Bis zu 3.500 Filme oder 1,75 Millionen Lieder ließen sich auf eine kleine Quarzglasplatte speichern. Strom würden die Platten lauf Microsoft ebenfalls nicht benötigen. (Microsoft, Speichermedien)
Quelle: Golem
Google hat sein KI-gestütztes Verkehrsmanagementsystem Project Green Light erweitert, das in zahlreichen Städten die Autoreisezeiten reduzieren soll. (Auto, Google)
Quelle: Golem
Außerdem werden SkySQL und Xpand von MariaDB eingestellt. (MariaDB, SkySQL)
Quelle: Golem
Ankers neues Solarkraftwerk hat zwei 540-Wp-Module und einen Mikrowechselrichter, der schon für 800 Watt bereit ist. (Balkonkraftwerk, Solarenergie)
Quelle: Golem
Generative AI is no longer just a buzzword or something that’s just “tech for tech’s sake.” It’s here and it’s real, today, as small and large organizations across industries are adopting generative AI to deliver tangible value to their employees and customers. This has inspired and refined new techniques like prompt engineering, retrieval augmented generation, and fine-tuning so organizations can successfully deploy generative AI for their own use cases and with their own data. We see innovation across the value chain, whether it’s new foundation models or GPUs, or novel applications of preexisting capabilities, like vector similarity search or machine learning operations (MLOps) for generative AI. Together, these rapidly evolving techniques and technologies will help organizations optimize the efficiency, accuracy, and safety of generative AI applications. Which means everyone can be more productive and creative!
We also see generative AI inspiring a wellspring of new audiences to work on AI projects. For example, software developers that may have seen AI and machine learning as the realm of data scientists are getting involved in the selection, customization, evaluation, and deployment of foundation models. Many business leaders, too, feel a sense of urgency to ramp up on AI technologies to not only better understand the possibilities, but the limitations and risks. At Microsoft Azure, this expansion in addressable audiences is exciting, and pushes us to provide more integrated and customizable experiences that make responsible AI accessible for different skillsets. It also reminds us that investing in education is essential, so that all our customers can yield the benefits of generative AI—safely and responsibly—no matter where they are in their AI journey.
We have a lot of exciting news this month, much of it focused on providing developers and data science teams with expanded choice in generative AI models and greater flexibility to customize their applications. And in the spirit of education, I encourage you to check out some of these foundational learning resources:
For business leaders
Building a Foundation for AI Success: A Leader’s Guide: Read key insights from Microsoft, our customers and partners, industry analysts, and AI leaders to help your organization thrive on your path to AI transformation.
Transform your business with Microsoft AI: In this 1.5-hour learning path, business leaders will find the knowledge and resources to adopt AI in their organizations. It explores planning, strategizing, and scaling AI projects in a responsible way.
Career Essentials in Generative AI: In this 4-hour course, you will learn the core concepts of AI and generative AI functionality, how you can start using generative AI in your own day-to-day work, and considerations for responsible AI.
For builders
Introduction to generative AI: This 1-hour course for beginners will help you understand how LLMs work, how to get started with Azure OpenAI Service, and how to plan for a responsible AI solution.
Start Building AI Plugins With Semantic Kernel: This 1-hour course for beginners will introduce you to Microsoft’s open source orchestrator, Semantic Kernel, and how to use prompts, semantic functions, and vector databases.
Work with generative AI models in Azure Machine Learning: This 1-hour intermediate course will help you understand the Transformer architecture and how to fine-tune a foundation model using the model catalog in Azure Machine Learning.
Access new, powerful foundation models for speech and vision in Azure AI
We’re constantly looking for ways to help machine learning professionals and developers easily discover, customize, and integrate large pre-trained AI models into their solutions. In May, we announced the public preview of foundation models in the Azure AI model catalog, a central hub to explore collections of various foundation models from Hugging Face, Meta, and Azure OpenAI Service. This month brought another milestone: the public preview of a diverse suite of new open-source vision models in the Azure AI model catalog, spanning image classification, object detection, and image segmentation capabilities. With these models, developers can easily integrate powerful, pre-trained vision models into their applications to improve performance for predictive maintenance, smart retail store solutions, autonomous vehicles, and other computer vision scenarios.
In July we announced that the Whisper model from OpenAI would also be coming to Azure AI services. This month, we officially released Whisper in Azure OpenAI Service and Azure AI Speech, now in public preview. Whisper can transcribe audio into text in an astounding 57 languages. The foundation model can also translate all those languages to English and generate transcripts with enhanced readability, making it a powerful complement to existing capabilities in Azure AI. For example, by using Whisper in conjunction with the Azure AI Speech batch transcription application programming interface (API), customers can quickly transcribe large volumes of audio content at scale with high accuracy. We look forward to seeing customers innovate with Whisper to make information more accessible for more audiences.
