Any developer can be a space developer with the new Azure Orbital Space SDK

Earlier this year, we announced our vision to empower any developer to become a space developer through Azure. With over 90 million developers on GitHub, we have created a powerful ecosystem and we are focused on empowering the next generation of developers for space. Today, we are announcing a crucial step towards democratizing access to space development, with the preview release of Azure Orbital Space SDK (software development kit)—a secure hosting platform and application toolkit designed to enable developers to create, deploy, and operate applications on-orbit.

By bringing modern cloud-based applications to spacecrafts we not only increase the efficiency, value, and speed of insights from space data but also increase the value of that data through the optimization of ground communication.

Many of the fundamental technological improvements that have accelerated the growth of Internet of Things (IoT) in the past decade remain untapped by space development missions today. With the Azure Orbital Space SDK, we will help bring those improvements to space through modern agile software deployment, container-based development, use of higher-level languages, and cloud-managed networking. Extending the power of the Azure cloud into space means that spacecraft development will take less time, cost less, and bring more people into the space development ecosystem.

What is the Azure Orbital Space SDK?

The Azure Orbital Space SDK was created to be able to run on any spacecraft and provide a secure hosting platform and application kit to create, deploy, and operate applications on-orbit. This "host platform" runs onboard the spacecraft including a containerized, scalable compute infrastructure with resource and schedule management capabilities.

The application kit provides a set of templates, samples, and documentation to make it easy to get up and running as a space developer with template applications for common workload patterns, such as earth observation image processing. There is also a "virtual test harness" that allows developers to easily test their applications on the ground against an instance of the host platform.

How the Azure Orbital Space SDK is changing what’s possible

By moving the application onboard the spacecraft through the Azure Orbital Space SDK, we enable time and cost savings while radically altering and expanding the capabilities of the spacecraft.

Remote sensing

Remote sensing from space provides the perspective we need to better understand our world and powers commercial, economic, humanitarian, intelligence, and military scenarios—from damage assessments after weather events, to vessel detection, to crop monitoring and land classification.

Most remote sensing satellites have limited connectivity windows and bandwidth to communicate data back to the ground. As the fidelity of sensors increases, the amount of data they generate eclipses the available bandwidth. Being able to prioritize images that are useful, or even being able to send insights rather than the raw data down to the ground significantly reduces costs, accelerates speed, and fundamentally increases the value of the satellite.

Through the Azure Orbital Space SDK, developers can write and host more intelligent applications on-board satellites, meaning that they can capture data and use time more efficiently, and even autonomously reconfigure applications at the ultimate edge. Instead of building a unique solution each time developers deploy a spacecraft application, the Azure Orbital Space SDK creates a common template for performing imaging tasks, making it easier to transfer models and applications from one satellite configuration to another.

Communications

Satellite communications is one of the most well-known and widely used space capabilities. It allows us to watch live events around the world, provides internet and cloud connectivity to remote locations both on earth and in space, and supports the backbone of cellular networks. By bringing applications and intelligent computing on board satellites through the Azure Orbital Space SDK, we enable a more sophisticated management of satellite communications – resulting in lower costs and higher efficiency for satellite-based communication networks

Telecommunications networks have transitioned to software-defined networks and application–centric approaches to manage their communications infrastructures. The inclusion of satellites in 5G standards is the push for satellite networks to follow the same digital transformation. The Azure Orbital Space SDK will provide a compute fabric with networking capabilities for hosting telecommunication workloads, allowing operators to move applications more easily from ground-based cell sites to satellites in orbit, enabling better resiliency and network utilization.

Ultimately, by combining the Azure Orbital Space SDK with our portfolio of Azure Orbital products, we are bringing the power of cloud networking to the edge in space.

Azure Orbital Space SDK Partnerships

In April, we launched the Azure Space Partner Community and unveiled our initial cohort of space community partners, including Loft Orbital, Ball Aerospace and Thales Alenia Space. Today, we are announcing the newest member of our partner community—Xplore—who will help us continue to shape the future of space technologies and services.

Xplore

Xplore provides unique data including optical, video, and hyperspectral imagery via the XCRAFT, its highly capable, multi-sensor satellite. The XCRAFT's sophisticated sensors produce terabytes of data per day and will utilize powerful compute, storage, and communication solutions to deliver the unique insights derived to customers.

Microsoft and Xplore are partnering to use Azure Orbital Space SDK to gather new insights into how edge computing solutions can better enable both government and commercial customers to achieve their mission objectives. Together, our teams will investigate numerous on-orbit compute use-cases from downlink optimization to multi-sensor data fusion.

Loft Orbital

Loft Orbital is a space infrastructure and services company providing customers rapid, reliable, and simplified access to space. Loft has developed a highly modular satellite platform that enables them to provide a truly plug and play path to orbit for customer payloads and missions.

