It’s inspiring to see how customers continue to reimagine how they work with the help of AI, which is more important today than ever. Our customers are finding innovative ways to deliver crisis management solutions, drive cost-savings, redefine customer engagement, and accelerate decision-making.
Here are some notable examples we’ve recently seen:
Scaling crisis management
On the frontlines, first responders rely on Azure AI to scale their triage process to address the overwhelming number of people needing care and to ease volume in the system. For example, healthcare providers have created more than 1,400 bots using our Healthcare Bot service, helping more than 27 million people access critical healthcare information. The U.S. Centers for Disease Control and Prevention released a COVID-19 assessment bot that is powered by Azure Bot Service. Motorola Solutions uses Azure Bot Service, as well as speech and language services, in its own voice assistant for public safety, ViQi, to help 911 dispatchers and first responders focus on what matters most.
Azure AI is also helping customers optimize their operations to reduce costs. KPMG built a risk and fraud analytics solution using our speech and language services to streamline call center transcription and translation—cutting time,
As AI reaches critical momentum across industries and applications, it becomes essential to ensure the safe and responsible use of AI. AI deployments are increasingly impacted by the lack of customer trust in the transparency, accountability, and fairness of these solutions. Microsoft is committed to the advancement of AI and machine learning (ML), driven by principles that put people first, and tools to enable this in practice.
In collaboration with the Aether Committee and its working groups, we are bringing the latest research in responsible AI to Azure. Let’s look at how the new responsible ML capabilities in Azure Machine Learning and our open-source toolkits empower data scientists and developers to understand ML models, protect people and their data, and control the end-to-end ML process.
As ML becomes deeply integrated into our daily business processes, transparency is critical. Azure Machine Learning helps you to not only understand model behavior but also assess and mitigate unfairness.
Interpret and explain model behavior
Model interpretability capabilities in Azure Machine Learning, powered by the InterpretML toolkit, enable developers and data scientists to understand model behavior and provide model explanations to business stakeholders and customers.
Use model interpretability to:
Build accurate ML models.
Digital transformation in manufacturing has the potential to increase annual global economic value by $4.5 trillion according to the IDC MarketScape.iWith so much upside, manufacturers are looking at how technologies like IoT, machine learning, and artificial intelligence (AI) can be used to optimize supply chains, improve factory performance, accelerate product innovation, and enhance service offerings.
Digital transformation starts by collecting data from machines on the plant floor, assets in the supply chain, or products being used by customers. This data can be combined with other business data and then modeled and analyzed to gain actionable insights.
Let’s take a look at three manufacturers—Festo, Kao, and AkzoNobel—and see how each one is using technologies like IoT, machine learning, and AI to accelerate their digital transformation.
Providing predictive maintenance as a service
Based in Germany, Festo sells electric and pneumatic drive solutions to 300,000 customers in 176 countries. The company’s goal is to increase uptime for customers by providing predictive maintenance offerings as software as a service (SaaS) offerings. Festo’s strategy is to connect machines to the cloud with Azure IoT and then enable customers to visualize data along the entire value chain.
One of the first SaaS offerings is Festo
https://azure.microsoft.com/blog/extending-the-power-of-azure-ai-to-microsoft-365-users/Today, Yusuf Mehdi, Corporate Vice President of Modern Life and Devices, announced the availability of new Microsoft 365 Personal and Family subscriptions. In his blog, he shared a few examples of how Microsoft 365 is innovating to deliver experiences powered READ MORE
If you use Office 365, you have likely seen the Microsoft PowerPoint Designer appear to offer helpful ideas when you insert a picture into a PowerPoint slide. You may also have found it under the Home tab in the ribbon. In either case, Designer provides users with redesigned slides to maximize their engagement and visual appeal. These designs include different ways to represent your text as diagrams, layouts to make your images pop, and now it can even surface relevant icons and images to bring your slides to the next level. Ultimately, it saves users time while enhancing their slides to create stunning, memorable, and effective presentations.