Discover vision models in Azure AI model catalog.
Operationalize application development with new code-first experiences and model monitoring for generative AI
As generative AI adoption accelerates and matures, MLOps for LLMs, or simply “LLMOps,” will be instrumental in realizing the full potential of this technology at enterprise scale. To expedite and streamline the iterative process of prompt engineering for LLMs, we introduced our prompt flow capabilities in Azure Machine Learning at Microsoft Build 2023— providing a way to design, experiment, evaluate, and deploy LLM workflows. This month, we announced a new code-first prompt flow experience through our SDK, CLI, and VS Code extension available in preview. Now, teams can more easily apply rapid testing, optimization, and version control techniques to generative AI projects, for more seamless transitions from ideation to experimentation and, ultimately, production-ready applications.
Of course, once you deploy your LLM application in production, the job isn’t finished. Changes in data and consumer behavior can influence your application over time, resulting in outdated AI systems, which negatively impact business outcomes and expose organizations to compliance and reputational risks. This month, we announced model monitoring for generative AI applications, now available in preview in Azure Machine Learning. Users can now collect production data, analyze key safety, quality, and token consumption metrics on a recurring basis, receive timely alerts about critical issues, and visualize the results over time in a rich dashboard.
View time-series metrics, histograms, detailed performance, and resolve notifications.
Enter the new era of corporate search with Azure Cognitive Search and Azure OpenAI Service
Microsoft Bing is transforming the way users discover relevant information across the world wide web. Instead of providing a lengthy list of links, Bing will now intelligently interpret your question and source the best answers from various corners of the internet. What’s more, the search engine presents the information in a clear and concise manner along with verifiable links to data sources. This shift in online search experiences makes internet browsing more user-friendly and efficient.
Now, imagine the transformative impact if businesses could search, navigate, and analyze their internal data with a similar level of ease and efficiency. This new paradigm would enable employees to swiftly access corporate knowledge and harness the power of enterprise data in a fraction of the time. This architectural pattern is known as Retrieval Augmented Generation (RAG). By combining the power of Azure Cognitive Search and Azure OpenAI Service, organizations can now make this streamlined experience possible.
Combine Hybrid Retrieval and Semantic Ranking to improve generative AI applications
Speaking of search, through extensive testing on both representative customer indexes and popular academic benchmarks, Microsoft found that a combination of the following techniques creates the most effective retrieval engine for a majority of customer scenarios, and is especially powerful in the context of generative AI:
Chunking long form content
Employing hybrid retrieval (combining BM25 and vector search)
Activating semantic ranking
Any developer building generative AI applications will want to experiment with hybrid retrieval and reranking strategies to improve the accuracy of outcomes to delight end users.
Improve the efficiency of your Azure OpenAI Service application with Azure Cosmos DB vector search
We recently expanded our documentation and tutorials with sample code to help customers learn more about the power of combining Azure Cosmos DB and Azure OpenAI Service. Applying Azure Cosmos DB vector search capabilities to Azure OpenAI applications enables you to store long term memory and chat history, improving the quality and efficiency of your LLM solution for users. This is because vector search allows you to efficiently query back the most relevant context to personalize Azure OpenAI prompts in a token-efficient manner. Storing vector embeddings alongside the data in an integrated solution minimizes the need to manage data synchronization and helps accelerate your time-to-market for AI app development.
See the full infographic.
Embrace the future of data and AI at upcoming Microsoft events
Azure continuously improves as we listen to our customers and advance our platform for excellence in applied data and AI. We hope you will join us at one of our upcoming events to learn about more innovations coming to Azure and to network directly with Microsoft experts and industry peers.
Enterprise scale open-source analytics on containers: Join Arun Ulagaratchagan (CVP, Azure Data), Kishore Chaliparambil (GM, Azure Data), and Balaji Sankaran (GM, HDInsight) for a webinar on October 3rd to learn more about the latest developments in HDInsight. Microsoft will unveil a full-stack refresh with new open-source workloads, container-based architecture, and pre-built Azure integrations. Find out how to use our modern platform to tune your analytics applications for optimal costs and improved performance, and integrate it with Microsoft Fabric to enable every role in your organization.
Microsoft Ignite is one of our largest events of the year for technical business leaders, IT professionals, developers, and enthusiasts. Join us November 14-17, 2023 virtually or in-person, to hear the latest innovations around AI, learn from product and partner experts build in-demand skills, and connect with the broader community.