The Microsoft and Loft Orbital partnership will enable developers to easily develop, test, and deploy software-only “virtual payloads” to the Loft Orbital infrastructure. Together we are developing new technologies and products that will enhance the flexibility of on-orbit operations and provide seamless connectivity to the terrestrial cloud.

Earlier this year Microsoft and Loft conducted a successful test of demonstrating the integration of Loft spacecraft with the Azure Orbital Ground station.  Next year, we’ll build upon this success with the launch of YAM-6, a dedicated free-flying orbital testbed for customers to explore how our joint space infrastructure, connectivity, and on-orbit compute technologies will make access to space even easier than before.

Ball Aerospace

Ball Aerospace is a systems integrator with a heritage of designing and building government satellite programs and mission applications. Ball continues to innovate on behalf of its customers by combining their long expertise in exquisite satellite systems with modern tools and processes, enabling a more agile approach to space mission development and operations.

Together, Ball Aerospace and Microsoft are collaborating on the execution of series of on-orbit testbed satellites showcasing this highly agile future. These missions will leverage the Azure Orbital Space SDK to demonstrate modular and reconfigurable on-orbit processing technologies, necessary to support the complex missions for the United States Government.  The new software and hardware technologies demonstrated in these testbeds will unlock new capabilities for customers, granting the ability to support future concepts for smaller, agile, multi-mission capabilities across all federal space programs.

Thales Alenia Space

Thales Alenia Space is a leader in orbital infrastructures and is developing high-power, edge-computing solutions for space.

Microsoft is partnering with Thales Alenia Space to demonstrate and validate on-orbit compute technologies for multiple remote-sensing applications.   Our team’s future orbital testbed, launching to the International Space Station (ISS) in late 2023, brings together Thale’s edge computing hardware and Microsoft’s Azure Orbital Space SDK platform with visible and hyperspectral sensors, empowering the next generation to explore how space and on-orbit compute can improve our world. Developers on our platform will explore different on-orbit compute use cases, from AI-based hyperspectral image processing and to multi-sensor fusion algorithms, both computationally demanding workloads that benefit from Thales Alenia’s high-performance edge compute architecture.

In collaboration with Microsoft Research (MSR), Microsoft, and Thales Alenia Space, we are reducing the barriers for research in space through a range of outreach initiatives. One such initiative is the new Azure Space Academic Outreach program, that will work with research teams in remote sensing, computer vision, and climate science to demonstrate the potential of next-generation on-orbit compute for Earth observation. The first pilots exploring this program are the University of Illinois Urbana-Champaign and NSF Spatiotemporal Innovation Center; however, we hope to open this up to more participants over the coming year.

What we’ve done and what’s coming next

The Azure Orbital Space SDK is a key part of the Azure Space portfolio and joins our investments together to create a value chain that is unique in the industry today—from space to ground to cloud. Over the past two years we’ve moved from a vision of combining the power of the cloud with the possibilities of space, into a reality with the launch of our our Azure Orbital Ground Station, the recently announced Azure Orbital Cloud Access, and today the Azure Orbital Space SDK.  Integral to Microsoft‘s approach across these announcements has been partnership, and we have partnered with space industry leaders to deliver incredible value to our customers, with most recently the partnership with DIU to support their hybrid space architecture and the development of the internet of space.

The Azure Orbital Space SDK will change what is possible onboard spacecraft, but also more importantly change the applications and insights we gather on earth and inform critical decisions and communications across the planet.

Learn more

For space companies interested in applying for preview access to Azure Orbital Space SDK, reach out to the Azure Space Partner Community. 
For universities interested in participating in on-orbit research for climate science, please reach out to the Azure Space Academic Outreach Program.
To learn more about Azure Space view our solution page.

Quelle: Azure

Microsoft named a Leader in 2022 Gartner® Magic Quadrant™ for Full Life Cycle API Management

We are excited to share that Gartner® has positioned Microsoft as a Leader in the 2022 Magic Quadrant™ for Full Life Cycle API Management. This year’s placement marks the third consecutive year Microsoft has been recognized as a Leader. We believe our placement is a testament to our deep understanding of customer needs, strong customer adoption, positive feedback, and continued investments in building a differentiated platform.

Powering our customers’ digital transformation initiatives

APIs are critical to drive digital transformations in modern organizations. Thousands of the world’s largest enterprises trust Azure API Management to build, secure, and scale their API initiatives. With over a million APIs published on the Azure API Management platform today – it is a battle-hardened, production-ready, and highly scaled platform that stretches from on-premises to multicloud. Our customer use cases span a broad range from modernizing legacy applications to adopting API-first strategies to deliver innovations faster, create new revenue streams, and generate value for their customers and partners. Wegmans, a supermarket chain that re-invented the shopping experience in less than eight weeks, and Vipps, a leading Norwegian mobile payment provider that made mobile payments a norm, are examples of customers that are supercharging their digital transformation journey with the Azure API Management platform.