Designer uses artificial intelligence (AI) capabilities in Office 365 to enable users to be more productive and unlock greater value from PowerPoint. It applies AI technologies and machine learning based techniques to suggest high-quality professional slide designs. Content on slides such as images, text, and tables are analyzed by Designer and formatted based on professionally designed templates for enhanced effectiveness and visual appeal.
The data science team, working to grow and improve Designer, is comprised of five data scientists with diverse backgrounds in applied machine learning and software engineering. They strive to continue
Azure Container Registry announces preview support for Azure Private Link, a means to limit network traffic of resources within the Azure network.
With Private Link, the registry endpoints are assigned private IP addresses, routing traffic within a customer-defined virtual network. Private network support has been one of the top customer asks, allowing customers to benefit from the Azure management of their registry while benefiting from tightly controlled network ingress and egress.
Private Links are available across a wide range of Azure resources with more coming soon, allowing a wide range of container workloads with the security of a private virtual network.
Private Endpoints and Public Endpoints
Private Link provides private endpoints to be available through private IPs. In the above case, the contoso.azurecr.io registry has a private IP of 10.0.0.6 which is only available to resources in contoso-aks-eastus-vnet. This allows the resources in this VNet to securely communicate. The other resources may be restricted to resources only within the VNet.
At the same time, the public endpoint for the contoso.azurecr.io registry may still be public for the development team. In a coming release, Azure Container Registry (ACR) Private Link will support disabling the public endpoint, limiting access to
Microsoft 365 applications are so commonplace that it’s easy to overlook some of the amazing capabilities that are enabled with breakthrough technologies, including artificial intelligence (AI). Microsoft Outlook is an email client that helps you work efficiently with email, calendar, contacts, tasks, and more in a single place.
To help users be more productive and deliberate in their actions while emailing, the web version of Outlook and the Outlook for iOS and Android app have introduced suggested replies, a new feature powered by Azure Machine Learning service. Now when you receive an email message that can be answered with a quick response, Outlook on the web and the Outlook mobile suggest three response options that you can use to reply with only a couple of clicks or taps, helping people communicate in both their workplace and personal life, by reducing the time and effort involved in replying to an email.
The developer team behind suggested replies is comprised of data scientists, designers, and machine learning engineers with diverse backgrounds who are working to improve the lives of Microsoft Outlook users by expediting and simplifying communications. They are at the forefront of applying cutting-edge natural language processing (NLP) and machine
Enterprises today are transforming their businesses using Machine Learning (ML) to develop a lasting competitive advantage. From healthcare to transportation, supply chain to risk management, machine learning is becoming pervasive across industries, disrupting markets and reshaping business models.
Organizations need the technology and tools required to build and deploy successful Machine Learning models and operate in an agile way. MLOps is the key to making machine learning projects successful at scale. What is MLOps ? It is the practice of collaboration between data science and IT teams designed to accelerate the entire machine lifecycle across model development, deployment, monitoring, and more. Microsoft Azure Machine Learning enables companies to fully embrace MLOps practices will and truly be able to realize the potential of AI in their business.
One great example of a customer transforming their business with Machine Learning and MLOps is TransLink. They support Metro Vancouver’s transportation network, serving 400 million total boarding’s from residents and visitors as of 2018. With an extensive bus system spanning 1,800 sq. kilometers, TransLink customers depend heavily on accurate bus departure times to plan their journeys.
To enhance customer experience, TransLink deployed 18,000 different sets of Machine Learning models to better predict bus departure
https://azure.microsoft.com/blog/azure-machine-learning-ml-for-all-skill-levels/Enterprises today are adopting artificial intelligence (AI) at a rapid pace to stay ahead of their competition, deliver innovation, improve customer experiences, and grow revenue. AI and machine learning applications are ushering in a new era of transformation across industries READ MORE
https://azure.microsoft.com/blog/automated-machine-learning-and-mlops-with-azure-machine-learning/Azure Machine Learning is the center for all things machine learning on Azure, be it creating new models, deploying models, managing a model repository, or automating the entire CI/CD pipeline for machine learning. We recently made some amazing announcements on READ MORE