The post What’s new in Data & AI: Expanding choices for generative AI app builders appeared first on Azure Blog.
Quelle: Azure
The healthcare industry is undergoing a rapid transformation, driven by the increasing need for cloud computing to improve patient outcomes, capture cost efficiencies, and make it easier to coordinate care, especially for patients in remote areas. Cloud computing enables healthcare organizations to leverage advanced technologies such as artificial intelligence, machine learning, big data analytics, and Internet of Things to enhance their services and operations. However, cloud computing also brings new challenges and risks for securing and protecting sensitive healthcare data, such as electronic health records, medical images, genomic data, and personal health information. Healthcare organizations need to ensure that their cloud service providers meet the highest standards of security and compliance, as well as adhere to the complex and evolving regulations and frameworks that govern the healthcare industry.
Microsoft Azure committed to security and compliance in the healthcare industry
One of the most widely adopted and recognized frameworks for information protection in the healthcare industry is the HITRUST Common Security Framework (CSF). The HITRUST CSF is a comprehensive and scalable framework that integrates multiple authoritative sources, such as HIPAA, NIST, ISO, PCI, and COBIT, into a single set of harmonized controls. The HITRUST CSF provides a prescriptive and flexible approach for assessing and certifying the security and compliance posture of cloud service providers and their customers. Achieving HITRUST CSF certification demonstrates that a cloud service provider has implemented the best practices and controls to safeguard sensitive healthcare data in the cloud.
As healthcare organizations converge on the Dallas area for the HITRUST Collaborate 2023 event, providing secure and compliant cloud services for the healthcare industry is more important than ever. Microsoft Azure is committed to being a trusted partner for healthcare organizations in their digital transformation journey. Azure provides a comprehensive portfolio of cloud services that enable healthcare organizations to build innovative solutions that improve the entire healthcare experience. Azure also offers a range of capabilities that make it easier for healthcare organizations to achieve and maintain security and compliance in the cloud.
We are therefore proud to announce that Microsoft Azure has achieved HITRUST CSF v11.0.1 certification across 162 Azure services and 115 Azure Government services. All GA Azure regions across Azure and Azure Government clouds are included within this certification. This achievement reflects the continuous efforts by Azure to enhance its security and compliance offerings for customers in the healthcare industry.
HITRUST CSF v11.0.1 is the latest version of the framework that incorporates new requirements and updates from various authoritative sources, such as NIST SP 800-53 Rev 5, NIST Cybersecurity Framework v1.1, PCI DSS v3.2.1, FedRAMP High Baseline Rev 5, CSA CCM v3.0.1, GDPR, CCPA, and others. HITRUST CSF v11.0.1 also introduces new features and enhancements, such as maturity scoring model, risk factor analysis, inheritance program expansion, assessment scoping tool improvement, and more. Achieving HITRUST CSF v11.0.1 certification demonstrates the increasing commitment Azure has to providing secure and compliant cloud services for customers in the healthcare industry.
The HITRUST CSF v11.0.1 r2 Validated Assessment for Azure was performed by an independent third-party audit firm licensed under the HITRUST External Assessor program. The audit firm evaluated Azure for security policies, procedures, processes, and controls against the HITRUST CSF requirements applicable to cloud service providers. The audit firm also verified that security controls for Azure are implemented effectively and operate as intended. Azure customers can obtain the HITRUST CSF Letter of Certification, which contains the full scope of certified Azure offerings and regions, at the Service Trust Portal.
Microsoft Azure partners with HITRUST Alliance
In addition to today’s certification, Azure has also partnered in the past with HITRUST Alliance to release the HITRUST Shared Responsibility Matrix for Azure, which provides clarity around security and privacy responsibilities between Azure and its customers, making it easier for organizations to achieve their own HITRUST CSF certification. The matrix outlines which HITRUST CSF controls are fully managed by Azure, which are shared between Azure and customers, and which are solely the customers’ responsibility. The matrix also provides guidance on how customers can leverage the capabilities in Azure to meet their own security and compliance obligations.
Azure also supports the HITRUST Inheritance Program which empowers organizations to achieve more by significantly reducing the compliance cost and burden by enabling customers to externally inherit requirements from the Azure HITRUST CSF certification. The program allows customers to inherit up to 75 percent of applicable HITRUST CSF controls from the Azure certification scope without additional testing or validation by an external assessor. This reduces the time, effort, and resources required for customers to obtain their own HITRUST CSF certification or report on their compliance status using other frameworks or standards based on the HITRUST CSF. Azure has reviewed over 23,450 inheritance requests from customers since the program’s inception.