Delivering new capabilities for Azure API Management

Here are a few highlights of our latest features that are helping drive superior business outcomes for our customers around the world:

Support for new API types: Customers can now publish existing WebSocket and GraphQL backends as APIs in Azure API Management with high-fidelity experience in both Azure and the developer portal.
Support for hybrid and multicloud API management: To allow our customers to harness the power of hybrid or multicloud, we’ve enhanced the self-hosted gateway feature making it easier to efficiently and securely manage APIs hosted on-premises and across clouds from a single API Management service in Azure.
Security enhancements: Security is top of mind for all our customers, and we have added several new features—private links, managed certificates, authorizations to configure, store and swap authorization tokens, and more additions that help fortify their security and compliance posture.
Geographic expansion of existing Azure API Management availability regions: We have added four more regions to Europe and China, making Azure API Management available across 58 Azure regions.

Partnering for success on your digital transformation journey

Microsoft is committed to accelerating the pace of digital transformation for our customers.

Learn how organizations like yours use Azure API Management to accelerate their digital transformation journeys.
Download a complimentary copy of the 2022 Gartner Magic Quadrant for Full Life Cycle API Management to learn why Microsoft is named a Leader.

 

 

Gartner, Magic Quadrant for Full Life Cycle API Management, Shameen Pillai, Kimihiko Iijima, Mark O'Neill, John Santoro, Paul Dumas, Akash Jain, 14 November 2022.

Gartner and Magic Quadrant are registered trademarks and service marks of Gartner, Inc. and/or its affiliates in the U.S. and internationally and are used herein with permission. All rights reserved .

Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
Quelle: Azure

Expanding AI technology for unstructured biomedical text beyond English

The health industry is embracing the power of big data, cloud computing, and clinical analytics, harnessing data to deliver insights that can improve care and efficiency. Still, unstructured text remains a challenge—made even more complex by barriers of language. Doctors’ notes and other unstructured text are often left unreferenced, are hard to parse and learn from, and are difficult to extract insights from, which leads to missed opportunities for diagnosis and better care.

Microsoft recognizes the need to enable healthcare organizations worldwide to gather insights from this data—for better, faster, and more personalized care, and to improve health equity. With Text Analytics for Health, a part of Azure Cognitive Services, healthcare organizations around the world can now extract meaningful insights from unstructured text in seven languages and process it in a way that enables clinical decision support like never before. Moving beyond English, Text Analytics for Health has now released six additional languages in preview—Spanish, French, German, Italian, Portuguese, and Hebrew—making this groundbreaking technology that helps extract insights from multilingual unstructured clinical notes accessible to more health organizations globally. This marks the first of its kind Natural Language Processing (NLP) service that holistically supports analysis of unstructured biomedical data in multiple languages and was developed with a federated learning approach. Most health technology is limited to the English language, making it inaccessible to millions of people and countries where English is not the primary language. Releasing NLP technology in multiple languages is a huge step forward in bridging the gaps in health equity created by language barriers and ensuring that access and quality of health care is not determined by one’s ability to speak and understand English.

Text Analytics for Health uses powerful NLP to detect and identify medical terms in text, classify them and associate them with standard clinical coding systems, as well as infer semantic relationships and assertions in the data, enabling deeper contextual understanding. This opens a world of possibilities for providers, payors, life sciences, and pharmaceutical companies, allowing them to unify data points from unstructured text with structured data, and enabling them to surface key insights, identify risks, automate form-filling, or match clinical trials to patients for better sourcing of candidates—based on comprehensive data including unstructured clinical text.

Training the NLP model for different languages

One of the challenges for an NLP service comes in moving past English—in aiming to analyze text from different languages. This is what Microsoft’s team aimed to do—the goal was to empower all health organizations, no matter the language their text is in. The unique challenges come from the need to train AI models for multiple languages, as well as adjust to country-specific needs. Syntax is different between languages, especially when it comes to non-Latin languages. Languages have different semantics and boundaries, especially those with rich morphology or compound words. Vocabularies are different, jargon is country-specific, and even coding systems differ by country. Words are often borrowed from other languages, leading to text that contains a mixture of multiple languages. Written text is a mixture of colloquialisms, local medical terms, and shorthand that is country-specific. Training models to understand these differences and then evaluating those models required significant amounts of clinical data and working with subject matter experts in different languages.

