Large upfront costs can severely limit the scope and scalability of important projects. With major research institutes that work on projects where substantial volumes of data need to be analyzed, the investment in computing infrastructure for data processing can be a major concern. They need a solution that can ensure the proper scalability of research projects and eliminate the inefficiencies of having to constantly update, upgrade, or downscale on-site servers to address the data needs of specific projects. Fortunately, cloud computing is having an enormous impact on how research is done across the globe.

Watch this video to learn how the elasticity and scalability of Microsoft Azure has allowed genome researchers at Australian National University to access only the computational resources they need while delivering results faster than ever before.

Artificial Intelligence (AI) is the catalyst for the fourth industrial revolution, the most significant technological advancement thus far. AI has the potential to solve incredible challenges for all of humanity, including climate change, education, design, customer experiences, governance, and food. That said, among the biggest concerns regarding AI is the potential for unexpected and unintended consequences in building and deploying AI products.

According to Nate Yohannes, Principal Program Manager for Mixed Reality and AI Engineering at Microsoft, having appropriate representation at decision-making tables when building AI products is critical to help prevent these unfortunate scenarios. From his perspective, representation will go a long way toward preventing the unexpected consequences of AI products, and it will also guarantee that the products that are created will have the widest consumer base possible: everyone.

Listen to this podcast for an inspiring conversation about how to make the possible a reality by approaching AI with a new mindset that takes into consideration its full potential for improving the lives of everyone.

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Organizations that modernize their data estate can reap major benefits, including enhanced security and compliance, significant cost savings, and the ability to empower employees via business insights and advanced analytics capabilities. Organizations that don’t, on the other hand, risk putting themselves behind the curve by missing out on game-changing cost benefits, leaving their businesses open to potential vulnerabilities, and by not taking advantage of modern analytics capabilities.

Read this infographic to learn how businesses are taking advantage of the latest technologies by modernizing their datasets to create transformational benefits throughout their organizations, and discover how they’re doing so by leveraging Microsoft Azure.

View: 3 reasons to modernize your data estate ​

Not so long ago, the drawbacks of storing databases in the cloud were so great that most businesses gave it little thought. Today, the benefits far outweigh the shortcomings, with an incredible array of additional services and solutions now available that provide organizations with unparalleled efficiency and growth potential. Not only is the price-to-performance ratio of cloud software much better than that of on-site servers, but an array of additional services and solutions can also now be integrated in cloud applications.

Subscribe now to learn more about how cloud migration can provide you organization with the scalability and flexibility it needs to support its digital transformation roadmap, as well as how you can reap the benefits of industry-leading capabilities by using Microsoft Azure.

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Data-sharing is an immense enabler of scientific advancements. When researchers choose to make their data publicly available, they are allowing their work to contribute far beyond the original findings. Making research data more accessible also fosters transparency and trust in their work, enables other researchers to reproduce and validate their findings, and ultimately, contributes to the pace of scientific discovery by allowing others to reuse and build on top of the data. Fortunately, cloud technology has made it easier than ever to share data across major research institutions. Empowered by tools that include Microsoft Azure, researchers are relying more and more on digital collaboration and open source software to drive scientific breakthroughs.

Watch this video to learn how researchers at Australian National University (ANU) are using Azure to build on each other’s findings and avoid a siloed approach to data that leads to slower research pipelines.

From autonomous vehicles, predictive analytics applications, and facial recognition, to chatbots, virtual assistants, cognitive automation, and fraud detection, the use cases for AI span dozens of industries. Regardless of the AI application, though, these use cases all have a common aspect. After implementing thousands of AI projects, experts have come to realize that despite all of the diversity in applications, AI use cases fall into one or more of seven common patterns. One of them—the pattern-matching pattern—has allowed machines to digest large amounts of data to identify patterns, anomalies, and outliers in the data, so organizations can unearth previously undiscovered insights in their datasets.

In this article, you’ll learn how pattern-matching is being put to use in today’s organizations to prevent fraud, find the best job candidates, manage inventories in times of crisis, and empower data scientists with new perspectives on how to improve critical processes.

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Hand in hand with digital transformation, cloud technology has seen outstanding growth. Because of the rapid pace of adoption, it has overtaken traditional on-premises hardware. Given the cloud’s huge potential across industries, verticals such as manufacturing, railways, banking, retail, education, and healthcare are switching to cloud services to optimize their reach and performance and increase their flexibility. But moving to the cloud is a strategic move, and it requires organizations to make careful internal analysis in choosing the features that will allow them to get the most out of their cloud migration.

By reading this infographic, you’ll learn more about the most important benefits and features of Microsoft Azure. You’ll also discover how the Microsoft cloud is helping businesses enjoy unparalleled cost savings, easily plan migrations, avoid the complexity of multivendor support, and modernize existing cloud applications.

View: Move and modernize your Microsoft workloads with Azure

One of the main challenges that modern researchers encounter centers on the size of their datasets. As research projects become increasingly more digital, the vast volumes of data that research generates demands enormous raw computing power, for both storage and computational capacity, which most organizations simply didn’t have access to. Cloud technology and artificial intelligence (AI) address this need, allowing researchers to free themselves from the constraints of their physical hardware. Cloud-based approaches can also boost the speed and efficiency of publishing, increasing the impact of research publications.

Subscribe now to learn more about the data management and automation capabilities of the Microsoft cloud and how they’re enabling breakthrough research projects around the world.

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Thanks to cloud technology, researchers can take advantage of faster, more advanced and more scalable resources that enable them to perform tasks that they can’t manage using in-house resources. The cloud also enables scientists to quickly run tests across a variety of platforms and virtual machines with different specifications, which can aid rapid prototyping, interoperability testing, and performance testing. A cloud solution can also provide researchers with ways to augment their existing resources by handling peaks in demand and reducing competition for local resources, when multiple teams are working toward an upcoming deadline. By reducing dependence on on-site computing, research projects can increase efficiency and scalability, and deliver greater results faster.

Watch this video to learn how Australian National University (ANU) is using Microsoft Azure to help decode more than 7 billion base pairs of DNA in the human genome and take its research further than ever before.

Thanks to AI, business applications will soon be able to answer complex questions, help users navigate interfaces, and enable cloud vendors to reduce support from personnel to manage their loads. AI is also being used in various software applications to help decision-makers identify and automate repetitive tasks, improving employee productivity. Increased understanding of how to better implement AI in business applications likely will lead to the emergence of new features, such as natural-language processing (NLP), that can help managers interact in more-intuitive ways with AI-powered apps.

In this article, you’ll learn about the innovative features powered by AI and machine learning (ML) that you can expect to see in business applications in the next five years.

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