Azure has maintained the HITRUST CSF certification since November 2016. Azure was one of the first cloud service providers to achieve HITRUST CSF certification and has been continuously expanding its scope of certified services and regions. Azure is also one of the few cloud service providers that offer HITRUST CSF certified services in both public and government clouds. The Azure HITRUST CSF v11.0.1 certification is backward compatible with HITRUST CSF v9.1, v9.2, v9.3, v9.4, v9.5, and v9.6 certifications, offering support to a wide range of customers.
Learn more about the Azure HITRUST CSF certification
Azure is dedicated to helping healthcare organizations accelerate their digital transformation while ensuring security and compliance in the cloud. Azure provides a secure and compliant cloud platform that enables healthcare organizations to build innovative solutions that improve patient care, operational efficiency, and business agility. Azure also offers a variety of tools and resources that make it easier for healthcare organizations to achieve and maintain security and compliance in the cloud. The Azure HITRUST CSF certification is a testament to the commitment Azure has to be a trusted partner for healthcare organizations in their cloud journey.
The post Microsoft Azure achieves HITRUST CSF v11 certification appeared first on Azure Blog.
Quelle: Azure
This blog has been co-authored by Ashish Shah, Partner Director of Engineering, Azure Developer Experience.
We are excited to announce the preview of Microsoft Playwright Testing, a new service for running Playwright tests easily at scale. Playwright, a fast-growing, open-source framework, enables reliable end-to-end testing and automation for modern web apps. Microsoft Playwright Testing is a fully managed service that uses the cloud to enable you to run Playwright tests with much higher parallelization across different operating system-browser combinations simultaneously. This means faster test runs with broader scenario coverage, which helps speed up delivery of features without sacrificing quality.
Ready to jump in? Get your free Azure trial and start running your tests at cloud-scale with Microsoft Playwright Testing.
Get test suite results faster
Adding Playwright tests to your continuous integration (CI) workflow helps ensure that as the app evolves, your web app experiences continue to work the way you expect. But as the app becomes more complex, the test suite required for comprehensive testing across multiple browser and operating system combinations also increases in size. This leads to longer test suite completion times, potentially delaying your feature delivery. Development teams are already under pressure to quickly deploy app enhancements. To work around long wait times for test completion, it is common practice for development teams to selectively run only a small subset of tests. In a more detrimental scenario, a team may choose to execute tests less frequently, such as only a few times a week in an integration environment instead of with every pull request. This approach can potentially delay catching issues, complicate the process of pinpointing the cause of problems, and adversely affect the overall productivity of the development team.
With the @playwright/test runner, your tests run in independent, parallel worker processes with each process starting its own browser. Increasing the number of parallel workers can reduce the time it takes to complete the full test suite. You can set the number of workers using the command line:
npx playwright test –workers=4
However, when you run tests locally or in your CI pipeline, you’re limited to the number of central processing unit (CPU) cores on your local machine or CI agent machine. At some point adding more workers will lead to resource contention, slowing down each worker and introducing test flakiness.
By using Microsoft Playwright Testing service you can increase the number of workers at cloud-scale to much bigger numbers. The worker processes orchestrated by @playwright/test continue to run locally but the browser instances, which are resource-intensive, now run in the cloud. You can see in the demo video below how thousands of tests run on 50 parallel browsers in the cloud managed by Microsoft Playwright Testing, significantly reducing the wait time for test results.
Consistent test results across multiple operating systems and browser combinations
App complexity isn’t the only factor in increasing test suite size. Modern web apps need to work flawlessly across numerous browsers, operating systems, and devices. Testing across all these variables increases the amount of time it takes to run your test suite. With Microsoft Playwright Testing you’ll use the scalable parallelism provided by the service to run these tests simultaneously across all modern rendering engine. This includes Chromium, WebKit and Firefox on Windows, and Linux and mobile emulation of Google Chrome for Android and Mobile Safari. Also, the service-managed browsers ensure consistent and reliable results for both functional and visual regression testing, whether tests are run from your CI pipeline or development machine. This extensive cross-compatibility testing helps ensure your web app delivers consistent performance and functionality across all platforms, optimizing the experience for any user, regardless of their browser or operating system.
Figure 1-Use Microsoft Playwright Testing service from your CI pipelines and code editors.
No test code changes required
If you’re using Playwright today, getting started with Microsoft Playwright Testing is easy! The service is designed to seamlessly integrate with your Playwright test suite, no changes to existing test code required. In just a few steps you can connect your test suite to the service and unlock the full potential of cloud-powered parallel testing. Plus, the service supports multiple versions of Playwright and updates with each new Playwright release, ensuring your tests run against the latest browser versions and technologies while helping to keep your app current, robust, and secure. Now you can focus on thorough application testing without the worry of managing a complex test infrastructure.