Leumit Health Services, one of the four national health funds in Israel, worked closely with Microsoft's R&D team to train the TA4H model for the Hebrew language. Israel has a unique and robust healthcare system where every individual’s records are stored in electronic medical records (EMR) and all citizen residents are required to join one of the four designated HMOs as per law. The health data available is rich, diverse, and provides a great starting point for research and analysis.

Leumit Health Services had over 130 million patient records in their EMR that could be used for training the Text Analytics for Health multilingual model for Hebrew. The challenge was—how to allow Microsoft access to de-identified data for training purposes in a manner that protected the privacy and security of the customer’s health information. The answer was in a Federated Learning approach—meaning data never left Leumit’s trust boundary and Microsoft was never exposed to patient’s health information. Leumit created a separate subscription in Azure with strict access permissions where Microsoft installed its federated learning infrastructure and tools. Leumit then put in de-identified data needed for the research and Microsoft developers triggered the model training in a federated learning setup on that de-identified data—all the while, this data never left their subscription, and the developers were never able to see any identifying details of the data.

Leumit then became one of the first customers to test the Text Analytics for Health model for clinical Hebrew, which is challenging since it often includes Hebrew and English words in the same sentence. The use case was trying to see if the Text Analytics for Health model could analyze free text from medical visits to identify predictors of strokes in patients. Preliminary results are very encouraging and positive—showing the model has ability to parse through both the Hebrew and English clinical statements and analyze them in a way that could help identify various potential indicators of stroke. This could help care providers set up early warning mechanisms and provide more personalized care for a variety of acute conditions.

“Using Microsoft’s Hebrew NLP, we will be able to analyze our 20 years of EMR data and patient-to-doctor messages to develop tools that will save physicians time and will reduce their burnout in a post-Covid-19 world."—Izhar Laufer, Head of Leumit Start.

Figure 1: Analysis of Hebrew unstructured biomedical text using Text Analytics for Health

Figure 2: Analysis of Hebrew unstructured biomedical text using Text Analytics for Health

 

Analyzing unstructured text for Real-World Data

The challenge of unstructured data is even greater in the research world with the use of Real-World Data (RWD). In Brazil, amongst other places, the lack of a standard for interoperability and data collection leads to a lot of unstructured data—field reports, doctors' notes, and even laboratory exam results. This slows down the process of research and analysis for providers such as Grupo Oncoclínicas. Founded in 2010, Grupo Oncoclínicas is the largest oncology treatment provider in the private sector in Brazil, with 129 units in 33 cities—including clinics, genomics and pathology laboratories, and integrated cancer treatment centers.

With the help of Dataside, a Microsoft partner in Brazil, OncoClinicas is using Microsoft’s Text Analytics for Health to extract data from non-structured fields like medical notes, anatomic pathology, and genomic and imaging reports like MRIs. This data is then used 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.

Figure 3: Analysis of Portuguese unstructured biomedical text using Text Analytics for Health

“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 Groupo OncoClinicas.

Analysis and structuring to Fast Healthcare Interoperability Resources (FHIR®)

The Italian Vita-Salute San Raffaele University and IRCCS San Raffaele Hospital are building the healthcare of the future by leveraging Microsoft’s Artificial Intelligence(AI) services. With Text Analytics for Health, the hospitals can classify, standardize, and analyze the enormous amount of clinical data available at the hospital in order to create an innovative digital platform for data management. Using this platform, the hospital’s physicians can gain important clinical insights about their patients and provide more personalized care. One of the use cases that is currently being developed using this data platform is for allowing the selection of patients eligible for immunotherapy for non-small cell lung cancer. Medical staff can leverage the analysis of AI solutions to increase the success rate of therapy by matching the relevant treatment to the most eligible patients.

“Text Analytics for Health has played a key role in analyzing the enormous amount of unstructured clinical data that we have at the hospital. We are also using the FHIR structuring capability, which allows greater interoperability with other hospital systems. Having Text Analytics for Health available in Italian now allows us to expand our capabilities even further to offer our patients the best possible care.”—Professor Carlo Tacchetti, Professor of Human Anatomy, Vita-Salute San Raffaele University, and coordinator of the project.

Figure 4: Analysis of Italian unstructured biomedical text using Text Analytics for Health

Do more with your data with Microsoft Cloud for Healthcare

With Text Analytics for Health, health organizations can transform their patient care, discover new insights and harness the power of machine learning and AI by leveraging unstructured text. Microsoft is committed to delivering technology that enables your data for the future of healthcare innovation with new features in the Microsoft Cloud for Healthcare.

We look forward to being your partner as you build the future of health.
•    Learn more about Text Analytics for Health.
•    Learn more about Microsoft Cloud for Healthcare.

®FHIR is a registered trademark of Health Level Seven International, registered in the U.S. Trademark Office, and is used with their permission.
Quelle: Azure