI development platform  

Today’s generative AI solutions, like custom copilots, require various APIs, models, development tooling, responsible AI features, monitoring, and governance. Stitching together disparate products can be a roadblock, and a drain on developer’s time. That’s why we’re bringing together all the needed services and tools for enterprise generative AI, simplifying the creation, testing, and deployment of AI applications, with our investment in Azure AI Studio.   

Azure AI Studio emphasizes a code-first approach, enabling developers to swiftly move from concept to production while adhering to responsible AI practices. It’s a collaborative space that streamlines the development lifecycle, ensuring security, privacy, and compliance are at the forefront of innovation. 

Together, these tools form a robust ecosystem within Azure AI Studio, empowering customers to develop transformative AI-powered applications with confidence and agility.

Source: microsoft.com

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