Get started with a free trial
Discover all Microsoft Playwright Testing has to offer using the free trial today. Sign in using your Azure account (or create one free), then follow our Quickstart guide to configure your Playwright tests and run them at cloud-scale.
Next you can explore our flexible consumption-based pricing where you pay only for what you use.
Share your feedback
What would you like to see? We’d love to hear your feedback to help shape the future of this service.
Learn more about Microsoft Playwright Testing.
Learn more about using the Playwright Testing service for your web application testing.
Explore the features and benefits that Microsoft Playwright Testing offers for scalable and reliable web app testing.
Learn how to run your existing Playwright tests with highly parallel cloud browsers to reduce time waiting for test suite completion.
Learn how to set up continuous end-to-end testing to validate that your web app runs correctly across different browsers and operating systems with every code commit.
Learn about our flexible pricing.
Use the pricing calculator to determine your costs based on your business needs.
Learn how Playwright enables reliable end-to-end testing for modern web apps.
See Playwright on GitHub.
Interact with the Playwright community on Discord.
Stay up to date with Playwright releases.
The post Announcing Microsoft Playwright Testing: Scalable end-to-end testing for modern web apps appeared first on Azure Blog.
Quelle: Azure
Generative AI has become a critical tool for businesses seeking to streamline tasks and enhance productivity. Today, generative AI can generate everything from written content and music to product designs and programming code, paving the way for unprecedented levels of automation.
The demand and impact of cutting down on repetitive tasks is real. Generative AI solutions such as Azure OpenAI Service improve productivity and are useful for content creation, scientific advancement, customer service, and marketing automation.
According to a 2023 report by McKinsey Global Institute:
Combining generative AI with all other technologies could add 0.2 to 3.3 percentage points annually to productivity growth.
Generative AI could further reduce the volume of human-serviced contacts by up to 50 percent, depending on a company’s existing level of automation.
AI agents integrated through APIs could act nearly autonomously or as copilots, giving real-time suggestions to agents during customer interactions.
In the lead identification stage of drug development, scientists can use foundation models to automate the preliminary screening of chemicals to search for those that will produce specific effects on drug targets.
A 2023 BCG (Boston Consulting Group) article reported that emails drafted by a generative AI application achieved 18 percent higher customer happiness scores than humans’ email responses.
By streamlining tasks that were previously manual, time-consuming, and error-prone, generative AI is not just a tool for businesses—but a critical driver of future success.
How partners benefit from Generative AI
Customers around the globe have benefitted from the Microsoft AI Cloud Partner Program by allowing them to build quickly, scale growth, and sell worldwide. AI-specific benefits help partners leverage Microsoft’s extensive resources such as access to AI expertise, and network to develop, market, and sell AI solutions, thereby enhancing their competitiveness in the rapidly growing field of artificial intelligence.
Let’s have a look at how five partners (Commerce.AI, Datadog, Modern Requirements, Atera, and SymphonyAI) have powered their customers’ transformations and derived value from using generative AI.
Commerce.AI
Commerce.AI uses a combination of its own technology, Microsoft, and OpenAI solutions to streamline productivity in customer support centers using automation. When a customer call is received, Azure AI Services transcribes it in real-time using a custom Commerce.AI model, and, if necessary, translates it. Post-call, the system utilizes OpenAI technology to automatically generate a summary, determining any follow-up actions and exporting the data to Microsoft Dynamics 365, thereby eliminating the need for agents to write post-call notes. Commerce.AI’s solutions are lauded for enhancing productivity by up to 50 percent, increasing efficiency, and delivering instant insights.
“With OpenAI models, the answers to our questions are ready the moment we ask them,” says Andy Pandharikar: Founder and Chief Executive Officer at Commerce.AI. “What we’ve done at Commerce.AI using Azure OpenAI Service is supercharge our customers’ ability to take action based on those insights through automation.”
By automating workflows, Commerce.AI can respond swiftly to shifts in customer priorities. By analyzing unstructured data and using the insights to automate new ad campaigns or launch new products, Commerce.AI predicts that the cost of generative AI in business will decrease as its applications expand.
Datadog
Since launching its first monitoring solution for Azure Virtual Machines in 2015, Datadog has expanded its capabilities by embedding observability solutions within the Azure portal and developing over 600 in-house integrations. With many of Datadog’s customers leveraging Azure OpenAI Service, Datadog developed a seamless Azure OpenAI Service integration to expedite monitoring operations and improve efficiency.
This integration provides comprehensive monitoring for cloud-native and hybrid workloads, accelerates cloud adoption journeys, brings innovative monitoring capabilities, and guarantees best-in-class service quality.
“We have everything configured for autoscaling,” explains Benjamin Pineau, Senior Software Engineer at Datadog, “and Azure will always adapt to our needs, upping capacity by several hundreds of high-memory instances to ingest a spike and then slowing back down in a matter of minutes.”
Since launching this solution at Microsoft Build 2023, hundreds of organizations, including Fortune 50 and large global multinational companies, have adopted Datadog to monitor their AI applications. The solution enables these companies to monitor analytics, optimize costs, and troubleshoot issues in AI-powered applications, freeing up their development teams to focus on customer-centric product development. With this integration, customers can access metrics from Azure Virtual Machines, tag Azure metrics with resource-specific data, gain unique insights into their Azure environment, and correlate data across various Azure applications.
Modern Requirements
Modern Requirements is committed to optimizing the requirements processes of its customers through automation. Their key services include providing the tools necessary for effective project management throughout their life cycles, hastening time to market, and enhancing project quality. Their target sectors range from healthcare and financial services to automotive, aviation, and government, all of which have the common need for regulatory compliance, auditability, and seamless workflow solutions.
The foundation of Modern Requirements’ solution is Microsoft Azure DevOps, chosen for its scalability and security. The integration with Azure OpenAI Service further enhances this with its multifaceted model capable of handling various tasks while ensuring data privacy and security. This integration requires minimal training and opens doors for significant enhancements through OpenAI.
Designed with intent, Modern Requirements4DevOps serves both Modern Requirements’ and Microsoft’s clients in their product development life cycles by automating numerous functions. It further enriches this service with the introduction of Copilot4DevOps, an implementation of ChatGPT in Modern Requirements4DevOps. This tool automates several phases in the product development life cycle, freeing users to focus more on analytical and collaborative tasks.
Modern Requirements4DevOps relieves workflow and data management burdens, storing all information in a single source of truth in Azure DevOps. The extension also transforms Azure DevOps into a knowledge management system, moving away from just record-keeping and workflow management.
The solution is used by requirements engineers, business analysts, test leads, compliance leads, project managers, and project architects for information provision, reuse, and collaboration. It effectively substitutes up to half a dozen costly tools, providing an integrated, supportive, and affordable alternative for their clients.
Atera
Atera, an Israeli software company, has set a mission to increase IT efficiency tenfold through its AI-powered IT Platform. Developed in collaboration with Microsoft using Azure OpenAI Service, this groundbreaking tool offers a comprehensive view of IT activities and proactively identifies and resolves issues, allowing IT professionals to concentrate on critical tasks.
The platform, serving 11,000 customers across 105 countries, is revolutionizing the way IT issues are handled. It collects metrics continuously, offers immediate solutions, and remotely fixes machines. When customers contact IT support, the autopilot responds instantly with solutions, while a co-pilot takes over in case of complex issues, offering a summarized problem description and recommended solutions to technicians.
“Instead of spending 20 minutes trying to understand the problem, 15 minutes deciding on a solution, and then possibly 40 minutes to remotely fix the issue or two hours writing a script to run it, the technician can focus directly on fixing the issue,” says Oshri Moyal, Co-Founder and CTO of Atera. “All it takes is a few clicks, and the problem is solved. This change means a single technician can go from handling seven to 70 cases per day.”
SymphonyAI
Financial crime, which includes fraud and money laundering, is a major global concern, costing around five percent of the global GDP, and is linked to crimes like human trafficking and terrorism, among others. SymphonyAI is taking innovative steps to address this problem. The company’s Sensa-NetReveal division offers AI-powered solutions designed to detect financial crime and assist financial investigators. They have integrated AI algorithms and machine learning models into their platform to identify previously undetected risk areas, aiming to complete investigations up to 70 percent faster and with 70 percent less effort from human investigators.
Their Sensa Copilot—built on the Azure infrastructure, Azure Kubernetes Service (AKS), Azure AI solutions, and Azure OpenAI—was introduced in May 2023, and is designed to assist financial crime investigators by automatically collecting, collating, and summarizing financial and third-party information, identifying behaviors associated with money laundering, and efficiently analyzing these activities. Investigators can also use it to draft suspicious activity reports (SAR).
In early testing, the Sensa Copilot was shown to increase the productivity of a financial institution’s compliance department by approximately 60 percent, given the volume of alerts these institutions receive daily. This marks a significant shift in the financial crime investigation landscape. In a world where time and efficiency are of the essence, the five above-mentioned Microsoft Partners serve as an inspiration for all businesses, irrespective of their sector or size, to embrace the opportunities offered by generative AI.
Our commitment to responsible AI
Microsoft has a layered approach for generative models, guided by the Microsoft AI Principles. In Azure OpenAI, an integrated safety system provides protection from undesirable inputs and outputs and monitors for misuse. In addition, Microsoft provides guidance and best practices to help customers responsibly build applications using these models and expects customers to comply with the Azure OpenAI Code of Conduct.
Get started with Azure OpenAI Service
Apply for access to Azure OpenAI Service by completing this form.
Learn about Azure OpenAI Service and the latest enhancements.
Get started with OpenAI GPT-4 in Azure OpenAI Service in Microsoft Learn.
Read our Partner announcement blog, ”Empowering partners to develop AI-powered apps and experiences with ChatGPT in Azure OpenAI Service.”
Learn how to use the new Chat Completions API (preview) and model versions for ChatGPT and GPT-4 models in Azure OpenAI Service.
The post Get inspired: Five Microsoft partners using generative AI to enhance productivity appeared first on Azure Blog.
Quelle: Azure
This post was co-authored by Naveen Valluri, General Manager, Health Data & AI, Microsoft Health & Life Sciences.
In the past year, AI has transformed what we thought was possible and opened up new avenues for groundbreaking transformations. From creating personalized treatment plans to extracting insights from XRAYs and MRIs, generative AI has made the concept of artificial intelligence real—and accessible, such as with Azure AI Health Bot. For the healthcare industry, this might mean the beginning of a transformative era that changes how healthcare is delivered and accessed—making precision medicine truly individualized, speeding up groundbreaking research for life threatening diseases, and finding new and innovative ways to improve patient care.
Making AI and machine learning real and actionable starts with the data being analytics ready. Healthcare data has been growing at an exponential rate and most healthcare organizations don’t know where to start with organizing that data. It is usually on-premises, siloed, and hard to navigate. The very first step would be to make this data accessible and normalize it in a way that makes it ready for analytics and AI in the cloud. Industry-specific solutions in Microsoft Fabric provide relevant solutions that unify data and insights for healthcare organizations through one common architecture and experience. Now available in preview, healthcare data solutions in Microsoft Fabric eliminate the costly, time-consuming process of stitching together a complex set of disconnected, multi-modal health data sources—text, images, video, and more—and provide a secure and governed way for organizations to access, analyze, and visualize data-driven insights across their organization.
We’re making several exciting announcements about new data and AI capabilities that will be introduced across the Microsoft Cloud for Healthcare to help health organizations improve patient experience, gain new insights with machine learning and AI, and handle health information securely. Features like de-identification service and getting insights from unstructured text will also be available soon in Fabric. We’re pleased to announce:
General availability of multi-language support in Text Analytics for health, an Azure AI Language service. Healthcare organizations worldwide can use the Text Analytics for health service to extract meaningful insights in six languages in addition to English—Spanish, French, German, Italian, Portuguese, and Hebrew—making this technology more accessible to health organizations worldwide and improving health equity on a global scale.
De-identification service (in preview) in Microsoft Fabric and Azure Health Data Services so organizations can de-identify medical data such that the resulting data retains its clinical relevance and distribution while also adhering to the HIPAA privacy rule. Our service supports unstructured text and will soon cover various other data types (structured, imaging, and MedTech). The service uses state-of-the-art machine learning models to automatically extract, redact, or surrogate over 30 entities—including HIPAA’s 18 protected health information (PHI) identifiers—from unstructured text such as clinical notes, messages, or clinical trial studies.
Expansion of our Azure AI Health Bot in preview to allow healthcare organizations to build copilots for their healthcare professionals to further manage administrative and clinical workloads as well as improve patient experiences. Azure AI Health Bot is designed to help healthcare organizations create specialized chatbot experiences which are now powered by generative AI, enabling high-value conversational scenarios for the health and life sciences industry.
Adding three new built-in models in preview to Azure AI Health Insights. These built-in models create actionable, chronological patient timelines based on clinical data and evidence, provide simplified, patient-friendly versions of clinical notes and reports, and surface radiology insights from radiology reports to help radiologists improve their workflow.
Building a healthcare ecosystem with a partner network
In addition to our exciting product announcements, Wolters Kluwer also announced that its Health Language Platform, a Fast Healthcare Interoperability Resources (FHIR®) terminology server, will work with Microsoft Azure and Azure Health Data Services to help customers enrich and standardize their healthcare data with medical ontologies on Microsoft Azure.
Customers onboarding to Azure will be able to access Wolters Kluwer’s Health Language Platform via Azure Marketplace to validate and translate their FHIR data so that it is ready for future analysis. Organizations can achieve semantic interoperability across multi-modal data sources to propel a range of use cases across healthcare.
Working with our partner ecosystem, Microsoft is committed to continuing to develop healthcare technology that helps our customers use Microsoft Cloud to derive insights from their data and responsibly use AI. By connecting our customers with the right partners in our ecosystem and giving them access to Azure Marketplace, we want to ensure they have access to the right building blocks for their organizations use case.
Real-world innovation in healthcare
By combining Microsoft Cloud for Healthcare services and tools, health organizations are coming up with new and innovative solutions to meet their unique needs.
For example, let’s say a researcher is working on a new drug for Alzheimer’s disease and needs to find suitable patients with specific symptoms and diagnoses to work on a hypothesis. First, they would de-identify their raw data so that they can use it for their research. If we look at this from the perspective of the clinician, they may want to look at a specific set of patients to see if there are any similarities and patterns that may help them with treatment plans for specific patients. Once they have established this, they can then gather from clinical notes they may have missed to ensure they have the full picture. When writing out their report and prescriptions for the patient, the clinician can opt to simplify their note using AI, making the note much easier for the patient to read as it will exchange complicated terminology for something easier to understand.
Next, a patient who has been diagnosed with Alzheimer’s disease takes the leading role. They are interested in finding more information about their prescription medications in the report which they were able to understand much more easily than before due to the lack of medical jargon. They find that their hospital website has a chatbot and are easily able to interact with them to get answers about their medications and set up appointments if they want.
And that’s just one possibility. Whether it’s finding new treatments, enhancing patient engagement, or optimizing workflows, Microsoft Cloud for Healthcare can help healthcare organizations achieve more.
Helping solve healthcare’s biggest problems
At Microsoft, we want to empower you in solving the challenges you face on a day-to-day basis—whether it be reducing clinician burnout or delighting your patients with personalized care—and to do these—allowing you to gain insights from your data and develop and deploy AI at scale.
With the help of Dataside, a Microsoft partner in Brazil, Oncoclínicas is using Microsoft’s Azure AI text analytics for health to extract data from non-structured fields like medical notes, anatomic pathology, genomic, and imaging reports like MRI. This data was then used by Dataside for various use cases such as clinical trial feasibility, a better understanding of the scenarios for pharmacoeconomics, and gaining a deeper understanding of group epidemiology and outcomes of interest.
“Text Analytics for health was a turning point for Grupo Oncoclínicas to scale our processes and to structure our clinical notes, exam reports and field analysis, which previously only depended on manual curation. Having a solution that works in Portuguese is key—most global solutions tend to only cater to English, thereby neglecting other languages. Accuracy in the native Portuguese allowed us to maintain a high level of accuracy while analyzing the unstructured text.”—Marcio Guimaraes Souza, Head of Data and AI at Grupo Oncoclínicas.
“We are excited to be collaborating with Microsoft to explore the potential of generative AI through the Azure AI Health Bot. This partnership aims to enhance healthcare content utilization at Ramsay Healthcare, offering a transformative way for healthcare professionals to engage with the vast clinical knowledge base. Our innovative solution facilitates seamless and efficient interactions, providing healthcare teams with quick access to answers, recommendations, and inventive troubleshooting solutions, all delivered through an intuitive chat interface. We are confident that it holds the promise to play a pivotal role in our daily operations, reducing time to find relevant content, and potentially revolutionizing the way we provide patient care.”—Towa Jexmark, Head of Innovation and Strategic Partnerships at Ramsay Santé.
Do more with your data with Microsoft Cloud for Healthcare
With Microsoft Cloud for Healthcare, organizations can transform their patient experience, discover new insights with the power of machine learning and AI, and manage PHI data with confidence. Enable your data for the future of healthcare innovation with Microsoft Cloud for Healthcare.
We look forward to working with you as you build the future of health.
Introducing Microsoft Fabric and Copilot in Microsoft Power BI.
Learn more about Azure Health Data Services.
What is Azure Text Analytics for health?
Learn about Azure AI Health Bot.
Discover more about Azure AI Health Insights.
Learn more about Microsoft Cloud for Healthcare.
Discover how health companies are using Azure to drive better health outcomes.
FHIR® is the registered trademark of HL7 and is used with the permission of HL7.
The post Microsoft empowers health organizations with generative AI and actionable data insights appeared first on Azure Blog.
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